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Remote 5en5ing for Coastal Resource Managers: An Overview "T 300 4A, I F 54 I rl, 1997 GC 10.4 ;artment of Commerce R4 R46 I Oceanic an6i Atmoopheric Adminiotration 1997 1 Ocean 5ervice c. 3 ORCA Organization A Conterlte The Office of Ocean Resources Conservation and 1. Introduction ...................................................I Assessment (ORCA) is one of four line offices of the National Oceanic and Atmospheric 2. What is remote sensing? ................................3 Administration's (NOAA) National Ocean Service Ocean Color ..................................................5 Sea Surface Temperatures .............................6 (NOS). ORCA provides data, information, and Circulation .................................................7 knowledge for decisions that affect the quality of Wave Height ................................................8 natural resources along the nation's coasts and in Sea Surface Winds ......................................8 Sealce .........................................................9 its estuaries and coastal waters. It also manages Coastal Land Cover & Wetland Mapping...9 most of NOANs marine pollution programs. ORCA consists of three divisions and a center: the 3. Relationship to Coastal Resource Strategic Environmental Assessments (SEA) Management ......................................... 13 Division; the Coastal Monitoring and Bioeffects Environmental Monitoring ...................... 13 Resource Inventory and P apping ........... 14 Assessment Division (CMBAD); the Hazardous Damage Assessment ................................. 15 Materials Response and Assessment Division Protected Area Management ...................... 15 (HAZMAT); and the Damage Assessment Center Coastal Hazards ................................... 16 (DAC), a part of NOAA!s Damage Assessment and 4. Realities of Acquiring and Processing ......... 17 Restoration Program. Data Realities ...................................... 17 Acquiring and Procesing ......................... 19 The kernote 5en6ino Team 5. Concluding Thoughts ..................... ................ 21 Walton B. Campbell Current Requirements ......................... 21 Joann M. Nault A Look Toward the Future ......................... 22 Robert A. Warner 6. Additional Reading ...................................... 23 <1 Acknowledgmente, 7. Glossary ............................................................ 24 The Team thanks the following SEA Division per- 8. Summary of Appendices ............................. 29 sonnel: Daniel J. Basta (chief), and Charles Alexander, for providing guidance and direction throughout the process of developing this report; Pam Rubin, David Lott, and Davida Remer for their assistance in its production. Substantial insights and two figures were contributed by external review- ers Victor Klemas of the University of Delaware, Ken Haddad of the Florida Marine Research Institue and Donald Field of the NOAA Coastal A On the Cover Services Center. A hioh-rcoolution 5atellite imaec of FlorWa bay (Decernber 1995) u9ine KVR-1000 inotrument. Captain Key iq located at @ottorn leftthe Manatee Key5 areat upperri0ht. Thea@ovc- water lan I jo clearly outlinci, while the oul@mcrecd cora I, oand and mucl arcao appear much liohter. Parker oh3cle5 of blue indicate cleelper watem andlor dark-colorc6i veectatiori (ter- rootrial or oul@rnerocd). Averaoc rcoolution i5 2 metcro per pixel (note 300 m ocale @ar). Remote 5en5ing for Coaotal Re5ource Manager5: An Overview This report presents an overview of satellite-based re- mote sensing technologies, and discusses their poten- tial as tools for assessing, managing, and protecting Introduction coastal resources. While remote sensing has proven useful in open ocean applications, it is an under uti- lized, yet very promising, technology for use in coastal regions. This overview focuses on the available sys- tems, capabilities, and limitations of satellite-based technologies because they can be cost-effective methods for collecting environmental data. Once in service, satellites are usually a continuous source of information for many years, providing decade-scale monitoring of natural and man-made changes in ecosystems. This document is intended to provide coastal managers with sufficient detail to evaluate whether or not remote sensing can provide useful and usable information concerning their specific coastal issues. In addition, this overview is intended to be a ready reference for coastal resource managers and their assistants who have heard or read that remote sensing is the answer. Many resource managers have not had time to stay abreast of the rapidly developing technologies involved in remote sensing. Yet, they find themselves in the position of needing to resolve specific environmental problems in regions which are: difficult to gain physical access to; do not lend themselves well to conventional manual sampling regimes; so large they cannot be plausibly studied within time constraints; or are in need of a change analysis with no previous on-site sampling having been conducted. The different classes of instruments employed in a variety of satellite systems are discussed in the context of their application. Since most of these space-based sensors were not developed specifically to replace traditional manual coastal environmental assessment techniques, they have design and physical limitations for near shore applications. Additional limitations (such as whether or not they wil I be useful on a cloudy day) are also discussed. The realities of obtaining and utilizing remotely sensed data are reviewed. Since remote sensing and space science are highly technical arenas, they have generated their own lexicon of acronyms, which are explained in the Glossary. Five appendices provide tabular sum- maries of past, present, and proposed future space-borne environmental sensor systems. The coasts are used by many individuals and industries for many different purposes, thus, the term coastal has many different meanings depending upon the intended use. For the purposes of this docu- ment, the term coastal will be confined to include the waters adjacent to the coastline (mean high water mark) out to where the open ocean processes dominate (usually the 200 meter isopleth). This definition of coastal is meant to include estuaries, harbors, inlets, embayments, lakes, and swamps; but exclude areas along the shoreline which are above the mean high water line. Electromagnetic opectrum u5eJ for remote eenoing Generally, active and passive detectors in sate] li te-mounted instruments are sensitive to the optical (0.4 - 0.7 @Lm), near-infrared (0.7,- 0.9 @Lrn), infrared (0.9 - 12 gm), and microwave (0.3 - 30 cm) portions of the electromagnetic spectrum. Within this range of the spectrum, data from the sensors are used to detect four basic properties of the ocean: color, temperature, height, and roughness. Many applications have been derived from the quantitative detection of these properties. The images shown on the cover and in Figures 2-4 and 7-9 were produced from satellites with visible and thermal infrared optical sensors. Other remote sensing instruments provide information from parts of the electromagnetic spectrum beyond the visible and then-nal regions. Microwave instru- ments, such as Synthetic Aperture Radar (SAR), can be used to map oceanographic features includ- ing ice fields, internal waves, fronts, eddies, and coastal habitats(Figure 9) in all weather conditions. The high-resolution SAR instrument has been used to detect oil spills, locate ships, monitor the topography in the ocean surface to detect changes in the coast, and map the bottom topography of shallow water. When data from multiple sensors is integrated, the product (Figure 3) can provide additional environmental detail, such as when sea heights (from altimetry) and temperatures (from infrared detectors) arefused to study circulation dynamics. Wave- length <.0003 @tm .001 -.01PM .01 -.4 @Lm 1.5-Imm I Mrn - 0.8 in 0.8 in > Infrared Microwave VHF Radio L Near Infrared Y Rays X Rays 0.7 -1.5 Wn Visible 0.4 -0.7 PM Most remote sensing instruments utilize portions of the electromagnetic spectrum 0.4 pm Visible 0.7 pin (bands)from the visible to the relatively L long microwave wavelengths, 2 Remote sensing is the science of gathering infor- mation from a distance. Eyes and ears are remote 2 sensing instruments. Vision is a form of optical re- What is remotI6 mote sensing; listening is a form of acoustical remote sensing. Remote sensing makes use of a wide variety 5ensing? of media and technologies: radar is a type of radio energy remote sensing, and X-ray photography is a form of high-energy remote sensing. In the case of eyes and ears as remote sensing instruments they are passive detectors and rely upon other phenomena to supply the energy (room light or a car horn). In contrast, radar and sonar actively broad- cast their own energy source and derive- information from its reflection and scattering. Information is produced by processing and interpreting the data arriving at the instruments. Satellite remote sensing is used to obtain information about, and to take measurements of a place or phenomenon without direct physical sampling. The desired end product of photogrammetry* and re- mote sensing is scientifically valid, quantitative analyses derived from the data. A few of the environ- mental products derived from satellite remote sensing include: descriptions of current weather condi- tions; the status of wetlands habitat; coastal erosion processes; the location of oil spil Is; and the extent of algal blooms. Satellite imagery can be valuable for observing large expanses and/or inaccessible areas. Ocean features such as large-scale circulation, currents, river outflow and water quality; can be visualized by highlight- ing variations in water color and/or temperature. These observations can then be used for such activities as ship routing, environmental monitoring of sensitive coastal zones, hazards assessment, and manage- ment of fishing fleets. High-resolution coastal images can be used to analyze and map sediment trans- port, bathymetry, erosion, and aquaculture applications; however, several of these are possible only when the skies are clear. Applications of remote sensing to Remote Sensors View Earth coastal management activities in- Reflected clude infrared imagery to monitor MM Microwave 2-@-S #Yn, %Radiation changes in vegetative habitat; data on water temperature and color to K better understand fish and inverte- brate distributions; and real-time at- TO and ure mospheric data for weather fore- Y casting. Remote sensing techniques are becoming increasingly cost-ef- fective, given the rapid pace of in- novation in computer technology, information networks, and improve- ments in sensing systems for satel- lites. Figure 1, Oepiction of how remote 5ciisoro view the Earth. Courteey of .the U.5. Office of Tcchnolooy &55coomcrit. the science of making reliable measurements by the use of photographs and especially aerial photographs. 5ome Remote 5enr7lng Term5 Resolution: 0 Spatial is the parameter which describes the correspondence between the size of the spot on the ground viewed by each individual picture element (pixel) in the sensor on-board the spacecraft and is a function of altitude, lens geometry, construction of the sensing array, etc. (a I krn pixel may be useful for observ- in- the location of the Gulf Stream, but would be of no use in distinguishing among the different physi- Z@ c, cal habitats in a 2-4 km wide estuary). Temporal defines the number of repeat passes an imaging system may provide over the same location (a ZI satel I ite which provides repeat coverage of every other day may be sufficient to follow processes which have time scales of days but will be of limited use in observing change events which occur over only a few hours or during a tidal cycle). Radiometric is the number of data bits used to represent the intensity of the signal arriving at the sensor (a 4 bit representation or 16 levels of the full range from full brightness to full darkness is much less than Z@ that in an 8 bit or 256 levels radiometric resolution instrument). Spectral is the description of the instrument in terms of the number of different wavelengths each sepa- rate channel can detect and the width of each one of these (an 8 channel instrument with very wide channels is much less useful than an instrument with many, very narrow channels). Geoetationary ve. Polar Orbiting: The concepts explained above are not independent of one another. Ob- serving satellites in orbit around the earth are generally placed into either of two different types of orbits. The traditional weather satellites as seen on TV are placed into an orbit such that, when viewed from the ground looking up, they appear to be stationed above one place on the surface as a consequence of their velocity through space matching that of the rotation of the earth. Thus, these are called geostationary satellites and have the advantage of being able to view one side of the planet continuously from their 39,000 krn altitude. Geostationary satellites have very high temporal resolution and very wide viewing swath (one complete scan of one side of the planet every few minutes) but their spatial resolution is very low by virtue of being so high above the planet and their spectral and radiornetric resolution are usually quite low to ensure rapid data transmission sufficient to identify rapidly moving storm fronts. The other common orbital configuration for observing satellites is that referred to as Low Earth Orbiting (LEO) and is most commonly employed in near-polar orbits (canted to pass just to the East or West of the poles of the planet). While near-polar orbiting LEOs can view only a narrow swath as they speed by (low temporal resolution), they are able to collect imagery from the entire planet by virtue of the earth rotating underneath while the satellite collects non-repetitive imagery on succeeding passes. Near-polar orbiters, being much closer to the earth (800 km altitude) than geostationary satellites, also tend to collect much higher spatial resolution imagery. Ocean Color (instruments sensing the vioil7le portion of the s pectrurn) The colors of ocean and coastal waters provide infor- mation as to their contents, and thus, their recent his- 15-MAR-79 tory and possible present productivity. Clear waters do not contain much suspended material, such as al- gae or silt; opaque, muddy waters indicate high con- centrations of suspended sediment; and bright green waters normally indicate dense concentrations of al- gae, typically phytoplankton. These microscopic plants are important because they constitute one of the low- est trophic levels of the marine food web, and are, in- volved in many geochemical processes including fixa- tion of carbon and nitrogen. The observed color of water results from many phe- nomena: among them, the reflection and absorption U.U4 0.50 LDU 3.00 9.UO of sunlight off of phytoplankton, suspended minerals, Figments [mg/m3] organic complexes, and dissolved organic and inor- Fioum 2. Ocean color ima0e, Eactern Gulf of Mexico, ganic materials. The narrow, visible portion of the Nim@uo-7 (CZC,5)1Univ. of 5outh FloriAa, March 1979. electromagnetic spectrum is used to record ocean color (Figure 2), which can be measured only during daylight hours in cloud-free conditions. The atmosphere between the water and the sensor also affects the quality and quantity of light detected at the sensor. To ensure accurate calibration of the numbers from the remote sensor, it is necessary to obtain frequent, in situ measurements of the waters being remotely measured. Typical coastal applications of ocean color monitoring include quantitative estimates of riverine input into estuaries, coastal erosion (the magnitude and direction of sediment transport), and the location and extent of human impacts on the marine environment. However, the geographic scale of coastal events is often so small that the spatial resolution and/or radiometric sensitivity of current space-based sensors are of minimal utility to coastal resource managers. In the near future, sensors such as SeaWiFS on SEASTAR, MOS on PRIRODA, and OCTS and POLDER on ADEOS should provide sufficiently fine detail to permit the location of algal blooms, including toxic red tides, fish stocks (because many planktivorous fish aggregate near the food sources), and ocean fronts and eddies (see Table I for sensors and applications). Coastal Regions Coastlines (ocean, lake, river) vary widely in their geomorphology, biota, and hydrology and thus, the precise definition of coastal depends upon the phenomena under evaluation and the region of observation. Applications of coastal remote sensing are discussed throughout this document and the resolution of various sensing systems is rated relative to its applicability for specific tasks. For example, 4 km spatial resolution remote sensing system can be adequate for imaging storms moving across the middle of North America, but are of little use in discerning details of the Florida Keys (most of which are less than I km wide). The need to locate a 500 in long oil spill requires finer resolution imaging systems than ones following meanders of the Gulf Stream (found off the East Coast of North America). A 5ea Ourface Temperatureo (infrared, microwave) The surface temperature of ocean and coastal waters may provide information as to the waters' origins and recent history. Waters upwelled from great depths are cold, nutrient-rich, and clearer than the sur- rounding water. Many of the world's major surface currents are warmer than the adjacent water masses. In coastal areas, sea surface temperature (SST) measurements can locate coastal upwellings, fronts, river outflows, and intrusions of water masses. Regional SST measurements are useful for identifying the location and area] extent of major currents (e.g., Gulf Stream, Labrador Current) and their associated eddies and meanders, and major upwelling events (e.g., Peruvian upwelling during non-El Nifio years). The very narrow infrared portion of the electromagnetic spectrum is typically used for high-resolution temperature observations, which can be made any time of day but only under cloud-free conditions. Thermal infrared energy from the sun reflected off the water's surface can lead to daytime interpreta- tion problems. Passive microwave sensors can measure water surface temperatures through clouds, although with a significant decrease in thermal accuracy and spatial resolution. To ensure accurate cali- bration of the temperature numbers from the remote sensor, frequent, in situ measurements are re- quired. Remote sensing systems can view only the top few SST NOWNESDIS EDGE ORID RWX DISPLAY 20.32 LAT 14KM ANAL. GLAY OF CA-IF. / NOAA-14 OPEPAT -136.-105 LON millimeters to centimeters of the water and thus, can- M/13/96 ZW - 06/17/96 ZWO 95 HOURS not provide information on subsurface temperatures. Making use of temperature remote sensing techniques for coastal waters requires high resolution data because of the small spatial scale of the land and its adjoining water masses. Many coastal areas are so calm that the water surface maintains a constant temperature for months at a time, rendering thermal imagery of little use. Due to their low spatial resolution, the current SST- sensing satellites are of minimal utility for coastal ap- plications. Currently, AVHRR on TIROS and ATSR on ERS provide the data that is used predominantly for regional and ocean-basin SST determinatioris (Fig- ure 3). The ATSR provides a more accurate measure- ment, while the wider viewing swath of the AVHRR (2,580 km) provides more coverage. Sensors such as OCTS on ADEOS (12 channels, 700 m resolution) and L9 2M 22 24 the soon to be deployed MODIS on EOS (36 channels Figure 3. Sea 5urface ternperasure (14- km analy@i5), at 250 m resolution) should improve available spatial Gulf of California, NOAA-14/NOAA/NE5Pl5, June 1996. and spectral resolution significantly. Circulation (altimetere) There are several physical reasons for the movement of water from one place to another, such as wind stress, tides, and density discontinuity. Intense and/or lengthy windstorms crossing the surface of a regional body of water can push large quantities of water away from one area and pile it up onto another, such as a shore or embayment. In coastal areas-particularly in regions where the bottom shallows over a very short distance and/or the entrance to an embayment narrows abruptly-the daily ebb and flow of the tides can produce substantial changes in the elevation of the water across a short distance. Several phenomena can cause water masses to have differing elevations from those around them. One of the most consistent and significant is the gravitational attraction of seafloor mountains and canyons. Undulations of local mass of the earth, and therefore differences in this gravitational pull, are referred to as the earth's geoid. The more massive mountains attract more water above them; canyons attract pro- portionately less. Altimeters in orbit provide high-precision (3 P, 91F W V cm) information on the height of various water V74 77 masses and the earth's geoid. The location and motion of large-scale water masses, such as Gulf Stream eddies or the Gulf of Mexico Loop Current, can be visualized using satellite-borne altimeters (Figure 4). On a coastal scale, knowl- edge of the velocity and direction of parcels of 2%, water known to contain toxic red tide algal blooms or hazardous materials (e.g., spilled oil, industrial waste) is essential to planning an % appropriate response. Additionally, data on -10- ocean circulation is a significant component of global climate programs. Since they are active microwave instruments, which calculate the round trip time of a pulse transmitted from a satellite in space, altimeters are usable in all weather conditions. With the Figure 4. 5ca level height differenceo ae deterrnineJ from Topex development of higher spatial resolution altim- altirmeter data euperirripooccl over AVHKR temperature image. eters (presently one measurement every 25 km) Relative, heighro above andbelow mcan are. repre5ented by line and/or deployment of a larger constellation of l,,01h, proportional to the maonituclc of the water 6urface instruments, remote sensing could be used to elevation (to the right of oatellite track) or deprcooion (to the left of satellite trick), Gulf of Mexico, -l`6pcx/N0AA/N05, study coastal processes for resource assess- December 1995. ments such as beach erosion, salt-marsh sub- sidence, and barrier island expansion. Wave Height and Opectrum (altimetem and 5AR) @'.j *ivint Vve Hei&r. (M) Wave height is dependent on the velocity of the wind, V__'= the distance over which the wind blows (fetch), and M + rr. 6 M 8 M 10 -r m ?1@ the length of time it blows. Wave direction, average Z7' wave height and wave spectrum data are very use- ful, both as inputs to predictive weather forecast models and for real-time information about sea con- ditions. Sea state is an important consideration when planning any at-sea operations such as search-and- rescue, response to hazardous material releases, ship routing, oil drilling, and dredging. Satellite altim- eters provide only limited wave height infon-nation (Figure S) due to poor spatial resolution (25 km). These active microwave instruments derive wave information from the shape of the reflected micro- wave pulse transmitted from satellite to the water. Figur'e 5. Wave height, North Pacific Ocean, Wave Mociel/ Thus, they will function in all weather. FNMOC, March 199ro. 5ea 5urface Windo (5catterornetem) r Information about the velocity of coastal and ocean 0 5 W 15 20 25 30 35 winds is important in resource management. This is especially true during response efforts to hazardous materials releases, since disasters seldom happen in ideal weather. It is also useful in weather forecasting, ship routing, and air-sea flux studies (Figure 6). .............................. ........ Winds transfer some energy to the surface layer of the sea, causing ripples. The ripples can develop into wavelets and waves in proportion to the direction and magnitude of the wind. Scatterometers compare a mi- crowave pulse transmitted from a satellite with the waveform of the reflected pulse to extrapolate a wind speed. They lack sufficient spatial resolution (7-50 ....... . .. ........................... .. ..... ...... ......... km) to be of direct use in near shore coastal processes, 30 -70 but they can provide warnings of surface wind con- Figure 6. Wind opeei, U.S. Northeaot; coa5t, ER5-1/ ditions that may be headed toward shore. Previous NOAA/NE5[)15, June 1996. generations of scatterometers were limited by a single- side field of view. With the launch of ADEOS, this wind direction limitation should be minimized due to its dual-sided viewing NSCAT instrument. A 5ea Ice (optical, infrared, microwave) Nearly 12% of the world's ocean is covered by sea ice, the properties of which can differ greatly from both the land and the liquid water. Sea ice may be distinguished from the surrounding water by virtue of its being more reflective, lower in temperature, and different in texture and salt content. Using these properties, optical, thermal and especially microwave (because microwaves pass through clouds or fog for all weather capabilities) remote sensing is employed for ice investigations. The location, formation, melting, movement, 0 and thickness of ice in coastal waters are im- portant to organizations conducting ocean or i lake surface activities (disaster mitigation, transportation, fishing). The principal con- cerns in ice observations are ice concentra tion, thickness, and the locations of the edge, polynya (areas of open water), and open leads (channels) (Figure 7). The areal extent of ice *0 coverage is used for input to climate models. Visible and infrared observing satellites (TIROS, ASTR, GOES) can be used for moderate reso- lution (1-4 km) data, but only under cloud-free conditions. Passive (SSM/I) and active (SAR) microwave imagers can produce ice imagery products in all weather, but are currently lim- ited by poor resolution (12-25 km) and narrow swath widths, respectively. Figure 7. 5ca iGe (near infrared), Larw IGe 5h6f, Ant;arctica, AVHRR/N5IDC, March 1995, Coa5tal Land Cover and Wetland Mapping (optical, infrared, microwave) Habitat mapping and classification by means of remote sensing are performed by correlating a cluster of numerical pixel values with verified features, such as vegetative cover, open water, tidal flats, inland marshes, forested wetlands, or bare soil type. Multispectral. sensors such as Landsat's Thematic Mapper (TM) and SPOT have been the traditional instruments of choice for these types of mapping projects over relatively large areas (Figure 8) (e.g., estuarine sediment/dumping plumes, shallow-water bathym- etry) because of the relatively high spatial (20-30 m) and radiometric resolution (eight bits), and be- cause the visible spectral bands are co-registered with the infrared channels. These passive optical instruments are unable to produce land/water imagery during cloudy weather. Developed, High Intensity Developed, Low Intensity Grassland Cultivated Land Evergreen Forest Scrub/Shrub Bare Land Estuarine Emergent Palustrine Emergent Palustrine Scrub/Shrub Palustrine. Forest Water Unconsolidated Shore Mixed Forest Deciduous Forest Figure 8. Land Cover, Waohington 5tate, Landoat; TM/NOAA1C5C, 56p@,em@er 1992. The Synthetic Aperture Radar (SAR) in- struments on ERS-1, JERS-1 and RADARSAT also show promise in pro- viding higher spatial resolution (10-30 in) data for wetland mapping and classifica- tion for fine scale coastal regions (Figure 9). These instruments rely on reflected microwave energy from the earth to pro- vide an image. Land and water bound- aries appear in sharp contrast in SAR imagery because the water tends to re- flect energy away from the sensors while rough textured land scatters transmitted signals. Soil moisture and plant type pro- duce differential (gray shade) absorptions of the microwave energy providing coastal surface habitat information in all weather conditions. Figure 9. Coaotal 5AK Irria0e, Tromoo Norwiy, January 1996. KAPAK5AT data Canadian 5pace Agency 1996. Pata received by the Canada Centre for Rermote 5cnalng. Proceosc,@ an i diatributeJ @y RAPAR5AT International. 10 TaWe 1. 5eieote,@ platformfsem5oro an@ traolitional coaotal ar6i. ocear, applioatior!5 Plalform Serw@. An lica,,;on So S.- tace Wave surface sea Icc Lznd Cove-/ MI& welan& ERS-1 2 AMI-SCAIT, RA RA SAR ... . ........ .... . ... ... INSATI IVIFRR .. .......... GCES 7 VAS I.- ....... ..... .. .......... .... ....... VISSR JERS-1 OPS 0 SAR ................... . ',V@A I& TIM ... .... ... ........... . ME-I, OSATI 3-7 MOS-lb Mm I-- . .... ........... V TIR NOAA 9-14 AIM HM .... . ....... ......... . ..... . OKEMN-01 RLSDO -os RESOLRCE-01 V2 &:,\3 NSL;-E WU-SK ........... ........... . .. nV TOPEX/pOSE1001%, ALT SALT 0 ..... . .... . .... GOES 9 K-V NAGER FOODA DLkR-,\*, R-0 DCAM, R-W Mos SAR . . ... ..... . ... ........ @@M@T SASTA@R SEAWJ-S SICH-1 %U-M MSU-s ...... ........ RIM-0.8 ADEOS AVNIR OCTS 0 POLM .......... NOA.A X-M ANZU B 0 TaWe I (cont.). 5electe6i, pil,,@itfo,m-nJoemoor5 am,@, ocean applicatiorlo Platform Sensor Application 00em C010- Sea Swface Cucuktion wave Surface Sea Ice lwid Coval Heights ffzlds Wetl;inds NOAA K-N AN(SU A AVHRR/3 ....... . ... .... ... ... ..... ... ... HM/3 %0 NTj-S ........... .NM-SK MSUN FY-2 VIS & IR 6 ICH-2 SAR SICH-3 SIX SPOT, 1-MIR ----- -------- -- ------- VEG ENRqSAT-I AATSR ASAR DORS RA-2 EOS-A.Ml ASM MOMS EOS-CCLOR OCEAN COLOR .... ........ .. . ........ . . ....... . ..... . FY-IC VIS & IR LANDSAT7 -rN.+ 8 ADEOS U ANGR 0 .. . ........ POLDMR SEAMM MALT DORIS SSET. FY-ID MS VIS IR !6G SMIC EOS-pm AM AMSU .MNR .. .. .... . ..... MODIS SPOT 3 HRG VEG or-AN, 12 This section describes existing and potential rela- tionships between remote sensing and five repre- 43 sentative examples of issues facing coastal man- to agers: (1) environmental monitoring; (2) resource Relationghip inventory and mapping; (3) damage assessment; (4) protected area management; and (5) coastal haz- Coa6tal Re6ource ards. It includes a discussion of limitations of cur- rent remote sensing systems as well as key, soon- Management to-be-launched satellites which should provide a plethora of datasets with spectral, spatial, and ra- diometric resolutions to be of direct value to the coastal resource manager. Environmental Monitoring Coastal environmental monitoring includes a wide variety of activities directed toward understanding the status and trends of environmental quality. Examples of measured properties include: water tem- perature, salinity, sediment loading, rainfall, water quality, and the presenc@/absence/ health of plants and animals. Monitoring is conducted in many different ways depending, in part, on the parameter(s) being measured, the monitoring objective, and the resources available to conduct the work. Remote sensing can, under certain conditions, contribute to environmental monitoring by allowing managers to obtain repetitive, nonintrusive, synoptic data for some parameters across broad spatial and temporal domains. With respect to water quality, certain sensors can provide managers with data on water temperature, clarity, circulation, depth, and productivity. Multi-spectral sensors on satellites such as Landsat-MSS, Landsat-TM, SPOT-HRV, and ADEOS-OCTS are already providing quantitative in- formation on water color that can be applied to investigations of sediment plumes and transport, algal blooms, and point sources of pollution. Point sources of pollution are typically detected by recognizing characteristic surface patterns within the water body rather than by a simple analysis for anomalous spectral properties. Pollution detection is more difficult if it has had time to disperse over a large area, or when it does not emanate from a concentrated point source. In such cases, remote sensing can be used to quantitatively compare spectral properties of similar, unpolluted water from elsewhere, or to evaluate images of the same area that predate the pollution event(s). Both methods are constrained by the high natural variability of the coastal environment. Thermal sensor bands, such as AVHRR on the TIROS satellite series can provide data on water temperature that can help track large (greater than 5 km) coastal upwellings, river outflow, and major coastal currents. Presently, there are substantial limitations in the availability of high spatial resolution, multi-spectral and thermal satellite image data. With the near-term expectation for the launch of high resolution satellites including Earlybird/Quickbird (3-15 m, due in 1997-98), Lewis/Clark (3-30 in due in 1997), and EROS (1.8-11.5 in due in 1997) many of these problems should be overcome. A A Coastal Management In the U.5. The U.S. has extensive coastal boundaries with the Atlantic, Pacific, and Arctic Oceans, the Gulf of Mexico, and the Great Lakes. The majority of the population is located either directly along these coastlines or within the associated waterways, embayments, and estuaries which presents the potential for widespread environmental stress to these regions. Since the enactment of the Coastal Zone Management Act in 1972, the U.S. has expended increasing resources to manage these regions and understand how they are chang- ing under our stewardship. Coastal management includes a broad range of activities that typically occur among and across Federal, 0 state, county, and municipal levels of government. These include the promotion and regulation of recre- ation, land development, and transportation as well as the protection of property and life against natural C, hazards both on the land borderin coastal waters as well as in and on the water itself. The coal of coastal 9 C, management is to achieve a balance between conservation of resources and sensible development in order to ensure the optimal and most sustainable use of these unique regions for current and future generations. As priorities and technologies change, this is an ongoing, dynamic process that requires constant evalua- tion and revision. Resource Inventory and Mapping Environmental inventory and mapping is performed to establish a baseline description of resource spa- tial distribution and abundance, from which to determine trends, and identify priorities for management. Coastal resources that are often inventoried and/or mapped include wetlands, harvestable resources such as timber and oil, birds, finfish, and shellfish. Inventories are typically conducted using a combina- tion of extensive field work (e.g. species collection from specific sampling sites), data cataloging, and mapping. Inventory of living marine resources by space-borne sensors has had variable degrees of success. Large pelagic species of fish which form large schools near the surface can be readily imaged by satellites, but many near-shore fish schools are relatively small compared to the spatial resolution of current satellite imaging systems (30-1000 m). However, satellites can identify a number of environmental variables associated with habitat that are potential indicators of distribution and abundance such as water tem- perature, water clarity, circulation, the location of fronts and eddies, and the presence of coastal veg- etated habitat such as wetlands and sea grasses. Sub-surface habitats such as corals, shellfish beds, and sea grasses are more difficult to quantify by satellite than those above the water line because the space-borne sensors can image only that electro- magnetic energy which makes it up through the water column. Thus, turbid waters present significant limitations in the ability of remote sensing systems to quantify bottom features. Mapping wetlands with satellite imagery provides a number of advantages over conventional ground surveys or aerial photogra- phy including: timeliness, synopticity, frequency of repeated observations and significantly reduced costs. 14 Parnage Aose5rrnent Environmental damage assessment typically involves evaluating impacts on coastal natural resources resulting from natural events as well as from human activities. These include: long-term exposures to pollutants, cumulative changes caused by certain land use practices, and episodic events such as oil spills, ship groundings, flooding, and hurricanes. Satellite remote sensing derived inventories of existing resources can be crucial in establishing the before and after status of a region to quantify the extent of damage. Such baseline studies are also useful for identifying areas that may be particularly susceptible to damage such as a sensitive habitat located close to shipping lanes, or densely populated areas that are subject to storm surge inundation. This information can improve the effectiveness of management decisions with respect to preparedness and response. Remote sensing can be of value to managers in tracking the movement of air or water-borne hazardous materials releases. Large surface oil slicks are routinely imaged by TIROS/AVHRR, Landsat, SPOT, ERS-l/SAR, RADARSAT/SAR satellites, but oil type, age, slick thickness, sea state, and the satellite's viewing angle can limit remote sensing's ability to quantify or locate oil spills. For a meaningful response to hazardous materials spills, managers need timely access to data on its size, position and trajectory. Frotected Area Management Sanctuary areas managed by various Federal, state, local, and private institutions have been set aside for special use and protection because of their environmental, recreational and/or historical value. These include parks, recreation areas, wildlife reservations, and marine sanctuaries. Managers of these areas are typically required to balance the needs of public access and use with natural resource conservation and protection. The goal is to ensure that these areas and their associated natural resources are protected and, where possible, enhanced for future use. Several remote sensing applications for protected area management are described above (e.g. Environ- mental Monitoring, Resource Inventory and Mapping, and Damage Assessment). Additional applica- tions include monitoring public use, particularly in expansive marine areas where access is difficult or impossible to restrict, assessing the status of protected area resources with respect to adjacent areas that are not similarly protected, and evaluating the effectiveness of various management strategies. Such information can provide critical early warning information regarding the possible need for additional protective measures. Direct monitoring of public use in coastal areas through remote sensing is usually restricted to identify- ing the presence/absence of boats in open water. This type of monitoring is possible only with ex- tremely high resolution media such as aerial photography or classified satellite imagery. Some coun- tries (including the U.S.) use this technique to assist with the enforcement of fishery regulations. Such monitoring may become a routine resource for coastal managers with the anticipated launch of several high resolution commercial satellites (see Environmental Monitoring) and the potential availability of at least some of the imagery from previously classified space-borne sensors. 15 Coaotal Hazard5 Coastal hazards are natural phenomena that have the potential to impact natural resources, property, and the quality of human life. These include coastal erosion, flooding, storms, and salt water intrusion. The proximity of population centers to the coasts accentuates the perceived effects and real costs of coastal hazards. Imagery products are often invaluable in determining response priorities during emergency situations. Because of their synoptic coverage, satellites are also quantitative tools for post mortem damage assessments to property and resources. The primary application for remote sensing to coastal hazards is the forecasting and analysis of local and regional wind and rain events. Landsat and SPOT satellites currently provide synoptic, regional imagery that can help managers identify natural resources and property at risk. A time series of such imagery may help identify local patterns of shoreline erosion and/or accretion, or plant community successional events. Understanding these patterns may be particularly important in some regions since coastal wetlands such as salt marshes and mangroves can mitigate the severity of coastal hazards from waves and flooding. Coartal Nutriemt Emrichment Coastal regions are not only delicately balanced ecosystems, but are a primary location for introduction of nutrient-laden or toxic materials such as domestic sewerage, agricultural runoff, and industrial waste. Supple- menting the concentrations of nutrients (which would otherwise be limiting factors for growth, such as phosphorous, nitrogen, or silicon) or poisoning key species in any stable or metastable environment gener- ally produces biological imbalances. Left unchecked, these conditions can produce massive die-offs of many of the native organisms and alter the local geochemistry (pH, Eh, alkalinity). This may lead to oscillations in species composition and even the habitat's suitability to sustain long-term, stable populations. Accelerated erosion of the underlying substrate is a common outcome of loss of biological stability and diversity, resulting in permanent loss of habitat. While it is presently not possible to measure nitrate, phosphate, or silicate concentrations (much less pH, Eh, or alkalinity) from an aircraft or satellite-borne system, the effects of changes in their values on the biota are frequently easily observed by visible spectrum (and fluorescence spectroscopy) remote sensing techniques. Red tide and green algal blooms are readily detected, located, and quantified by ocean color sensing systems (see section on Ocean Color). Algal blooms which correlated with cholera outbreaks have been identified by use of ocean color sensors. Although the remote sensing systems mentioned above and described in Appendices A through D rely upon 4 very different phenomena to provide information about the coastal environment, they have several issues in common with regard to getting from a number sent Realities of by the sensor in space to a usable product for the ana- lyst or resource manager. This section describes the Acquiring processing steps required before remotely sensed data can be utilized by the analyst or resource manager. and General processing considerations are briefly outlined below, followed by a typical 6-step processing sce- Proce5sing Data nario. Ten to 32 weeks is a realistic time frame for implementing such a project (Figure 10). This time frame largely depends on an organization's experience and/or the number of steps that have been provided by others (e.g., data providers, software programs). Processing of photogrammetry and remote sensing information is composed of several related compo- nents: hardware; software; personnel; and data. As with most things, the more that is desired and the quicker it is needed constitute the principal cost drivers. Thus, if the data has been preprocessed (irre- versible mathematical transformation) to a high level by the data providers (high cost), then entry level personnel (low cost) can use fully developed software (high cost) running on a moderately powerful hardware system (low cost) to produce standard (defined by the software manufacturer) products. 4@A Pata Realitieg � Incoming data: Each data provider typically has several levels of processed products, so that data must be carefully defined. The timeliness and convenience of directly receiving data has, historically, been offset by the cost of establishing and maintaining a large, complex receiving station. With the rapid development of hardware and software ingest systems, it is now cost-effective, in some instances, to purchase a complete download station and data license (if required), rather than to submit data orders and await delivery. � Data Proceoeing/Display: The appeal of raw data is the ability to apply one's own calibra- tion/navigation formulae to it, in contrast to using standard algorithms from some data pro- vider (often full of errors). It is virtually impossible to return to the original data quality once it has been processed (think of a food processor!). The disadvantage of this approach is that the user must possess the hardware, software, and personnel resources to perform these steps before the data is usable. 17 Nevertheless, the costs of hardware, maintenance, and personnel can be relatively fixed once guidelines have been established for data access, volumes, processing and desired end products. The cost of developing application-specific software can be high, but may be rather stable when compared against the licensing costs added to by-the-hour consultant charges for customized modifications of commercial software products. Presently, there exist several hundred stan- dard data formats for remotely sensed data, and there are multiple international efforts to create a single standard format to describe them. Calibration: Calibration of the sensor systems is a critical part of remote sensing. The instru- ment manufacturers carefully determine the relationship between known radiances and detector counts prior to deployment in space (launch). Monitoring the sensor system's calibration after deployment is more difficult, but at least as important because electronic systems age in unpre- dictable ways. Since the ultimate objective of remote sensing is to accurately relate the numbers returned from the remote system to the physical state of the object(s) being sensed, it is impera- tive to maintain a rigorous in-situ validation (ground truth) program for known reference points which are relevant to the specific concerns of the user. Atmospheric considerations: Remote determination of temperature can be accomplished with either infrared film (photogrammetry) or electronic detectors that are sensitive to low- energy infrared photons (imagery). Remote detection of temperatures in marine environments by use of a single remote sensing system is subject to serious, changeable errors in calibration accuracy. This is due to variations in the local relative humidity, because water vapor absorbs infrared radiation very strongly and is not uniformly distributed. Thus, multiple, simultaneous measurements are required if high-precision thermal measurements are to be made remotely. This is commonly performed with a multichannel instrument which permits calculation of a moisture content correction for each pixel in the scene. Navigation co m side ration s: Another crucial aspect of remote sensing is knowing precisely where, on the face of the earth, the numbers being returned from the satellite originated. With on-board telemetry information, the location of the platform and its attitude (pitch, roll, yaw) are known. With this information, the location of each pixel within the scene can be calculated (often performed by the data provider - with varying accuracy). a:@I Cautionary Note The tools of remote sensing can provide many useful products for the coastal manager, but, as with Z@ most tools, some knowledge is required to obtain the desired end result. An ocean color image can be equally used for mapping estuarine eutrophication as it could be used for directing fishing efforts to the total depletion of a fishery. Acquiring and Proce5r2ing There are generally six steps involved in processing photogrammetric and remotely sensed data: ac- quire, ingest, geo-reference, calibrate, display, process/analyze. These steps are not necessarily indepen- dent of one another. The amount of development effort required to get from the first step to the last can vary substantially depending upon many factors, not the least of which is the developers' experience with the data and its idiosyncrasies (Figure 10). 1. The first step is to identify and acquire the correct information. This involves identifying a source for an appropriate type, location and date of photo or image, determining the most effec- tive method for obtaining it, and making the necessary arrangements to acquire it. This can involve anything from a quick phone call to international negotiations with foreign govern- ments, and from a simple network file transfer to complex archival exhumations. Because of the complex nature of international negotiations, this can often be the most time-consuming step. (Appendix D contains many useful contact names, addresses, and phone numbers to sim- plify this task.) 2. The second step is to ingeet the data. Hard-copy imagery must be digitally scanned. Digital imagery can be made available at any of the stages through which it passes from the initial observation/direct download stage to data that a vendor has recorded in predetermined formats on standard media (e.g., tape, disc, CD-ROM). Data cannot be viewed, mapped, calibrated, or used until it can be accessed and decoded by computers and transformed into its constituent components (scan lines, channels, etc.), which are then converted into individual pixels (nu- merical picture element values). 3. Once picture/image data has been ingested, 0% it needs to be geo-referenced. This is nor- 10% cquire - malty performed as a series of mathematical A L. - > 20% calculations, which permits the pixels to be 30% located with respect to the surface of the earth Ingest 441% and the desired viewing projection. Usually, this step also provides geometric corrections G f c 50% eo re eren ei@_ to each pixel for viewing angle anomalies. CAM This is often the second most complex opera- 70% Calibrate tion because there is such a plethora of simi- lar but totally incompatible map projections Display (cf: Mercator, Lambert, Polar 90, etc.). Typi- Process IN% cally, data suppliers have limited subsets of projections available and thus, users must be very specific in their requirements. Figure 10. Kermot_- octioitiq irriagery praccooire ocemario (percent,90c of efforc). 4. After the data pixels are geo-referenced so that they will fit properly onto the desired digital map, they are calibrated. Sensor values are converted into geophysical parameters by means of known conversion algorithms and constants for each sensor (e.g., a temperature of two degrees has twice the numerical value of a temperature of one degree). Different instrument channels have differing sensitivity to various parts of the electromagnetic spectrum, and to the physical environment between the sensor and the objects being sensed. Subsequent to the derivation of calibration equations and coefficients, an accuracy assessment should be per- formed. Independent estimates of the error associated with each processed pixel measurement should be performed using data from a series of both in situ measurements and remote sensing data which have been collected independent of the data used in the derivation of the calibration algorithms. There are several levels of calibration precision and thus, users must balance their specific requirements against the amount of effort (cost) required to achieve it. 5. Properly geo-referenced and calibrated imagery is non-nally graphically Jisplayed to en- sure that the preceding calculations have had the desired effect, and that the resulting image product approximates reality. Common image display/manipulation systems include ArcView, MIPS, PCI, ERDAS, IDL, SEls, etc. Depending on the knowledge base of the user's support personnel, this can be the shortest step. 6. Image proGer2r2ing and analysir, are usually necessary to derive useful analytical products from the geo-referenced, calibrated imagery. This is accomplished by manipulating individual pixels to add information to the image (e.g., atmospheric moisture corrections) and produce a de- rived image product (e.g., calculating temperatures or chlorophyll concentrations using multiple channels). Additional data may also be integrated from a variety of other sensors (e.g., ship and buoy data), coastal geography files, and time series. Image data and/or their derived products may be imported as information layer(s) into a geo- graphic information system (GIS). Image processors also normally provide the ability to zoom, roam, pan, modify enhancement curves, annotate, export analyses, etc. This step results in the creation of products that coastal resource managers can use (e.g., analyses of habitat change, locations of oil spiHs, intensity of algal blooms, upwelling events), as illustrated on the cover of this document and in Figures 2 through 9. 20 Large-scale changes of the earth's surface have been occur- ring at a rapid pace, particularly in coastal regions. Remote sensing from space-borne satellites is perhaps the only data- 5 Concluding acquisition system capable of recording many of these changes at the required spatial and temporal resolution, given the size of the areas affected and the rate at which these Thought,5 changes are taking place. Remote sensing systems maxi- mize information and areal coverage in a timely fashion and at minimal cost. Current Requiremente The space and time domains for observing various coastal phenomena are diagrammed in Figure 11 (repro- duced from Klemas et al. 1995). Note that the spatial/temporal resolution provided by weather satellites appears by itself in the upper left of the diagram, while the spatial resolution required for following coastal processes (pollution, upwelling, plankton dynamics, wetland biomass studies, marsh habitat mapping) occu- pies the 10-100 m spatial resolution range, and the temporal requirements for repeat coverage over the same area span the range from hours to hundreds of days. None of the present satellite sys- 105- tems were specifically designed to examine coastal processes. While maximum resolution (spatial, tem- poral, spectral, radiometric) is de- 104- Gros sirable, it would not be practical to Ocean create any single system to meet all Circulation of these needs. Each portion of the Gulf Siream 10- & Eddies electromagnetic spectrum-the Shelf physical parameter quantified in re- Circulation & Fronts Coastal mote sensing-offers specific ad- Ul a ling vantages (e.g., all-weather, high- S 102- Red TI Phytoplan Coastal Dynamics Land Use resolution) and contains inherent Estuarine Studies TWI limitations (e.g., unusable in cloudy Circulation Ice Weiland Estuarine Ocean Cover Biomass weather, narrow viewing swath) for Front & Studi Marsh 101- Pollutant Dumpin Habitat determining variables in the coastal Dynamics Rive Storm Mapping Marsh Damage wale@ay environment. It is important to Marine Flooding Assessment Siltation Traffic note, however, that systems now Control Long Term r being developed will make use of 00- zr..,.n advances in sensor and computa- 1@111 104 too 101 102 103 tional technologies to provide more TEMPORAL RESOLUTION (days) capable instruments, probably Figure 11. 5patialard Temporal Rcoolution Requiremerito for Coaoral Otudieo, within the next eight years. Univ. of Delaware. d Use d'as ..'sh Habitat Mapping L. @,Ie, Erosion 21 A A Look Toward the Future Remote sensing is a technology whose time is coming as an important tool for coastal resource manag- ers. Strengthening the connections between coastal management issues and the contributions that re- mote sensing technology can make toward resolving them will require addressing of important issues. Remote sensing engineers and coastal managers must increase their efforts to communicate and col- laborate. Coastal managers need to become more familiar with the capabilities of remote sensing sys- tems, and designers of remote sensing systems need to focus on the requirements of these relatively new customers. Another effort is to develop better and cheaper remote sensing instruments-sensors that are designed to detect specific coastal changes at a relatively fine level of resolution (high-resolution imag- ery can be sub-sampled if less detail is required, but coarse-resolution imagery cannot be substantially reprocessed to improve its inherent limitations). The image on the cover of this document is representative of commercially available 2 rn panchromatic (black and white) products from Sovinformsputnik (Russia). At the time of this printing, the Japanese ADEOS satellite has been successfully placed into orbit (on schedule) and has begun collection of imagery from its 12 channel Ocean Color and Temperature Sensor (OCTS). The follow-on ADEOS II system (scheduled for launch in 1999) will have 34 channels digitized to 12 bits radiometric resolution. Several governmental and commercial organizations have undertaken significant initiatives (Appendi- ces C through D) to begin supplying very high quality (high spectral, spatial, radiometric resolution) imagery to all customers. The constellation of planned active and passive microwave and optical satel- lite sensors will provide the coastal manager the means to perform coastal surveillance within a single synoptic view. The fusion of multiple, complementary image data sources (differing spatial, spectral, temporal, radiometric resolutions) and existing GIS databases into single products for the analyst con- tinues to accelerate due to the growth in capabilities of small, inexpensive computers. As the products from these systems become readily available in a timely manner, the remote sensing problem of the coastal resource manager will become one of making educated decisions on which of the plethora of alternatives will best address the issues currently on the table. For additional information see references in Section 6. 22 Additional Reading American Society of Photogrammetry and Remote Sensing. 1981. Manual of Remote Sensing, Second Edition, Sheridan Press. 2,440 pp. American Geophysical Union. 1983. SEASAT special issue, reprinted from J. Geophys. Res. (88). 1,952 pp. Burrows, W.E. 1986. Deep Black, Random House. 401 pp. David Sarnoff Research Center. 1993. Proceedings, National Softcopy Review. Drury, S.A. 1990. A Guide To Remote Sensing Interpreting Images of the Earth, Oxford University Press. 199 pp. Elachi, C. 1987. Introduction to the Physics and Techniques of Remote Sensing, John Wiley & Sons. 412 pp. Environmental Research Institute of Michigan. 1994. Integrating Remote Sensing and GIS for Natural Resource Management, proceedings of the second thematic conference on remote sensing for marine and coastal environments. 135 pp. Gonzalez, R.C. and P. Wintz. 1987. Digital Image Processing, Addison-Wesley Publishing. 503 pp. Jones, I.S.F., Y. Sugimori, and R.W. Stewart. 1993. Satellite Remote Sensing of the Oceanic Environ- ment, Seibutsu Kendyusha. 528 pp. Klemas, V.V., R.G. Gantt, H. Hassan, N. Patience, and OR Weatherbee. 1995. Environmental Information Systems for Coastal Zone Management. World Bank, Washington, DC. 104 pp. Maul, G.A. 1985. Introduction to Satellite Oceanography, Martinus Nijhoff Publishers, Dordrecht. 606 pp. Ryerson, R.A., S.A. Morain, and A.M. Budge (eds.). 1996. Manual of Remote Sensing, third edition. CD-ROM edition. Szekielda, K-H. 1988. Satellite Monitoring of the Earth, John Wiley & Sons. 326 pp. Verbyla, David L. 1995. Satellite Remote Sensing of Natural Resources, Lewis Publishers. 198 pp. 23 7 Gloooary AATSR Advanced Along Track Scanning Radiometer to be flown on ESA!s ENVISAT ADEOS NASDA!S Advanced Earth Observing Satellite AIRS Atmospheric InfraRed Sounder to be flown on NASAs EOS-PM ALADIN Atmospheric laser Doppler Instrument on ESA satellite ALMAZ Russian satellite series ALOS Japanese satellite scheduled to be launched in 2000 ALT Altimeter altim Altimeter AMI Active Microwave Instrument, 3 modes on ERS satellite AMMS Airborne Multispectral Measurement System AMR Scanning Microwave Radiometer on NSAU SICH satellite AMSR Advanced Microwave Scanning Radiometer on ADEOS II satellite AMSU Advanced Microwave Scanning Unit on NOAA k-n satellites ASAR Advanced Synthetic Aperture Radar on ESA!s ENVISAT ASCAT Advanced Scatterometer to be flown on future ESA missions ASTER Advanced Spaceborne Thermal Emission and Reflection to be on NASA!s EOS- AM platform ATSR Along Track Scanning Radiometer flown by ESA on ERS satellite AVHRR Advanced Very High Resolution Radiometer flown by NOAA on TIROS AVNIR Advanced Visible and Near-Infrared Radiometer flown by NASDA on ADEOS BTVK Scanning television radiometer on Russian Electro-GOMS satellite BUFS Backscattering UV spectrometer on Russian METEOR satellite CAST Chinese Academy of Space Technology CBERS China-Brazil Earth Resources Satellite CCD Charge-Coupled Device CLARK Joint NASA and CTA Systems satellite CONAE Comision Nacional. de Actividades Espaciales (Argentina) CSA Canadian Space Agency CZCS Coastal Zone Color Scanner flown by NASA on NIMBUS-7 DARA Deutsch Agentur Fur Raumfahrtangelenheiten GmbH (Germany) DCP Data Collection Platform DCT Data Collection and Transmission system DCS Data Collection System DELTA Multispectral microwave scanner on board the NSAU Okean satellite DMSP United States Defense Meteorological Satellite Program DORIS Doppler Orbitography and Radio positioning Integrated by Satellite to be flown on ESA!s Envisat,TOPEX/POSEIDON, and NASA!s EOS-ALT EARLY BIRD An EarthWatch, Inc satellite 24 Eh Oxidizing potential in millivolts ELECTRO-GOMS Geostationary satellite flown by Russia ENVISAT environmental Satellite to be flownbyESA EOS Earth Observing System platforms to be flown by NASA ERS European Remote Sensing Satellite flown by ESA EROS-1 Israel's satellite carring high resolution VIS/IR instruments EROS Earth Resources Observation Systems of the U.S. Geological Survey of the U.S. Department of the Interior ESA European Space Agency ETM Enhanced Thematic Mapper to be flown on LANDSAT 7 FY Feng Yeng (cloud wind) satellite series flown by The People's Republic of China GDE GDE Systems, Inc. and the name of their satellite GEOSAT Geodynamic Experimental Ocean Satellite flown by the U.S. Navy GLAS Geoscience laser Altimeter System to be flown on NASA's EOS-ALT GLI Global Imager to be flown on the Japanese NASDA!s ADEOS II GMS Geostationary Meteorological Satellite flown by NASDA GOES Geosynchronous Operational Environmental Satellite flown by NOAA GOME Nadir looking double spectrometer flown on ESA!s ERS-2 HIRS High resolution InfraRed Sounder flown on NOAXs TIROS satellites HRC High Resolution CCD HRG Enhanced High Resolution plus vegetation flown on CNES SPOT 5 HRV High Resolution Visible flown by CNES on SPOT HRVIR High Resolution Visible and Infra-Red flown on CNES SPOT 4 HSI HyperSpectral Imager flown on NASA!s and TRW's Lewis satellite IASI Infra-red Atmospheric Sounding Interferometer flown on EUMETSAT METOP satellite IMAGER Visible and IR radiometer flown on NOAA!s GOES INE Instituto de Pesquisas Espaciais (Brazil) INSAT Indian Satellite in geostationary orbit IKAR Multispectral microwave scanner flown on Russia's PRIRODA IKAR-D Multispectral microwave scanner flown on Russia's PRIRODA IR Infrared IRMSS Infrared Multispectral Scanner flown on CBERS IRS Indian Remote Sensing Satellite ISRO Indian Space Research Organization JERS Japanese Earth Resources Satellite KARI Korean Aerospace Research Institute KFA Photographic camera flown on Russia's Resource satellites KLIMAT Scanning IR radiometer flown on Russia's METEOR satellite KOMSAT Korean Mapping Satellite, operated by KARI KVR Photographic camera flown on Russia's and Lambda Tech's satellite LANDSAT Land Remote Sensing Satellite flown by NASA, then NOAA then EOSAT LEISA Linear Etalon Imaging Spectral Array flown on NASA!s and TRW's Lewis LEWIS Polar orbiting satellite co-operated by NASA and TRW. LFC Large Format Camera flown on NASA!s Space Shuttle Continued on next page 25 Gloggary (cont.) LISS Linear Imaging Self Scanning sensor flown on ISRO's IRS MECB Brazilian satellite operated by INPE MERIS Medium-Resolution Imaging Spectrometer flown on ESA!s ENVISAT MESSR Multispectral Electronic Self-Scanning Radiometer flown on NASDA!s MOS satellite series METEOR Satellite platforms flown by Russia METEOSAT Geostationary satellite series flown by EUMETSAT METOP Meteorological Operational Satellite flown by EUMETSAT MIMR Multifrequency Imaging Microwave Radiometer to be flown on NASA!s EOS-PM MISR Multi-angle Imaging Spectro-Radiometer to be flown on NASA!s EOS-AM MITI Japan's Ministry of International Trade and Industry MIVZA Experimental mivrowave radiometer flown on Russia's METEOR MK Multispectral photographic camera flown on Russia's Resource MODIS Moderate-Resolution Imaging Spectroradiometer to be flown on NASA!s EOS-AM platform moms Modular Opto-electronic Multi-spectral Scanner to be flown on Russia's PRIRODA MOS Marine Observation Satellite flown by NASDA MOS Modular Optoelectronic Scanner flown on Russia's PRIRODA MSR Microwave Scanning Radiometer flown on NASDA!s MOS NISS MultiSpectral Scanner flown on LANDSAT MSG Geostationary satellite series flown by EUMETSAT MSU Medium Resolution Scanner flown on Russia's RESOURCE MTZA Scanning microwave radiometer flown on Russia's METEOR MVIRI MET`EOSAT Visible and Infra-Red Imager operated by EUMETSAT MWR Microwave Radiometer flown on ESA!s ENVISAT MZOAS Scanning microwave radiometer flown on Russia's METEOR satellites NAPP National Aerial Photography Program archived by the USGS NASA U.S. National Aeronautics and Space Administration NASDA National Space Development Agency of Japan NHAPP National High Altitude Photography Program archived by the USGS NIMBUS NASA!s satellite series first launched in 1964 NOAA U.S. National Oceanic and Atmospheric Administration NRSA India's National Remote Sensing Agency NSAU National Space Agency of the Ukraine NSCAT NASA Scatterometer flown on NASDXs ADEOS OCEAN-01 N7 of the OKEAN-01 satellite series launched by Russia OCEAN COLOR NASA instrument to fly on EOS-COLOR satellite OCTS Ocean Color and Temperature Scanner flown on NASDA!s ADEOS OKEAN Soviet Union satellite series, now with NSAU OLS Operational Line Scanner flown on the U.S. DMSP OPS Optical sensors flown on NASDA!s JERS- I satellite OSC Orbital Sciences Corporation 2 Go ORBVIEW Visible and infrared instrument flown on ORBVIEW satellite by OSC PAN Panchromatic mode of an instrument sensitive to a wide visible band pH Hydrogen ion concentration POLDER Polarization and Directionality of the Earth's Reflectances flown on NASDA's ADEOS PRIRODA Russian space station type platform QUICKBIRD EarthWatch, Inc. satellite R Single channel microwave radiometer flown on NSAU OKEAN series RA Radar Altimeter flown on ESA's ERS satellite RADAR Radio Detection and Ranging RADARSAT Canadian Radar Satellite RESOURCE Russian successor to the RESURS satellite series RESOURCE21 Name of Vis/IR sensor and satellite platform flown by RESOURCE21 Company. RLSBO Side looking microwave radar flown on NSAU OKEAN satellite RM Scanning microwave radiometer flown on Russian OCEAN satellite RSA Russian Space Agency SAC Argentine satellite SAR Synthetic Aperture Radar flown on many satellites (SEASAT, ERS, JERS, SIR) SCARAB Scanner for Earth's Radiation Budget flown on Russia's METEOR and on ESA!s ENVISAT scene A view or "picture" of landscape or image SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric Cartography to be flown on ESA!s ENVISAT SCR Scanning Microwave Radiometer SEASAT NASA satellite launched in 1978 SEASTAR NASA and Orbital Sciences Corporation's (OSC) satellite SEAWINDS NASA Scatterometer to be flown on NASDA!s ADEOS II SeaWIFS Sea-viewing Wide Field-of-View Sensor to be flown on NASA!s and OSC's SEASTAR SEVIRI Spinning Enhanced Visible and Infra-Red Imager flown on EUMETSAT's MSG SICH NSAU's successor to the Soviet Union's OKEAN satellite series SILVA Optical Equipment for Stereograpby to fly on Russian ALMAZ SLAR Side Looking Airborne Radar SLFMR Scanning Low-Frequency Microwave Radiometer SMMR Scanning Multichannel Microwave Radiometer flown on NASA!s SEASAT SMR Scanning microwave radiometer flown on NSAU's SICH satellite SPACE IMAGING name of the instrument, satellite and company SPOT System Probatoire d'Observation de la Teffe flown by CNES SROSM Spectroradiorneter for ocean monitoring flown on Russia's ALMAZ SRMR SpectroRadiometer medium Resolution flown on NSAU's SICH SSALT Solid State Altimeter to be flown on NASA!s EOS-ALT SSM/I Special Sensor Microwave Imager flown on the U.S. DMSP SSM/T Special Sensor Microwave Temperature flown on the U.S. DMSP SSR Camera flown on INPE's MECB SSU Stratospheric Sounding Unit flown on NOAA!s TIROS SWIR Short Wave Infra Red flown on NASKs EOS-AM Continued on next page 27 Glo55ary (cont.) TIR Thermal Infra Red TIROS Television InfraRed Observation Satellite series referred to as NOAA polar orbiter series TK Photographic camera flown on Russia's and Lambda Tech's satellite TM Thematic Mapper instrument flown LANDSAT satellite TMR TOPEX Microwave Radiometer flown on NASA!s and CNES's TOPEX/ POSEIDON and follow on platforms such as NASA!s EOS-ALT TOMS Total Ozone Mapping Spectrometer flown on NUMBUS satellite TOPEX NASA/CNES ocean topography experiment satellite TRASSER Microwave spectroradiometer flown on NSAU OKEAN TRMM NASA satellite scheduled to be launched in 1997 TSR Thermal Spectroradiometer flown on NSAU's SICH UV Ultra-violet portion of the electromagnetic spectrum VAS VISSR Atmospheric Sounder flown on NOANs GOES VEG Vegetation instrument to be flown on CNES's SPOT satellite VHRR Very High Resolution Radiometer flown on ISRO's INSAT and early NOAA satellites and on NASA!s NIMBUS VIRR Visible and Infrared Radiometer flown on NASAs SEASAT VIRS Visual Infra-Red Scanner to be flown on NASA!s TRMM VIS Visible portion of the electromagnetic spectrum VISSR Visible and Infrared Spin-Scan Radiometer flown on NOAA!s GOES and NASD,Ks GMS VNIR Visible and Near Infrared Radiometer flown on many platforms, CONAE's SAC, NASA!S EOS-AM, KARI's KOMSAT, OSC's ORBVIEW VSAR Synthetic aperture radar instrument to be flown on NASDA!s ALOS VTIR Visible and Thermal Infrared Radiometer flown on NASDA!s MOS WIFS Wide Field Sensor flown on ISRO's IRS 174-K IR atmospheric sounder flown on Russia's METEOR satellite 28 The following appendices provide a tabular summary of past (Appendix A), present (Appendix B), and intended future (Appendix C) satellite-bome remote sensing systems, of along with a qualitative ranking (high, medium, low) of 5ummary their applicability to coastal resource management issues. iGeo Appendix D provides summary details on specific sensors Append aboard a wide variety of current and proposed remote sens- ing platforms. Appendix E summarizes the potential appli- cation of NASA's proposed 36-channel MODIS platform. Appendix A: Past Sensors .................................................................................................................. 28 Appendix A is a tabular compilation of many of the older satellite-borne remote sensing systems de- ployed since the first successful launches in the late 1950's. The platform on which the sensor was flown, the major applications for the data, the mean wavelength of the spectral band(s) for the detector, and the spatial resolution of the sensor are provided. From the sensor attributes, resource managers can understand why there have traditionally been only limited uses for satellite-borne remote sensing for coastal and estuarine applications. Appendix B: Present Sensors ............................................................................................................. 29 Appendix B is a brief table of some of the remote sensing systems that are active at the time of this report. From this table, it is clear that present satellite-borne remote sensing systems-optimized for large-scale oceanographic and meteorological processes and for land-use applications-are better than previous systems, but continue to lack sufficient spatial and spectral resolution for extensive use in the environmentally complex coastal zone. Appendix C: Future Sensors ............................................................................................................. 33 Appendix C is a brief tabulation of some of the satellite remote sensing systems that have been an- nounced for future deployment by a variety of organizations. Coastal environmental management will become much more quantitative and accessible if these succeed. Appendix D: Detailed Descriptions of Selected Present and Future Platforins/Sensors ............. 41 Appendix D is a summary of the satellite remote sensing systems whose resolution is appropriate for use in oceanic and coastal regions. It is organized by responsible organization/company, characteristics of the platform, characteristics of the sensor, and organizational contact for additional information. This information was compiled, in part, from infon-nation contained in the ASPRS workbook Land Satellite Information in the Next Decade (September 1995). Appendix E: MODIS Characteristics ............................................................................................... 75 The MODIS instrument to be flown on the NASA EOS AM I platform, currently scheduled for a 1998 launch, is summarized here. The 36 bands of MO- DIS are separated into categories by application and Summary_of Qualitative Rankings Platforms/Sensor JLzh further annotated as to the intended applicatio v@ total@ n of 1@o@ @ each band of the instrument. This instrument may Past (1978-1988) 1 4 9 14 be useful for the study of ocean basin phenomena; Present. @6peratio'nal'): 13 32 55 however, for coastal and estuarine work, the 250 M F.ture (1996-2004) 38 22 40 100 resolution will not be adequate for most applications. Rotals .49. 39 8 1 169 29 Appendix A. Eaa 5cnooro Seasat internal waves, water vapor/precip, sea wind speed, sea surface temperature ALT (M) 13.5 GHz 2.4 km VIRR (M) 0.7 pm 3 Ian 11 AM 5 Ian SMMR (L) 6.6 GHz 87 x 149 km 10.7 GHz 53 x 89 km 18 GHz 31 x 53 Ian 21 GHz 27 x 42 km 37 GHz 27 x 16 Ian SASS (L) 14.59 GHz 50 km SAR (H) 1.275 GHz 25M est-of chlo' It'!0hotoplanktbribibmassl suspended sediments C zCS (M) 0.44 pm 850 m 0.52 pm 850 M 0.55 pm. 850 rn 0.67 pm 850 m 0.75 pm 850 m :clo,,uds",.o ean color;` s,ca@suitace@t'e'm'ver'a'tuie,,,s''u"s-'ve'nd6d"siM'nnents c .............. . ... ... --- - ------ AVHRR (M) 0.63 pm 1.1 km 0.92 pm 1.1 km 0.51 Pm 1.1 km 0.56 pm 1.1 km 11.5 Pm 1.1 km tempera A 'd a,cblorAce'txt Am s e @,se ent,,cloud cover, precipitation e 1'-- , I - @ 111.1 - -11... 1- - I -I.. 11--l-I.-I.. 1. MSU-M (L) 0.55 pm 1 x 1.7 Ian 0.65 pm 1 x 1.7 km 0.75 gm 1 x 1.7 km 0.95 pm 1 x 1.7 Ian MSU-S (L) 0.62 pm 345 m 0.9 Pm 345 m MSU-SK (L) 0.55 pm 170 m 0.65 pin 170 m 0.75 pm 170 m 0.92 pm 170 m 11 P.M 600 m MSU-V (L) 0.49 pm 50M 0.57 pm 50 m 0.68 pm 50m 0.86 pm 100 M 1 100 m 1.6 pm 100 M 2.2 pm 100 m 11.4 pm 100 M R-225 (L) 13.3 GHz 130 km R-600 (L) 4.9 GHz 130 km RLSBO (L) 13 GHz 2 Ian 30 Appendix B. Preoctit 5emooro DNISP atmospheric temperature, ice, salinity, temperature, surface roughness, SSMT (L) 55 GHz 180 km SSMI (L) 19 GHz 25 Ian 22 GHz 25 Ian 37 GHz 25 km 85 GHz 12.7 km ve g e t a ti on," 1 @c@e`,':se' ai ce te-eraiuie MP OLS (M) 0.7 pm 620 m 11 Pm 560 m ELECTRO-, vegetatiqp;16@npeiatures, space nvironmerit S, GOM' BTVK (L) 0.55 pm- 15 km 11 Pm 8 1(m internal wavvesr ice slicics, currefitAivergence,,seasurfa ERS4 ce convergence;@, AMI-SAR imager (H) 5.3 GHz 30m AMI-SAR wave (L) 5.3 GHz 30m AMI-SCATT (L) 5.3 GHz 50 lan ATSR (M) 1.6 gm 1 Ian 3.7 pm 1 km 11 Pm 1 km 12 pm 1 kn 23.8 GHz 50 Ian 36.5 GHz 50 km RA (M) 13.8 GHz 7 Ian GOME (K 0.51 Pm 40 km GEOSAT' fron ice, eddiesi geostrophic currents ALT (L) 13.5 GHZ 6.8 km GMS sexsurface teirnperatuies VISSR (L) 0.63 pm i-.25 k m 11.5 pm 5 Ian sea@s e4em iiatuWl,,@ A` VAS (L) 0.6 PM 1.0 kin 4 pm 4 Ian 6.8 pin 10.5 km INSA7T'-@'- ieii6xirfa@,@;temperatures@@"i VHRR (L) 0.6 pm 2.75 km 11 Pm 11 Ian o-astal, Li�S (M) 0.5 pm 72.5 m 0.55 pm 72.5 m 0.65 pm 72.5 m 0.8 pm 72.5 m dd A IL' de"d i:lim e 2 _USS 11 (H) 0.48 gm 36m 0.55 pm 36m 0.66 pm 36m 0.81 pm 36m Appendix 13. Preoent 5enooro cortinued JERS-I geology, vegetation, cartography, shallow water bathymetry OPS (H) 0.56 pm 18mx24m 0.66 pm 18mx24m 0.81 pm stereo 18 m x 24 rn 1.65 pm 18mx24m 2.07 pm 18mx24m 2.19 pm 18mx24m ice, snow, internal waves SAR (H) 1.275 GHz 18mxl8m LANDSAT vegetation'discrimination,,vi orAssessmentj oceantolor, shallowwater bathymetry MSS (Mj 0.55 pm 80 rn 0.65 pm 80m 0.75 pm 80m 0.9 PM 80M :*e@and@,,m,@Rping@iess.@s@Oowwa r@<30),@,benthic communities, sea surface temperature TM (H) 0.48 pin 30m 0.57 gm 30m 0.67 pm 30m 0.82 pm 30m 1.65 pm 30m 2.2 pm 30m 11.5 PM 120 m METEOR- -ozoneatmosp.,he'd-c" tj wa r sen' 174-K (L) 9.6 pm 42 kin 11.1 Pm 42 km 18 pm 42 kin 13.33 jim 42 km 13.7 pm 42 Ian 14.24 pm 42 Ian 14.43 pm 42 Ian 14.75 pin 42 km 15.02 pm 42 kin ,,c on, e, :so AfrAdiatibw UX@Icl' v etation BUFS-4 (L) 250-350 rrn 180 kin KLMIAT (L) 11 PM 1 krn t -4tM6s# eric eratu mpera@ e'-;',,-wa-'ter vapor,, ciouas @ MIVZ@k (L) 0.86 cm 20-80 km MTZA (L) 20-94 GHz 20-80 km MZOAS (L) 6. -94. GHz 9-160 km ScaRaB (L) 0.2-12 pm 60 Ian .......... bzone@,'O, up 'f0idS (L) 0.3 prn 47 lan ter, sea,sur accte! ra MVIRI (L) 0.7 pm 2.5 km 6 pm 5 Ian 11 pm 5 km 32 Appendix 13. Frooent5enooro continued MOS-1,2 suspended sediments, land/water, water vapor MESSR (H) 0.55 pm 50m 0.65 pm 50in 0.75 pm 50in 0.95 pm 50m watOrvapor,-sea surfacetemperature VTIR (L) 0.6 pm �00 m 6.5 pin 900 in 11 AM 900 m 12 pm 900 m ice, sea surfac,ePug6elss MSR (L) 23.8 GHz 32 km 31.4 GHz 23 Ian NOAA,series, sea,surface temps, vegetationaerosols- AVHRR (M) 0.63 pin 1.1 km 0.9 pm 1.1 km 3.8 pm 1.1 kin 11 Pm 1.1 kin 12 pm 1.1 kin HIRS (L) 0.66-14.98 pin 17.4 km MSU (L) 50.3 GHz 105 kin AMSU (L) 53.7 GHz .50 Ian 54.9 GHz 50 kin 57.9 GHz 50 Ian 89 GHz 50 Ian Ocean-01 ocean frontsVi@egetation MSU-M (L) 0.55 Pm 1 km 0.65 pin 1 km 0.75 pm 1 kin 0.95 pin 1 kin MSU-S (L) 0.68 pin 345 m 0.85 pin 345 m ge'717- suria'ce; U-@'@--""'-,"S"'@ RLSBO (L) 3.1 an 1. RM-0.8 (L) 0.8 an 15x2O km Resource-41 lani sea;.Ve ',",atejr.v4"' 4 MSU-E (L) 0.55 pin 45M 0.65 pin 45m 0.85 pin 45m MSU-SK (L) 0.55 pm 170 in 0. 65 pm 170 m 0.75 pin 600 in 0.95 pm 600 in 10.6 pin 600 in ROsburce-TIM'' tart@ Phy,"tidil,@mar@h'@b6un4ik@s@,,,berithi@ibi,6ta'@@ """'tjj series KFA-1000 (L) 0.69 pin 6m KFA-200 (M) 0.65 pm 23m Appendix 13. Freoent Sonooro continued Resource-F2 cartography, tidal marsh boundaries, shallow water, benthic biota cultural identification series MK-4 (M) 0.41 pm lom 0.49 pm lom 0.54 pxn lom 0.67 pm lom 0.68 pm lom 0.84 pm lom Resource-,F2M @cartqgraphy,,, dal,marsh@bouridaries,,,sh@kllow water, benthic biota cultural identification ,series MK-4M (M) 0.67 pm 6m 0.54 p.Tn 6m 0.64 pm 6m 0.84 pm 6m Resource-F3 .' . :,tartograp@y,,,,tidil@marsh@boundaries,@sh;illowwater;@b'@nthtc,biota cultural identification 'series KFA-3000 (M) 0.65 pm 3m SIR-B @8A@-.@@ @izitemal,.,way4o,,,ite;,oceaii:fioiits@,,., SAR (M) 1.282 GHz 20m an on s,,,, 'SII@C@, "SAR internal, i ocei-fr. 't"' 1.25 GHz 40 x 10-60 m 5.3 GHz 40 x 10-60 m 9.6 GHz 40 x 10-60 m ca SPIN.41@'@-"@ ... rt @@pl@y,'tidat@v,=,sh,boundaiie!@@,benthic@blota' KVR-1000 (H) 0.66 pm 2m TK-350 (H) 0.66 pm lom SPOT, flat ma ph ,Ig p HRV (H) 0.57 pm 20m 0.65 pm 20m 0.85 pm 20m ':cartograp,,,y', PAN @H) 0.6 pan lom -su ace oid ,TPP,E)(/,, A @elerMickvige' ,rOSI@tPON-@ -- - ------ - - XLT (L) 5.3 GHz 20 x 2-10 km 13.65 GHz 20 x 2-10 km TMR (L) 18 GHz 50.86 km 21 GHz 39.76 km 37 GHz 27.37 km 34 Appendix C. Future Semooro ADEOS ocean-color, suspended sediments OCTS (M) 0.41 pm 700 m 0.44 pm 700 m 0.49 pm 700 m 0.52 pm 700 m 0.56 pm 700 m 0.66 pm 700 m 0.77 gm 700 m 0.86 pm 700 m 3.7 pm 700 m 8.5 pin 700 m 10.7 pm 700 m 11.7 pm 700 m ow coastal shall j, benthic, mapp ng,,vegetation, ocearv'co or, AVNIR . . .... ...... @6.4'8 pm" 0.55 pm 16m 0.64 gm 16m 0.82 pm 16m PAN (H) 0.6 pm 8m NSCAT (L) 14 GH1z 25 km POLDER(H) 0.443 pm 6km 0.495 pzn 6 Ian 0.565 pm 6 km 0.665 pm 6 km 0.763 pm 6 km 0.765 pm 6 km 0.865 pm 6 km 0.91 Pm 6 Ian pceart color, sedimenW,@i@ AP@9@7# POLDER (L) 0.443 PM 6 Icrn 0.67 pm 6 Ian 0.865 pm 6 Ian 0.49 pm 6 Ian 0.565 pm 6 Ian 0.763 pm 6 Ian 0.765 pm 6 Ian 0.91 Jim 6 Ikm ace @co or;.Pust)en ve @sea- GLI 34 channels (M) Vis-TIR 250 m 35 Appendix C. Future 5emooro contimuM ALMAZ vegetation, suspended s.edimentsi ocean color MSU-E (M) 0.55 Pm lom 0.65 pm lom 0.85 pm lom ocean color MSU-SK (M) 0.56 pm 80m 0.65 pin 80m 0.75 prn 80m 0.9 Pm 80m 11 pm 300 m 4 a,sur accs i sea,state SAR (H) 3.49 an 260 m 3.49 cm 6 m 9.58 an 6 m 9.58 an 6 m 9.58 an 30m 70 an 30m ryegetation;suTen e,:@se oce SILVA (H) 0.55 pzn 4m 0.65 pm 4m 0.75 pm 4m A c 'or,,,,, yegfftti' n e sediments@oee -an ",o SROSM (M) 0.41 pm 600 m 0.44 pm 600 m 0.49 pm 600 m 0.52 pm 600 m 0.56 pm 600 m 0.66 pm 600 m 0.6 W 600m 0.86 pm 600 m 3.65 pm 600 m 11 Pm 600 m 12 pm 600 m ve ptati -*Jin 'e' AVNIR-2 (H) 0.46 pm lom 0.58 pm lom 0.65 pm lom 0.82 pm lom PAN (H) 0.54 pm 2.5 m 0.63 pin 2.5 m 0.74 pm 2.5 m "Y VSAR (H) 15 NMz lom BERS C 4s P@Dceanc Rr, CCD (M) 0.47 pm 20m 0.55 pm 20m 0.63 pm 20m 0.66 pm 20m 0.83 jim 20m i t h1rc. IRMSS (M) 0.8 Pm 80m 1.6 @un 80m 2.2 pm 80m 11 Pzn 160m Appendix C. Future Semooro coritinued CLARK vegetation, suspended sediments, ocean color PAN (H) 0.6 pm 3m multispectral (H) 0.54 pm 15m 0.65 pin 15M 0.84 pm 15m EARLYBIRD vegetation, imagery,,,suspended sediments PAN (H) 0.62 prn 3m 0.54 pin 15m 0.63 pm 15m 0.74 pm 15m. ENVISAT I temperature,@vegetation, cloud, aerosol, sea surface temperature AATSR (L) 0.555 prn 1 km 0.659 pm. 1 km 0.865 prn 1 krn 1.6 pm 1 km 3.7 pm 1 km 10.85 pm 1 km 12 pm 1 kin drold geoio' ASAR (M) 6 GHz 30m. m-an" neJ@ioclieli" NERI�- " i5 c@a@els (M) 0.4-1.05 pin 300 rn @2 eric um'di MWR (L) 23.8 GHz: 20 Im 36.5 GHz 20 km wixf&s peed;,�ign ,ificant.wave heij@t, sea ejoplo" ice.,@' gy, RA-2 (L) 13.8 GHz: 7km 3.2 GHz 71an :4tm li, fil s f,@chemical,compon ni@ Is qci@ e 4er6so' ., dou SCIAMACHY (L) 0.23-2.38 pm 3km EOS-ALT @:,-Precige vibiVderterndnitioh:@ DORIS (L) 2036-25 MHz 1 per 10 sec 'ickn6s, aerosol hei stilb ..... .. utions, i@ind: 6L IAS 0.532 -pm. 70x188m. 1.064 pm. 70 x 188 m. SSALT (L) 13-55 GHz 300 m TMR (L) 18 GHz 23-44 km. 21 GHz 23-44 km 37 GHz 23-44 km. 37 Appemdix C. Future 5encoro coritimuM EOS-AM series, aerosols, digital elevation, temperature ASAR'(H)_ [email protected] pm 15M [email protected] pm 20m [email protected] prn 90M ,aerosols, vegetation, NUSR (L) 0.44 prn 240 m 0.56 pm 240 m 0.67 pm 240 m 0.86 pm 240 m oceamcolor, biogeochemistry,'water vapor, sea surface temperature MODIS - 36 bands (M) 0.4-14.4 pm 250 m - 1060 In and/sea; water. vapor swik (M) 1.65 1. pm 30m 2.1 pm 30m 2.2 pm 30m 2.25 pm 30m 2.3 jim 30m sea suri@cele`mperaiure;',water vapor 2.35 pm 30m TIR (M) 8.2 pm 90M 8.6 pm 90M 9.1 Pm 90M 10.5 Pm 90M 11.4 pm 90M ,@"etation;,,,,ciilt@i@i,""I'dentificiition VNik"@i4) ': 0.58 pm 15m, 0.66 pm 15m 0.78 pin 15m fi@"Iancbsea, PAN (H) 0.7 pm 15m Vege [email protected],"tol@or,,su endedso ents-'@@" '@!' _ ""'_ " , I SP VNIR (H) 0.48 prn 30m 0.56 pm 30m 0.66 jim 30m 0.82 pm 30m e wai ,;!yap SWIR (H) 1.6 pm 30m 2pin 30m 1 Pm 240 m EOS-COLOR' . ..... @6attbiology@@@;(@!oriole,ofg!@@ glo@ ch carbon and.b cal c --y Ocean-Color - 8 channel (M) 6.'402-0.'985 pm 1.1 km arth s' u _,,@e 'o tgqin$'iiidiation@,'@_ AIRS 2300 channel (L) IR' iSkm 'Lultural@feature@identifi,cat'oiij coastal morAtoring,; IPP "I -PAN (H) 0.7 pm 1.8 m VNIR (H) 0.7 pin 1.5 m Appendix C. Future Semooro coritinued ESA. sea'surface temperature, ice, snoW, aerosols, vegetation AATSR (L) 0.555 pm 1 Ian 0.659 pm 1 km 0.865 pm 1 Ian 1.6 pm 1 kin 3.7 pm 1 km 10.85 pm 1 km 12 pin 1 km @vertical dist.d6utionoif @lo'u'As,'ieros'ol.properties,,winds, 9.41 15 km -w.aves, ice@'seasurface@wmdsjmarme bio @&emkal and.biophysicitparameters' ASAR (M) 6 GHz 30m ASCAT (L) 6 GHz 25 Ian MERIS (M) 0.4-1.05 pm 300m xp!ecip onji-c' c@temper@iiie--sea suiria,ce;@'f- rbu MIMR (L) 6.8 GHz 3-60 km 10.65 GHz 3-60 km 18.75 GHz 3-60 km 23.8 GHz 3-60 km 36.5 GHz 3-60 km 90 GHz 3-60 km ",Ice . ....... . RA-2 (L) 13.8 GHz 7km v6getatioxi,,oceari'eololrl,,Ise,gi,surf 10 channel (L) vis and IR 1 Ian FY-lD @vegFtation, ocean colori sea surface temperature, *ate@vapor 10 channel (L) vis and IR 1 kin GDE vggetation,'suspended sedimentsi;;ulturalleatures, to be determined (H) 0.6 PM 1M IRS'@O/IRS-lC' @,y@g@ta#On,,s@xi@ii@ehded@ii@diinents,,,,,,, LISS3 (H) 0.55 PM 23.5 m 0.66 pm 23.5 m 0.82 pm 23.5 m 1.6 pm 70.5 m PAN (H) 0.62 pin 5.8 In WiFS (M) 0.65 pm 188 m 0.81 pm 188 m tali"' I o or PAN (H) 0.6 pm lorn VNIR (H) 0.46 pm 20m 0.64 pm 20m 0.77 pm 20m tation.@iiceantdbrlius -04e4@sedimen urf le - turi ve Oe mp ,ace ETM+ (H) 0.7 pm 15M 0.48 gm 30m 0.57 pm 30m 0.66 pm 30m 0.83 pm 30m 1.65 pm 30m 2.21 pm 30m 11.5 pm 60m 519 Appendix C. Future 5&mooro continued LEMS vegetation, cultural feature identification, tidal marsh boundaries HSI(pan) (H) 0.6 pm 5m -HSI(vnir) (H) 0.7 pm 30m _HSI(swir) (H) 2 pm 30m LEISA(swir) (L) 2 pm 300m MECB SSR-1 vegetation,,suspended sediments IIS camera (L) 0.66 pm 200 m 0.83 pm 200 m NMCB SSR-2, vegetatiom suspended sediments IIS camera (L) 0.66 pm 200 m 0.83 pm 200 m NMTOP-si-ries sea surface temperature, aerosols,-vegetation AATSR (L) 0.555 Pm 1 km 0.659 pm I km 0.865 pm I km 1.6 pm 1 km 3.7 pm 1 km 10.85 pm 1 Ian 12 pm 1 km ,@@a,@surfac: tem erature ta. erq@o!s@ice,,snow p , _,,,,,p@ec p@_, 't@pn@,a AVHRR/3 (L) 0.63 pm 1 km 0.8 Pm 1 km 1.6 pm I km 3.76 pm 1 Ian 10.4 pm 1 km 11.9 Jim 1 km 1 0,,S,, HIRS/3 (L) 0.69 pm 19 krn 4.1 pm 19 km ... .......... tempera re,,, ro es ,--@. - @-P . .. ..... IASI (L) p'm 1 km AM, s SEVIRI (M) 0.63 pm 1 km 0.7 pm I km 0.83 pm 1 1cm 1.61 pm 1 Ian 3.8 pm 1 km 8.78 pm 1 Ian 10 pin 1 Ian 12 pm 1 km co@,s!u@ 1-1111, d6isedim SeaWifs (M) 0.412 pan 1.1 km 0.443 jim 1.1 km 0.49 pm 1.1 kin 0.51 pm 1.1 km 0.555 pm 1.1 km 0.67 pm 1.1 km 0.765 pm 1.1 km 0.865 pm 1.1 km 40 Appendix C. Future. 5emooro continued OKEAN-0 ice, precipitation DELTA-2 (L) 7 GHz 100 km 13 GHz 100 km 22.5 GHz 100 km 36.5 Gl-lz 100 km ,.physical ocean6graph@, hydrometeorology,, ice and snow MSU-M (L) 0.55 pm 1 x 1.7 km 0.65 pm 1 x 1.7 km 0.75 pm 1 x 1.7 km 0.95 pin I x 1.7 km MSU-S (L) 0.65 gm 345 m 0.85 gm 345 m jand/sea, snow and ice MSU-SK (L) 0.55 pm 170 m 0.65 pm 170 m 0.75 pm 170 m 0.95 Pm 170 m 11 Pm 600 m eratu're;@,ocei @coioir' Mkj-v (L) 0.48 pin 50m O@55 pm 50m M8 pm 50m 0.84 pm 50M 1 Pm 50m 1.6 prn 50m 2.2 prn 50M 11.2 pm 100 m 4e ea;stAte@@Internd R-225 (L) 13.3 GHz 130 krn R-600 (L) 4.9 GHz 130 km RLSBO (L) 3.1 an 2.1 x 1.2 km TRASSER-0 (L) 62 band 100 Ian a ve ti I @Cultural :feattre'@!4@@ cation PAN (H) 0.68 pin m 0.68 pm 2m VNIR (H) 0.48 pm 8m 0.56 pm 8m 0.66 pm 8m 0.83 pm 8m 6,`4ee olor@-c %44@g_ etididz sediinent in't arto ap@y,@qeyation,cartograpY3@ MOMS (H) 0.48 Wn 18m 0.55 Pm 18m 0.66 pm 18 m 0.79 pm 18m PAN (H) 0.64 pm 6m fore,aft (H) 0.64 pm 18 m QUICKBIRD-@,,@,..- PAN (H) 0.62 Ilm 3m 0.48 pm 15M 0.56 pm 15M 0.66 pm 15M 0.83 pm 15 m RAD s@-'ve etation;@slicks;,Iand,c v r, ice-coastiLion'e,monitozin e 9 SAR (H) 5.36 GHz 103 41 Appendix C. Future 5eriooro contirlued RESOURCE21 vegetation, suspended sediments, ocean color to be determined (H) 0.47 pm lom 0.56 pm lom 0.65 pm lom 0.83 pm lorn 1.58 pm 20m 1.35 prn 100 M SAC-C vegetation, ocean color, suspended sediments VNIR (M) 0.49 pm 150 rn 0.55 Pm 150 rn 0.66 pm 150 m 0.79 pm 150 m vegetation, water va or P SWIR (M) 1.68 prn 150 m SICH-1 ,vegetation, jand/sea MSU-S (M) 0.62 pm 410 rn 0.5 pm 410 m '[email protected]. @J' MSU-M (L) 0.55 prn 2000 m 0.65 pin 2000 m 0.75 pm 2000 m 0.9 Pm 2000 m SJCH-2,,",`.@ s6a@state;*.,md RLSBO with scatterometer (L) 3.1 an 0.8xl.6 km ,slicks, waves, ice-, SAR (M) 23 an 10-50 m SICH-3 @ice,,preqpitaiti on, SMR (L) 10 GHz 50 x 70 km 18 GHz 35 x 50 Ian 22 GHz 27 x 35 km 37 GHz 15 x 21 krn 90 GHz 6x6km .. ..... 'dim, - -yegetatio pceah,' lo"I en wateryapor _"_ t,,, tsi SRMR (H) 0.4-0.7 pm 10-40 m 0.8-2.4 pro. 10-40 m @sea:s 4@-' r iur' TSR ''Tpe a,,,e 3.0-13.0 pm 100 km SPACE d d dim ts" ' or, ,"pe@,,e'se_"e ioceancol PAN (H) 0.6 pin 1M 0.48 pm 4m yqeta VNIR (H) 0.56 pm 4m 0.66 pm 4m 0.88 pm 4m @sit@surface@temveriture,@,water"@4pot Al cloud,,',radiation, VIRS (L) 0.63 jim 2 krn 1.6 pm 2 Ian 3.75 pm 2 km 10.8 prn 2 krn 12 pm 2 Ian 42 Appendix P: Detailed deocriptiono of oome Freocrit and Future Flatformo/5cnooro ADEOS AVNIR: JAPAN Mission/Instrument name: ADEOS / Advanced Visible & Near-Infrared Radiometer (AVNIR) Operating organizations: National Space Development Agency of Japan (NASDA) Operational date: August 1996 to July 1999 Number of satellites: 1 Satellite Orbit Altitude: -797 kin Inclination: -98.6 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30-+:15 descending nodal crossing Ground track repeat interval: 41 days and 585 orbits Instrument Bands VNIR PAN Band: 1 2 3 4 1 5 Spectral range from gm: 0.42 0.52 0.61 0.76 0.52 to: 0.50 0.60 0.69 0.89 0.69 Signal to noise ratio: >200 >200 >200 >200 >90 Ground sample distance in: 16 16 16 16 8 Viewing Geometry Instrument field of view: 5.7 deg Scene dimension at nadir: 80 kin x 80 kin Instrument field of regard: �40 deg <-> �700 km Along-track tilt: fixed nadir Stereo capability: cross-track Precisions Radiometric calibration accuracy: Accuracy of on-board calibration using internal lamp and sunlight is �5% RMS ground location accuracy: [not provided] Collection/Return Capacity Min. revisit time w1cross-track tilt: 3 days at equator Onboard storage: 3 x 72 Gb (total satellite capacity) Max. contiguous one-pass coverage: 80 kin x -5000 km = -400 k sq kin Ground network (nominal): I station; additional stations can be supported within satellite resources Avg. land data collection per orbit: -500 k sq kin System annual land data colledion capability: 300 M sq kin Technical Contact Name: Yoshio Tange Title: Sr. Eng., E0S Address: NASDA, Hamamatsu-cho Central Bldg 1-29-6 Hamamatsu-cho, Minato-ku Tokyo, 105 JAPAN Phone: 81-3-5401-8663 Fax: 81-3-5401-8702 e-mail: n/a 43 Appendix P (corltiriue6i) ALMAZ OPTICAL: RUSSIA & SAR CORP. .Mission/Instrument name: ALMAZ Mulit-Sensor Satellite System Operating organizations: Russia (RSA) & SAR Corp. (Sokol-Almaz Radar) Operational date: Mid 1998 Number of satellites: 3: ALMAZ 1B (1998) followed by ALMAZ 1C & ALMAZ 2 Satellite Orbit Altitude: 397 km nominal; 388-404 km range Inclination: 72.7 deg Local mean solar time at equatorial crossing: n/a Ground track repeat interval: 10.8 days and 168 orbits Instrument Bands & Viewing Geometry Optronic Equipment for Stereography (OES), Mulitzone High-Resolution Electronic Scanner (MSU-E), Multizone Middle-Resolution Optomechanical Scanner (MSU-SK), Spectro-Radiometer for Ocean Satellite Monitoring (SROSM) Band: OES MSU-E MSU-SK SROSM VIS IR Spectral range from pm: 0.5 0.5 0.54 10.4 0.405 0.475 to: 0.6 0.6 0.6 12.6 0.422 0.785 Spectral range from pm: 0.6 0.6 0.6 0.433 0.843 to: 0.7 0.7 0.7 0.453 0.884 Spectral range from Am: 0.7 0.8 0.7 0.480 3.6 to: 0.8 0.9 0.8 0.500 3.9 Spectral range from gm: 0.58 0.8 0.510 10.5 to: 0.8 (PAN) 1.0 0.530 11.5 Spectral range from gm: 0.555 11.5 to: 0.575 12.5 Spectral range from jim: 0.655 to: 0.675 Signal to noise ratio: Ground sample distance in: 4/2.5(PAN) 10 80 300 600 Viewing Geometry histrurtient field of view: OES 80 kin CT x 180 k AT; MSU-E 2 x 24 km; MSU-SK VIS: 2 x 300 km IR: +/-39 deg 300 km; SROSM 2 x 1100 km Scene dimension at nadir: Instrument field of regard: OES 30 deg <-> 300 km; MSU-E 2 x 550 km; MSU-SK VIS: 2 x 550 kin IR: 300 km; SROSM 2 x 1100 km Along-track tilt: Stereo capability: OES 1001%, using fore /aft 25 deg tilt; CE(.9) = 5 in LE(.9) = 5 m Precisions Radiometric calibration accuracy: [not provided] RMS ground location accuracy: [not provided] CollectiontRetum Capacity Min. revisit time w/cross-track tilt: 3 days at the equator Onboard storage: 32 Gb Max. contiguous one-pass coverage: [not provided] Ground network (nominal): 3 stations Avg. land data collection per orbit: OES 370 k sq km; MSU-E 350-700 k sq km; MSU-SK 3.7 M sq km; SROSM 60 M sq km System annual land data collection capability: OES 2,044 M sq km; MSU-E 1,890-4,410 M sq km; MSU-SK 20,300 M sq km; SROSM 329,175 M sq Ian Technical Contact Name: Pavel Shirokov Title: Director c/o Jean-Pierre Schwartz, Program Manager Address: SAR Corp. Suite 800 818 Connecticut Ave, NW Washington, DC 20006 Phone: 202-628-1144 and 7-095-307-9194 Fax: 202-331-8735 and 7-095-302-2001 e-mail: 44 Appendix 0 (oontirluecl) ALMAZ SAR: RUSSIA & SAR CORP. Mission /Instrument name: ALMAZ Mulit-Sensosr Satellite System Operating organizations: Russia (RSA) & SAR Corp. (Sokol-Almaz Radar) Operational date: Mid 1998 Number of satellites: 3: ALMAZ 1B (1998) followed by ALMAZ 1C & ALMAZ 2 Satellite Orbit Altitude: 397 km nominal; 388-404 kin range Inclination: 72.7 deg Local mean solar time at equatorial crossing: n/a Ground track repeat interval: 10.8 days and 168 orbits SAR Sensors & Viewing Geometry I-SLR-3 (side Looking Radar); 2-SAR-3 Narrow Mode; 3-SAR-10 Narrow Mode; 4-SAR-10 Intermediate Mode; 5- SAR-10 Survey Mode; 6-SAR-70 1 2 3 4 5 6 Wavelength cm: 3.49 3.49 9.58 9.58 9.58 70 Survey slide: left left left left left left View angle off nadir deg: 38-60 25-51 25-51 25-51 25-51 25-51 Beam slip angle deg: 49.1 63.3 63.3 63.3 63.3 63.3 to: 23.0 34.3 34.3 34.3 34.3 34.3 Slant range km: 518 444 444 444 444 444 to: 895 00 670 670 670 670 Effective coverage width km: 450 330 330 330 330 330 Swath width km: 450 20-30 30-55 60-70 120-170 120-170 Resolution 190-250 5-7 5-7 5-7 22-40 22-40 (range x azimuth) in: 1200-20005-7 5-7 is 30 30 Stereo capability: n/a multi-pass multi-pass multi-pass Signal polarization (xmit/rcv): V/V V/V H/H V/VH,H/VH V/V - V/VH,H/VH Contrast sensitivity dB: 2-3 2-2.5 2-2.5 1.5-2 1-1.5 1 Avg. land data collection per orbit k: 1,400 76 80-450 80-450 80450 330-450 Sys annual land collection capability M: 7,650 420 480-2460 480-2460 480-2460 1800-2400 Precisions Radiometric calibration accuracy: [not provided] RMS ground location accuracy: (not provided] Collection/Retum Capacity Min. revisit time w/cross-track tilt: 3 days at the equator Onboard storage: 32 Gb Max. contiguous one-pass coverage: [not provided] Ground network (nominal): 3 stations Technical Contact Name: Pavel Shirokov Title: Director c/o Jean-Pierre Schwartz, Program Manager Address: SAR Corp. Suite 800 818 Connecticut Ave, NW Washington, DC 20006 Phone: 202-628-1144 and 7-095-307-9194 Fax: 202-331-8735 and 7-095-302-2001 e-mail: 45 Appendix 0 (comtimued) ALOS AVNIR-2: JAPAN Mission/Instrument name: ALOS / Advanced Visible & Near-Infrared Radiorneter-2 (AVNIR-2) Operating organizations: National Space Development Agency of Japan (NASDA) Operational date: Launch February 2002 Number of satellites: I Satellite Orbit Altitude: 700 kin (TBR) Inclination: 98.1 deg (TBR), Sun synchronous Local mean solar time at equatorial crossing: 10:30-+:15 (TBR) descending nodal crossing Ground track repeat interval: 45 days (TBR) Instrument Bands Multispectral PAN Band: 1 2 3 4 1 fore nadir aft Spectral range from gm: 0.42 0.52 0.61 0.76 0.52 0.52 0.52 to: 0.50 0.60 0.69 0.89 0.77 0.77 0.77 Signal to noise ratio: 200 200 200 200 70 70 70 Ground sample distance in: 10 10 10 10 2.5 2.5 2.5 Viewing Geometry Multispectral PAN Instrument field of view: 5.8 deg 2.9 deg Scene dimension at nadir: 70 x 70 kin 35 x 35 km Instrument field of regard: �40 deg <-> �1.5 deg <-> �613 km �35 kin Along-track tilt: fixed nadir fixed �40 deg + nadir Stereo capability: cross-track simultaneous fore, aft, nadir Precisions Radiometric calibration accuracy: not available RMS ground location accuracy: 2.5 m Collection/Return Capacity Min. revisit time w/cross-track tilt: MS: 2 days; PAN: 45 days at equator Onboard storage: 706 Gb Max. contiguous one-pass coverage: MS: 70 x 20,000 kin = 1,400 k sq kin PAN: 35 x 20,000 km 700 k sq kin Ground network (nominal): Data Relay Satellite & direct transmission to ground stations Avg. land data collection per orbit: MS: 420; PAN: 210 k sq km System annual land data collection capability: NIS: 1120; PAN: 560 M sq km Technical Contact Name: Takashi Hamazaki Title: Senior Engineer Address: NASDA, Hamamatsu-cho Central Bldg 1-29-6 Hamamatsu-cho, Minato-ku Tokyo, 105 JAPAN Phone: 81-3-5401-8556 Fax: 81-3-5401-8702 e-mail: [email protected] Appendix 0 (continued) ALOS VSAR: JAPAN Mission/Instrument name: ALOS / VSAR Operating organizations: National Space Development Agency of Japan (NASDA) Operational date: Launch February 2002 Number of satellites: 1 Satellite Orbit Altitude: 700 kin (TBR) Inclination: 98.1 deg (TBR), Sun synchronous Local mean solar time at equatorial crossing: 10:30�:15 (TBR) descending nodal crossing Ground track repeat interval: 45 days (TBR) instrument Bands Band: L Bandcenter Mhz: 15 Polarization: Signal to ambiguity ratio dB: Signal to noise ratio dB: -15 Ground sample distance in: 10 Viewing Geometry Instrument field of view: Scene dimension at nadir: 70 x 70 km Instrument field of regard: 18-48 deg off-nadir range <-> 600 km Along-track tilt: n/a Stereo capability: interaferomtry Precisions Radiometric calibration accuracy: not available RMS ground location accuracy: 2.5 in Collection/Retum Capacity Min. revisit time w/cross-track tilt: 2 days at the equator Onboard storage: 706 Gb Max. contiguous one-pass coverage: 70 km x 20,000 km = 1,400 k sq kin Ground network (nominal): normally use Data Relay Satellite Avg. land data collection per orbit: 420 k sq km System annual land data collection capability: 560 M sq km Technical Contact Name: Takashi Harnazaki Title: Senior Engineer Address: NASDA, Harnamatsu-cho Central Bldg 1-29-6 Hamamatsu-cho, lvhnato-ku Tokyo, 105 JAPAN Phone: 81-3-5401-8556 Fax: 81-3-5401-8702 e-mail: hamazakiQrd.tksc.nasda.go.jp 47 Appendix 0 (continued) CBERS CCD & IRMSS: CHINA-BRAZIL Mission/Instrument name: China-Brazil Earth Resources Satellite (CBERS) - CCD Camera & Infrared Multispectral Scanner (IRMSS) Operating organizations: Chinese Academy of Space Technology (CAST) (satellite) & Insituto de Pesquisas Espaciais (INPE) Operational date: October 1997 Number of satellites: 1 Satellite Orbit Altitude: 78 kin Inclination: 98 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 26 days and 337 orbits Instrument Bands CCD IRMSS Band: 1 2 3 4 5 1 6 7 8 9 Spectral range from Wn: 0.45 0.52 0.63 0.77 0.51 0.5 1.55 2.08 10.4 to: 0.52 0.59 0.69 0.89 0.73 1.1 1.75 2.35 12.5 Signal to noise ratio: 36.6 41.1 42.0 45.0 48.0 24 20 17 1.2K Ground sample distance in: 20 20 20 20 20 80 80 80 160 Viewing Geometry Instrument field of view: 8.4 deg (CCD) & 8.8 deg (IRMSS) Scene dimension at nadir: 120 km CT x 778 km AT Instrument field of regard: �32 deg <-> 600 kin Along-track tilt: fixed Stereo capability: Adjacent orbits Precisions Radiometric calibration accuracy: Stability <1%; Internal calibrators 2% [relative??]; & External calibrators 10% [absolute ??] RMS ground location accuracy: 200 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 3 days at equator, 2-3 days at �50 lat Onboard storage: 40 Gb (experimental) Max. contiguous one-pass coverage: 4000 Ian by 120 km = 480,000 sq km Ground network (nominal): 2 stations (China, Brazil) Avg. land data collection per orbit: 200,000 sq km System annual land data collection capability: 250 M sq kin Technical Contact Name: Prof. Chen Yiyuan Title: Chief Engineer Address- Chinese Academy of Space Technology P.O. Box 2417 Beijing, CHNA Phone: 86-10-837-9423 Fax: 86-10-837-8237 e-mail: 48 Appendix 0 (continue&i) CLARK: USA (NASA) & CTA Mission/Instrument name: Small Spacecraft Technology Initiative (SSTI) "Clark" / Worldview sensor Operating organizations: NASA Headquarters, Spacecraft Systems Div. & CTA Systems Operational date: September 1996 Number of satellites: 1 Satellite Orbit Altitude: 476 kin Inclination: 97.3 deg, Sun synchronous Local mean solar time at equatorial crossing: 11:15 descending nodal crossing Ground track repeat interval: 20 days and (TBS) orbits Instrument Bands PAN Multispectral Band: 1 2 3 4 Spectral range from gm: 0.45 0.50 0.61 0.79 to: 0.80 0.59 0.68 0.89 Signal to noise ratio: Ground sample distance m: 3 15 15 15 Viewing Geometry Instrument field of view: Scene dimension at nadir: Panchromatic: 6 krn x 6 km; Multispectral: 30 kin x 30 kin Instrument field of regard: �30 deg <-> (TBS) km Along-track tilt: �30 deg <-> (TBS) kin Stereo capability: Yes - fore and aft pointing Precisions Radiometric calibration accuracy: [not provided) RMS ground location accuracy: <100 rn Collection/Return Capacity Min. revisit time w/cross-track tilt: 4-5 days at equator Onboard storage: 1.37 Gb Max. contiguous one-pass coverage: Pan: 34,00 sq kin Ground network (nominal): 3 stations (Livermore CA, Fairbanks AK, Kiruna SV%7E) Avg. land data collection per orbit: 000 sq km System annual land data collection capability: 0 M sq kin Technical Contact Name: Dr. Robert J. Hayduk Title: Program Manager Address: NASA Headquarters, Code XS Washington, DC 20546 Phone: 202-358-4690 Fax: 202-358-2697 e-mail: [email protected] 49 Appendix 0 (contirlued) EARLYBIRD X QUICKBIRD: EARTHWATCH mission/Instrument name: EarthWatch EarlyBird Panchromatic and Multicolor EarthWatch QuickBird Panchromatic and Multicolor Operating organizations: EarthWatch, Incorporated Operational date: EarlyBird: 1996 QuickBird: 1997 Number of satellites: 2 of each Satellite Orbit Altitude: 470 kin Inclination: Sun synchronous Local mean solar time at equatorial crossing: [not provided] Ground track repeat interval: [not provided] Instrument Bands EarlyBird QuickBird Band: Pan Green Red NearIR I Pan Blue Green Red NearIR Spectral range from jim: 0.45 0.50 0.61 0.79 0.45 0.45 0.53 0.63 0.77 to: 0.80 0.59 0.68 0.89 0.90 0.52 0.59 0.69 0.90 Signal to noise ratio: [not provided] [not provided) Ground sample distance m: 3 15 15 15 1 4 4 4 4 Viewing Geometry Instrument field of view: Scene dimension at nadir: EarlyBird Panchromatic: 6 kin x 6 kin EarlyBird Multicolor: 30 kin x 30 kin QuickBird Panchromatic: [not provided] QuickBird Multicolor: 30 kin x 30 kin Instrument field of regard: �30 deg xxx kmj Along-track tilt: �30 deg xxx km] Stereo capability: Precisions Radiometric calibration accuracy: EarlyBird: 8 bit quantization QuickBird: 11 bit quantization [calibration not provided) RMS ground location accuracy: [not provided] Collection/Return Capacity Min. revisit time w/cross-track tilt: [not provided] Onboard storage: yes Max. contiguous one-pass coverage: [not provided] Ground network (nominal): store-and-forward to EarthWatch stations Avg. land data collection per orbit: EarlyBird: [not provided) QuickBird: 100 30km x 30 kin = 90,000sq kin System annual land data collection capability: 34.2 M sq kni Notes [See NASAS "Clark" mission for additional information on EarlyBird like instrument.] Technical exchange of sensor data with early customers is being done at a detailed level on a contract-by-contract basis. Technical Contact Name: Doug Gerull Title: President & CEO Address: EarthWatch, Incorporated 1900 Pike Road Longmont, CO 80501-6700 Phone: 303-682-3800 Fax: 303-682-3848 e-mail: 50 Appendix P (continued) EOS ASTER: Japan& USA Mission/Instrument name: EOS-AMI / Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) Operating organizations: Japan (MITI & Japan Resources Observation System Organization) & NASA /JPL Operational date: Late 1998 Number of satellites: 1 Satellite Orbit Altitude: 705 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 �15 descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands VNIR SWIR Band: 1 2 3N,B 1 4 5 6 7 8 9 Spectral range from gm: 0.52 0.63 0.76 1.600 2.145 2.185 2.235 2.295 2.360 to: 0.60 0.69 0.86 1.700 2.185 2.225 2.285 2.365 2.430 Signal to noise ratio h: >140 >140 >140 140 54 54 54 70 54 Ground sample distance in: 15 15 15,17 30 30 30 30 30 30 TTR Band: 10 11 12 13 14 Spectral range from gm: 8.125 8.475 8.925 10.25 10.95 to: 8.475 8.825 9.275 10.95 11.65 Signal to noise ratio h: <0.3 K <0.3 K <03 K <0.3 K <03 K Ground sample distance in: 90 90 90 90 90 Viewing Geometry VNIR SWIR, TIR Instrument field of view: 5 deg (5.3 deg band 3B) 4.9 deg Scene dimension at nadir: 60 kin CT 60 kin CT Instrument field of regard: �24 deg <-> 314 kin --t8.55 deg <-> 106 kin Along-track tilt: 3B tilted 27.6 deg fixed Stereo capability: In-track, 3B (back) & 3N (nadir) -> B/H=0.6 Precisions Radiometric calibration accuracy: Bands 1-9: �4% absolute radiometry calibrated by halogen lamps. Bands 10-14: � K (270-340 K). �2 (240-370 K); cal. by onboard blackbody. RMS ground location accuracy: VNIR: <90 in; SWIR 6 m;TIR 31.5 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 16 days at equator, 7-9 days at �45 lat; VNIR only: 4-7 days at equator Onboard storage: share of EOS 140 Gb solid-state recorder Max. contiguous one-pass coverage: VNIR, SWIR: 8% duty cycle <-> 60 kin x 3400 kin = 250 k sq kin. TIR duty cycle and coverage twice as large Ground network (nominal): Primary data return via TDRSS to processing and archives in Japan and at USGS/EDC, Sioux Falls Avg. land data collection per orbit: 205 k sq kin System annual land data collection capability: 1090 M sq km Technical Contact Name: Masahiko Kudoh Name: Dr. Hiroji Tsu Name: Dr. Anne B. Kahle Title: Project Manager Title: Science Team Leader Title: Science Team Leader Address: JAROS Address: ERSDAC (USA) Towa-Hatchobori Bldg Forefront Tower Address: JPL Mail Stop 183-501 2-20-1 Hatchobori Chuo-ku 3-12-1 Kachidoki Chuo-ku Pasadena, CA 91109 Tokyo, 104 JAPAN Tokyo, 104 JAPAN Phone: 81-3-5543-1061 Phone: 81-3-3533-9380 Phone: 818-354-7265 Fax: 81-3-5543-1067 Fax: 81-3-3533-9383 Fax: 818-354-0966 e-mail: e-mail: [email protected] e-mail: [email protected] 51 Appendix 0 (corltiriuc6l) EOS LATI (Option D: NASA Mission/Inst-ument name: EOS-AM2 / Landsat Advanced Technology Instrument (LATI) Option I Operating organizations: NASA & other US government (TBD) Operational date: 2004 Number of satellites: 1, follow-on to Landsat 7 Satellite Orbit Altitude: 705.3 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:00 descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands PAN VNIR SWIR Atmos Band: 8 1 2 3 4 5 5' 7 5 bnd Spectral range from gm: 0.50 0.45 0.52 0.63 0.76 1.55 1.2 2.08 0.8 to: 0.90 0.52 0.60 0.69 0.90 1.75 1.3 2.35 1.4 Signal to noise ratio: consistent with Landsat 7 continuity Ground sample distance m: 15 30 30 30 30 30 30 30 240 Viewing Geometry Instrument field of view: 15 deg Scene dimension at nadir: 185 km CT x 170 kin (nominal) AT Instrument field of regard: �30 degrees Along-track tilt: fixed nadir Stereo capability: none Precisions Radiometric calibration accuracy: Uses full aperture solar diffuser, standard ground scenes, and precise atmospheric compensation techniques to achieve 5% absolute radiometry. RMS ground location accuracy: < 250 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 3 days at equator, 2 days �60 lat Onboard storage: (TBD), optimized with cloud editing and lossless data compression Max. contiguous one-pass coverage: (TBD) Ground network (nominal): Primary station at USGS/EDC, Sioux Falls SD + 1 supplementary station at Fairbanks AK for real-time & playback collection to archives; cooperating intl. ground stations for local real-time collection Avg. land data collection per orbit: >540,000 sq kin System annual land data collection capability: >2,800 M sq km Technical Contact Name: Dr. Darrel Williams Title: Landsat Project Scientist Address: Biosperic Sciences Branch, Code 923 NASA/Goddard Space Flight Center Greenbelt, MD 20771 Phone: 301-286-7282 Fax: 301-286-0239 e-mail: [email protected] 52 Appendix D (coritirlued) EOS LATI (Optio; MID: NASA Mission/Instrument name: EOS-AM2 / Landsat Advanced Technology Instrument (LATI) Option H Operating organizations: NASA & other US goverrinient (TBD) Operational date: 2004 Number of satellites: 1, follow-on to Landsat 7 Satellite Orbit Altitude: 705.3 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:00 descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands Band: PAN VNIR SWIR Spectral range from gm: 0.5 0.4 1.2 to: 0.7 0.9 2.4 No. of hperspectral chan: 1 50 24 Signal to noise ratio: consistent with continuity Ground sample distance in: 10 20 20 Viewing Geometry Instrument field of view: 15 deg Scene dimension at nadir: 185 kin CT x 170 kin (nominal) AT Instrument field of regard: �30 deg (TBR) Along-track tilt: fixed nadir Stereo capability: none Precisions Radiometric calibration accuracy: Uses transfer radiometer for intercomparison with (advanced?) MODIS, standard ground scenes, and Moon-look techniques to achieve 5% (TBR) absolute radiometry. RMS ground location accuracy: < 250 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 3 days at equator, 2 days �60 lat Onboard storage: (T7BD), optimized with cloud editing, lossless data compression, hyperspectral data compression, and/or onboard data aggregation Max. contiguous one-pass coverage: (TBD) Ground network (nominal): Primary station at USGS/EDC, Sioux Falls SD + I supplementary station at Fairbanks AK for real-time & playback collection to archives; add'I real-time collection at intl. ground stations Avg. land data collection per orbit: >540,000 sq km System annual land data collection capability: >2,800 M sq km Notes Annual collection: Based on 250 scenes/day to archives. Additional scenes collected at international ground stations Technical Contact Name: Dr. Darrel Williams Title: Landsat Project Scientist Address: Biosperic Sciences Branch, Code 923 NASA/Goddard Space Flight Center Greenbelt, MD 20771 Phone: 301-286-7282 Fax: 301-286-0239 e-mail: [email protected] 53 Appendix D (cotitimued) EOS MODIS: USA (NASA) Mission/Instrument name: EOS-AMI, PM-1 / Moderate Resolution Imaging Spectrometer (MODIS) Operating organizations: NASA/GSFC Operational date: Late 1998 (AM-1), 2000 (PM-1) Number of satellites: 2 Satellite Orbit Altitude: 705 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30-+:15 (AM-1); 13:30-+:15 (PM-1) descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands Sharpening VNIR SWIR Ocean Thermal VNIR Atmosphere Band: 1-2 3-4 5-7 8-19 8-36 Spectral range from pm: 0.6 0.46 1.2 0.4 1.3 to: 0.9 0.57 2.2 1.0 14.3 Signal to noise ratio: >500 Ground sample distance in: 250 500 500 1000 1000 (see Appendix E: MODIS characteristics at bottom of file) Viewing Geometry Instrument field of view: �55 deg Scene dimension at nadir: �1150 kin CT Instrument field of regard: nadir centered Along-track tilt: fixed Stereo capability: n/a Precisions Radiometric calibration accuracy: <3gm: 5% absolute radiometry >3@=: 1% absolute radiometry calibrated by halogen lamps, onboard blackbody, solar viewing RMS ground location accuracy: Collection/Return Capacity Min. revisit time w/cross-track tilt: 2 days at equator Onboard storage: share of EOS 140 Gb solid-state recorder Max. contiguous one-pass coverage: continuous operation; reflection bands on daylit side only Ground network (nominal): primary data return via TDRSS to processing and archives at GSFC Avg. land data collection per orbit: System annual land data collection capability: Technical Contact Name: Dr. Vincent V. Salomonson Title: Science Team Leader Address: NASA/Goddard Space Flight Center Code 900 Greenbelt, MD 20771 Phone: 301-286-8601 Fax: 301-286-1738 e-mail: [email protected] 54 Appendix D (coritinued) EROS-1,2: Israel Mission/histrument name: EROS-1, 2 Operating organizations: Israel Aircraft Industries and Core Software Technology Operational date: 1995 & 1997 Number of satellites: 2 Satellite Orbit Altitude: 480 krn Inclination: 97.4 deg, Sun synchronous Local mean solar time at equatorial crossing: [not provided] Ground track repeat interval: [not provided] Instrument Bands Band: PAN VNIR Spectral range from gm: 0.50 [not provided] to: 0.90 [not provided] Signal to noise ratio: [not provided] [not provided] Ground sample distance in: 1.8/11.5 Viewing Geometry Instrument field of view: [not provided] Scene dimension at nadir: EROS-1: 11 kin CT x 55 kin AT; EROS-2:15 kin CT x 55 kin AT Instrument field of regard: �30 deg <-> xxx km Along-track tilt: fixed nadir Stereo capability: [not provided] Precisions Radiometric calibration accuracy: [not provided] RMS ground location accuracy: 800 m Collection/Retum Capacity Min. revisit time w/cross-track tilt: 3 days at equator Onboard storage: [not provided] Max. contiguous one-pass coverage: 11 or 15 kin by 55 kin 605 or 825 sq kin Ground network (nominal): [not provided] Avg. land data collection per orbit: [not provided] System annual land data collection capability: [not provided] Notes General: (These missions have not been formally announced. They are believed to be awaiting Israel government policy decisions.] Along track tilt: EROS uses a fon-to-aft slew technique to reduce effective scene motion at the focal plane, and increase integration time. Technical Contact Name: [not provided] Title: Address: Phone: 55 Appendix D (continued) ERS-1/2 SAR: ESA Mission/Instrument name: ERS-1 /2 Synthetic Aperture Radar (SAR) Operating organizations: European Space Agency (ESA) Operational date: July 1991 & (TBS) Number of satellites: 2 Satellite Orbit Attitude: -780 km Inclination: 98.5 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval; 35 days and 501 orbits Instrument Bands Band: C Bandcenter Ghz: 5.3 Bandwidth MHz: 15.55 Polarization: V/V Integrated sidelobe ratio dB: 8 Ground sample distance in: 30 AT; <=26.3 CT Viewing Geometry Instrument field of view: 20.1 deg to 25.9 deg Scene dimension at nadir: 102.5 km CT (80.4 km full performance) Instniment field of regard: fixed 250 kin offset, right from nadir Along-track tilt: n/a Stereo capability: none Precisions Radiometric calibration accuracy: n/a RMS ground location accuracy: 1 kin Collection/Return Capacity Min. revisit time w/cross-track tilt: 35 days at equator, 16 days �60 lat Onboard storage: none Max. contiguous one-pass coverage: 10 min -> 100 km x 4000 km = 400 K sq kin Ground network (nominal): 22 stations Avg. land data collection per orbit: 3500 sq kin System annual land data collection capability: n/a; Avg production from processing is 8000 scenes per year (TBS) M sq km Technical Contact Name: Alberto Combardi, ERS Title: Product Manager Address: Eurimage Via D'Onofrio 212 RomeITALY Phone: 39-6406-941 Fax: 39-6-406-94232 e-mail: (TBS) 56 Appendix 0 (comtlnue6f) GDE SYSTEMS Mission/Instniment name: (TBD) Operating organizations: GDE Systems, Inc., et al. Operational date: Late 1998 Number of satellites: at least one Satellite Orbit Altitude: 704 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands Band: 1 Spectral range from gm: 0.5 to: 0.9 Signal to noise ratio: >4 Ground sample distance m: 0.8-1.0 Viewing Geometry Instrument field of view: 1.2 deg Scene dimension at nadir: 15 km CT Instrument field of regard: �45 deg (CT) <-> 700 kin Along-track tilt: �45 deg <-> 700 kin Stereo capability: Single pass fore/aft imaging along track or within �45 deg cross track. Maximum single pass stereo image size is 70 x 70 km Precisions Radiometric calibration accuracy: not applicable RMS ground location accuracy: 1500 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 1.8 days at equator, 1.5 days at �30 lat Onboard storage: 30 Gb Max. contiguous one-pass coverage: 15 kin x 1600 kin = 24 k sq km Ground network (nominal): 7 stations Avg. land data collection per orbit: 20,000 sq kin per ground station System annual land data collection capability: 102 M sq kin (7 stations) Technical Contact Name: Sean Crook Title: Chief Engineer Address: GDE Systems, Inc. RO. Box 509008 San Diego, CA 92150-9008 Phone: 619-592-5395 Fax: 619-592-5407 e-mail: [email protected] 57 Appendix D (oontimue6i) IRS-1B LISS 1 & 2: INDIA & EOSAT Mission/Instrument name: IRS-1B (Indian Remote Rending Satellite) LISS I (Linear Imaging Self Scanccer) & LISS 2 Operating organizations: National Remote Sensing Agency (NRSA) Operational date: August 1991 Number of satellites: 1 Satellite Orbit Altitude: 904 krn Inclination: 99,028 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:25�:20 descending nodal crossing Ground track repeat interval: 22 days and 307 orbits Instrument Bands LISS 1 LISS 2 Band: 1 2 3 4 1 1 2 3 4 Spectral range from gm: 0.45 0.52 0.62 0.77 0.45 0.52 0.62 0.77 to: 0.52 0.59 0.68 0.86 0.52 0.59 0.68 0.86 Signal to noise ratio: 155 155 155 155 142 152 155 147 Ground sample distance m: 72.5 72.5 72.5 72.5 36.25 36.25 36.25 36.25 Viewing Geometry LISS 1 LISS 2 Instrument field of view: 9.4 deg 2 at 4.7 deg each Scene dimension at nadir: 148.48 kin C/T 2 x 74.24 kin C/T, by 174 kin AT by 87 kin AT Instrument field of regard: fixed nadir fixed nadir Along-track tilt: fixed nadir fixed nadir Stereo capability: n/a n/a Precisions Radiometric calibration accuracy: Uses internal calibrator; �1 digital number (relative calibration) RMS ground location accuracy: 1500 M Collection/Return Capacity Min. revisit time w/cross-track tilt: 22 days at equator Onboard storage: none Max. contiguous one-pass coverage: (T13S) Ground network (nominal): 2 stations Avg. land data collection per orbit: (TBS) sq krn System annual land data collection capability: (TBS) M sq kin Technical Contact Name: Mark Altman Title: Scientist Address: EOSAT 4300 Forebes Boulevard Lanham, MD Phone: 301-552-0535 Fax: 301-552-3028 58 Appendix D (continue.6i) IRS-1C LISS 3, PAN, WFS: INDIA & EOSAT Mission/Instrument name: IRS-lC (Indian Remote Rending Satellite) / LISS 3 (Linear Imaging Self Scanner) & Panchromatic WIFS (Wide Field Sensor) Operating organizations: National Remote Sensing Agency (NRSA) Operational date: December 1995 Number of satellites: 1 Satellite Orbit Altitude: 817 kin Inclination: 98.691 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30-+:05 descending nodal crossing Ground track repeat interval: 24 day s and 341 orbits Instrument Bands LISS 3 PAN WFS Band: 1 2 3 4 5 1 3 4 Spectral range from lim: 0.52 0.62 0.77 1.55 0.5 0.62 0.77 to: 0.59 0.68 0.86 1.7 0.75 0.68 0.86 Signal to noise ratio: >128 >128 >128 >128 >64 >128 >128 Ground sample distance m: 23.5 23.5 23.5 70.5 5.8 188 188 Viewing Geometry LISS 3 PAN WFS Instrument field of view: 4.7 deg Scene dimension at nadir: 141 x 141 km 70 x 70 km 770 x 770 km Instrument field of regard: fixed nadir �26 deg <-> fixed nadir �398 km; 0.2 deg steps Along-track tilt: fixed nadir fixed nadir fixed nadir Stereo capability: n/a cross-track n/a Precisions Radiometric calibration accuracy: Uses internal calibrator; �1 digital number (relative calibration) RMS ground location accuracy: 1500 in Collection/Retum Capacity Min. revisit time w/cross-track tilt: LISS 3: 24 days at equator PAN: 5 days at equator WFS: 5 days at equator Onboard storage: 62 Gb <-> 24 minutes of playback data consisting of (1 /2 PAN swath) or (LISS 3 + WFS) Max. contiguous one-pass coverage: playback: 14,400 km x 140 km = 2.0 M sq km (PAN) Ground network (nominal): 2 stations (Hyderabad & Norman OK) provide real-time coverage of So. Asia & N. Am., plus playback Avg. land data collection per orbit: (TBS) sq km System annual land data collection capability: (TBS) M sq km Technical Contact Name: Mark Altman Title: Scientist Address: EOSAT 4300 Forbes Boulevard Lanham, MD Phone: 301-552-0535 Fax: 301-552-3028 e-mail: Appendix D (contimued) IRS-P2 LISS 2: INDIA & EOSAT Mission/Instrument name: IRS-P2 (Indian Remote Rending Satellite) / LISS 2 (Linear Imaging Self Scanner) Operating organizations: National Remote Sensing Agency (NRSA) Operational date: October 1994 Number of satellites: 1 Satellite Orbit Altitude: 817 km Inclination: 98.691 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30-+:05 descending nodal crossing Ground track repeat interval: 24 days and 341 orbits Instrument Bands VNIR Band: 1 2 3 4 Spectral range from wn: 0.45 0.52 0.62 0.77 to: 0.52 0.59 0.68 0.86 Signal to noise ratio: >127 >127 >127 >127 Ground sample distance in: 36* 36* 36* 36* Viewing Geometry Instrument field of view: 4.7 deg Scene dimension at nadir: 67 km C/T, by 87 kin AT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: n/a Precisions Radiometric calibration accuracy: Uses internal calibrator; digital number (relative calibration) RMS ground location accuracy: 2200 in Collection/Retum Capacity Min. revisit time w/cross-track tilt: 24 days at equator Onboard storage: none Max. contiguous one-pass coverage: (TBS) Ground network (nominal): 2 stations Avg. land data collection per orbit: (TBS) sq kin System annual land data collection capability: (TBS) M sq kin Notes Ground sample distance: 32.74 x 37.39 in in object space resampled to 36m x 36m in output products Technical Contact Name: Mark Altman Title: Scientist Address: EOSAT 4300 Fores Boulevard Lanham, MD Phone: 301-552-0535 Fax: 301-552-3028 e-mail: 60 Appendix D (comtimueJ) JERS-1 OPS: JAPAN Mission/Instrument name: JERS-1 /Optical Sensor (OPS) Operating organizations: National Space Development Agency of Japan (NASDA) Operational date: September 1992 Number of satellites: 1 Satellite Orbit Altitude: 568 kin Inclination: 97.67 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:45-+:15 descending nodal crossing Ground track repeat interval: 44 days and 659 orbits Instrument Bands VNIR SWIR Band: 1 2 3 4 1 5 6 7 8 Spectral range from gm: 0.52 0.63 0.76 0.76 1.60 2.01 2.13 2.27 to: 0.60 0.69 0.86 0.86 1.71 2.12 2.25 2.40 Signal to noise ratio: (high lev) 242-398 69-117 (low lev) 65-96 19-26 Ground sample distance m: 18.3 in CT, 24.2 in AT Viewing Geometry Instrument field of view: 7.55 deg Scene dimension at nadir: 75 x 75 kin Instrument field of regard: fixed nadir Along-track tilt: fixed nadir, except band 4 tilted at 15.33 deg for Stereo capability. In track with bands 3 & 4 -> B/1-1=0.3 Precisions Radiometric calibration accuracy: RMS error of input radiance calibrated with AVIMS < 0.27-4.15 W m-2 sr-1 um-1 RMS ground location accuracy: 100 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 44 days at equator Onboard storage: 72 Gb Max. contiguous one-pass coverage: 75 km x 9000 krn = 675 k sq km Ground network (norninal): 15 stations Avg. land data collection per orbit: 675 k sq km System annual land data collection capability: 10 M sq kin [suspect meant "10,000 M"] Technical Contact Name: Noboru Takata Title: Project Manager Address: JAROS, Towa-Hatchobori Bldg. 2-20-1 Hatchobori Chuo-ku Tokyo, 104 JAPAN Phone: 81-2-5543-1061 Fax: 81-3-5543-1067 e-mail: n/a Appendix() (comtitiueJ) JERS SAR: JAPAN Mission/Instrument name: JERS-1 / Synthetic Aperture Radar (SAR) Operating organizations: National Space Development Agency of Japan (NASDA) Operational date: September 1992 Number of satellites: 1 Satellite Orbit Altitude: 568 km Inclination: 97.67 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:45�:15 descending nodal crossing Ground track repeat interval: 44 days and 659 orbits Instrument Bands Band: L Bandcenter Mhz: 15 Polarization: H/H Signal-to-ambiguity ratio dB: 22 Signal-to-noise ratio dB: -6 Ground sample distance in: 18 (3 looks) Viewing Geometry Scene dimension at nadir: 75 x 75 kin Instrument field of regard: 335 deg range in off-nadir angle Along-track tilt: n/a Stereo capability: adjoining passes or orbits Precisions Radiometric calibration accuracy: <1dB RMS ground location accuracy: 100 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 44 days at equator 44 [?] days at �30 lat Onboard storage: 72 Gb Max. contiguous one-pass coverage: 75 km x 9000 kin = 675 k sq kin Ground network (nominal): 15 stations Avg. land data collection per orbit: 675 k sq kin System annual land data collection capability: 30 M sq kin Technical Contact Name: Noboru Takata Title: Project Manager Address: JAROS, Towa-Hatchobori Bldg. 2-20-1 Hatchobori Chuo-ku Tokyo, 104 JAPAN Phone: 81-2-5543-1061 Fax: 81-3-5543-1067 e-mail: n/a 62 Appendix 0 (cotitinued) KOMSAT HRC: Korea Mission/Instrument name: Korean Mapping Satellite (KOMSAT) High Resolution CCD (HRC) Operating organizations: Korean Aerospace Research Institute Operational date: Number of satellites: I Satellite Orbit Altitude: 600-800 (TBD) kin Inclination: (TBD) deg, Sun synchronous Local mean solar time at equatorial crossing: (TBD) Ground track repeat interval: (TBD) Instrument Bands VNIR Band: PAN I B1 B2 B3 Spectral range from jim: 0.51 0.43 0.61 0.78 to: 0.73 0.49 0.68 0.89 Signal to noise ratio: 150 80 170 170 Ground sample distance in: 10 20 20 20 Viewing Geometry Instrument field of view: Scene dimension at nadir: 40 kin CT Instrurnent field of regard: as needed to achieve min revisit time Along-track tilt: fixed nadir Stereo capability: yes, LE 20 in Precisions Radiometric calibration accuracy: RMS ground location accuracy: +2,000 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 2 days at 34 lat Onboard storage: 1 Gb Max. contiguous one-pass coverage: Ground network (nominal): Korea Ground Station Avg. land data collection per orbit: System annual land data collection capability: Note General: [This material is based on functional requirements in the RFRI Technical Contact Name: [not provided] Title: Address: Phone: Fax: e-mail: 63 Appendix 0 (comtimueed) LANDSAT 5 TM: EOSAT Mission/Instrument name: Landsat 5 / Thematic Mapper JM) Operating organizations: EOSAT Operational date: March 1984 Number of satellites: 1, to be replaced by Landsat 7 in 1998 Satellite Orbit Altitude: 705.3 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 937 (mean), 9:19 (actual, 9/95) descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands VNIR SWIR TIR Band: 1 2 3 4 1 5 7 1 6 Spectral range from gm: 0.45 0.52 0.63 0.76 1.55 2.08 10.42 to: 0.52 0.60 0.69 0.90 1.75 2.35 12.50 Signal to noise ratio: 52 60 48 35 40 21 0.12K Ground sample distance in: 30 30 30 30 30 30 120 Viewing Geometry Instrument field of view: 15.39 deg Scene dimension at nadir: 185 km CT x 170 km (nominal) AT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: none Precisions Radiometric calibration accuracy: Uses onboard lamps to achieve <10% absolute radiometry RMS ground location accuracy: �250 in Collection/Retum Capacity Min. revisit time w/cross-track tilt: 16 days at equator, 8 days �60 lat Onboard storage: none Max. contiguous one-pass coverage: real-time to ground stations only Ground network (nominal): 15 stations Avg. land data collection per orbit: n/a System annual land data collection capability: n/a Note Signal to noise ratio: At minimum scene radiance for TIR band, noise-equivalent temperature Technical Contact Name: MarkAltman Title: Scientist Address: EOSAT 4300 Forbes Boulevard Lanham, MD Phone: 301-552-0,535 Fax: 301-552-3028 Appendix P (contitiucJ) LANDSAT7 Mission /Instrument name: Landsat 7/ Enhanced Thematic Mapper-Plus (ETM+) Operating organizations: NASA/GSFC (spacecraft), NOAA(s at.ops.), USGS (arc) Operational date: December 1998 Number of satellites: 1, follow-on to Landsat 5 Satellite Orbit Altitude: 705.3 kin Inclination: 98.2 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:00 descending nodal crossing Ground track repeat interval: 16 days and 233 orbits Instrument Bands PAN VNIR SWIR TIR Band: 8 1 1 2 3 4 1 5 7 1 6 Spectral range from grn: 0.50 0.45 0.52 0.63 0.76 1.55 2.08 10.42 to: 0.90 0.52 O@60 0.69 0.90 1.75 2.35 12.50 Signal to noise ratio: Ground sample dist: 15 30 30 30 30 30 30 60 Viewing Geometry Instrument field of view: 15.39 degrees Scene dimension at nadir: 185 km Cr x 170 kin (nominal) AT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: none Precisions Radiometric calibration accuracy: Uses onboard lamps, full aperture solar diffuser, partial aperture solar imager, standard ground scenes, and intercomparison with MODIS to achieve 2% relative (band-to-band) & 5% absolute radiometry. RMS ground location accuracy: (TBS) Collection/Return Cal2ag4 Min. revisit time w/cross-track tilt: 16 days at equator, 8 days at �60 lat Onboard storage: 380 Gb Max. contiguous one-pass coverage: 30 min -> 185 kin by 12,600 kin = 1.07 M sq kin Ground network (nominal): Primary station at USGS/EDC, Sioux Falls SD + 1 supplementary station at Fairbanks AK for real-time & playback collection to archives; cooperating intl. ground stations (-18) for local real-time collection. Avg. land data collection per orbit: 540,000 sq kin System annual land data collection capability: 2,800 M sq km Notes Annual collection: Based on 250 scenes/day to archives. Additional scenes collected at international ground stations. Technical Contact Name: S. Kenneth Dolan Title: Deputy Project Manager Address: Landsat Project, Code 430 NASA Goddard Space Flight Center Greenbelt, MD 20771 Phone: 301-286-7962 Fax: 301-286-1744 e-mail: (TBS) (555 Appendix P (coritirlued) LEWIS: USA (NASA) & TRW Mission/Instrument name: Small Spacecraft Technology Initiative (SSTI) "Lewis" / Hyperspectral Imager (HSI) & Linear Etalon Imaging Spectral Array (LEISA) Operating organizations: NASA Headquarters, Spacecraft Systems Div., TRW, & GSFC Operational date: (TBS) 1996 Number of satellites: I Satellite Orbit Altitude: 523 krn Inclination: 97.0 deg, Sun synchronous Local mean solar time at equatorial crossing: (TBS) descending nodal crossing Ground track repeat interval: (TBS) days and (TBS) orbits Instrument Bands HSI HSI HSI LEISA Band: Pan VNIR SWIR SWIR Spectral range from Wn: 0.45 0.4 0.9 1.0 to: 0.75 1.0 2.5 2.5 Spectral resolution rim: 5 6.25 3-8 Signal to noise ratio: (high rad) >200 >150 (low rad) >50* >10* Ground sample distance in: 5 30 30 300 Viewing Geometry Instrument field of view: Scene dimension at nadir: Panchromatic: 13 kin Hyperspectral: 7.7 kin LEISA: 77 kin Instrument field of regard: LEISA: �60 deg <-> (TBS) kin Along-track tilt: LEISA: �15 deg <-> (TBS) kin Stereo capability: n/a Precisions Radiometric calibration accuracy: Calibration by reclosable cover/diffuser & tungsten lamp Pan: <20 (absolute [not provided]) HS: <6% (relative[not provided]) RMS ground location accuracy: Collection/Return Capacity Min. revisit time w/cross-track tilt: 4-5 days at equator Onboard storage: 4 Gb Max. contiguous one-pass coverage: (TBS) sq kin Ground network (nominal): 2 stations (TRW Chantilly VA, Fairbanks AK) Avg. land data collection per orbit: (TBS) sq km System annual land data collection capability: (TBS) M sq kin Notes Signal to noise ratio: stimated from published curve at 85% & 5% albedo, outside atm. absorption bands. Along-track tilt:: LEISA uses forward-look for cloud cuing to HSI Technical Contact Name: [not provided] Title: [not provided] Address: [not provided] Phone: [not provided] Fax: [not provided] e-mail: [not provided] (50 Appendix P (coritinued) Z5RBVIEW - Mission/Instrument name: OrbView-1 Operating organizations: OrbImage, an OSC Company Operational date: 1st quarter 1998 Number of satellites: Initially one satellite, to be followed by a second after 2 years SatelHte Orbit Altitude: 460 kin Inclination: 97.25 def, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: Not an exact repeating orbit [approx. 3 days and 46 orbits] Instrument Bands PAN VNIR Band: 1 2 1 3 4 5 6 Spectral range from vm: 0.45 0.45 0.45 0.52 0.63 0.76 to: 0.90 0.90 0.52 0.60 0.69 0.90 Signal to noise ratio: >10 >10 >10 >10 >10 >10 Ground sample distance in: 1 2 8 8 8 8 Viewing Geometry Instrument field of view: 1 deg Scene dimension at nadir: 8 kin x 8 km for 2 in GSD panchromatic Instrument field of regard: �45 deg <-> 460 kin Along-track tilt: �45 deg <-> 460 kin Stereo capability: Same-pass stereo capability accommodated Precisions Radiometric calibration accuracy Periodic radiometric and geometric calibrations will be accomplished RMS ground location accuracy: < 15 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 3 days at equator, 2 days �60 W Onboard storage: 32 Gb Max. contiguous one-pass coverage: 92 kin by 85 kin = 7820 sq kin Ground network (nominal): 3 stations Avg. land data collection per orbit: 23,460 sq kin System annual land data collection capability: 34.2 M sq kin Technical Contact Name: Bill Hohwiesner Title: Director, Program Development Address: Orbital Sciences Corporation 21700 Atlantic Boulevard Dulles, VA 20166 Phone: 703-406-5443 Fax: 703-406-3505 e-mail: bhohw,@orbital.com 67 Appemdix 0 (oomtinucJ) PRIRODA MOMS: GERMANY& RUSSIA Mission/Instrument name: Priroda / MOMS (Modular Optoelectronic Multispectral Stereoscanner) Operating organizations: Germany (DARA) & Russia (RSA) Operational date: Spring 1996 for 18 months Number of satellites: 1 Satellite Orbit Altitude: pproximately 400 km Inclination: 51.6 deg Local mean solar time at equatorial crossing: n/a Ground track repeat interval: n/a Instrument Bands Band: 1 2 3 4 1 PAN I Fore, Aft Spectral range from gm: 0.45 0.53 0.65 0.77 0.52 0.52 to: 0.51 0.57 0.68 0.81 0.76 0.76 Signal to noise ratio: 5 10 10 2.5 Ground sample distance in: 18 18 18 18 6 18 Viewing Geometry Instrument field of view: 15 deg Scene dimension at nadir: PAN: 40 kin CT x 120 km AT others: 80 kin CT x 240 kin AT Instrument field of regard: fixed nadir Along-track tilt: fixed sensor channels at +/-21.4 deg Stereo capability: fore, aft, & nadir Precisions Radiometric calibration accuracy: dynamic range > 1200 gray levels; atm. com through concomitant MOS spectrometer RMS ground location accuracy: 1-2 in Collection/Retum Capacity Min. revisit time w/cross-track tilt: varying Onboard storage: 385 Gb Max. contiguous one-pass coverage: (TBS) Ground network (nominal): 2 stations: Neutrelitz D & Moscow RUS Avg. land data collection per orbit: (TBS) System annual land data collection capability: (TBS) Technical Contact Name: Peter Seige Title: Project Manager Address: DLR-OP P.O. Box 1116 82230 Wessling GERMANY Phone: 49-8153-28-2766 Fax: 49-8153-28-1349 Appemdix D (contirlued) RADARSAT: CANADA Mission/Instrument name: RADARSAT / Synthetic Aperture Radar (SAR) Operating organizations: Canadian Space Agency Operational date: October 1995 launch Number of satellites: 1, with follow-ons Satellite Orbit Altitude: 798 kin nominal Inclination: 98.6 deg Local mean solar time at equatorial crossing: 1800 ascending nodal crossing Ground track repeat interval: 24 days and 343 orbits Sar Sensors Modes Fine Standard Wide ScanSar-N ScanSar-W Ext-H Ext-L Incidence angle range deg: 37 20 20 20 20 49 10 48 49 49 46 49 50 23 Slant range km: Effective coverage wid km: 500 500 Soo 500 500 Nominal swath width km: 50 100 150 300 500 75 170 Nominal resolution m: 10 30 30 50 100 25 35 Instrument Bands Band: C Spectral range from Ghz: 5.6 Polarization: H/H Dynamic range dB: 30 Ground sample distance in: 10-100 Viewing Geometry Instrument field of view: Scene dimension at nadir: 100 kni x 100 kin to 500 kin x 500 kin Instrument field of regard: 10 - 60 deg from nadir, normally right Along-track tilt: n/a Stereo capability: adjoin passes or orbits Precisions Radiornetric calibration accuracy: 1 dB within 100 km x 100 kin scene RMS ground location accuracy: 1500 kni Collection/Return Capacity Min. revisit time w/cross-track tilt: 5 days at the equator, 3.5 days at �30 lat Onboard storage: 72 Gb Max. contiguous one-pass coverage: 500 kin x 6720 kin = 2,260 k sq kin Ground network (nominal): 3 stations Avg. land data collection per orbit: 2,200 k sq kin System annual land data collection capability: 4,000 M sq km Notes Field of regard: Twice during 5 year mission, spacecraft will be turned around forhorninal 2-wk period each to provide left-looking SAR, allowing complete coverage of Antarctica Technical Contact Name: Dr. Surendra Parashar Title: Deputy Director, RADARSAT Address: Mission Systems & Operations Canadian Space Agency 6767 Route de I'Aeroport Saint-Hubert, Quebec J3Y 8Y9 CANADA Phone: 514-926-4412 Fax: 514-926-4433 e-mail: parashars@sp-agencyca (59 Appendix 0 (cotitinucJ) RESOURCE21 Mission/Instrument name: Resource2l. Operating organizations: Resource2l Operational date: 1998-1999 Number of satellites: 4 in orbit + ground spare Satellite Orbit Altitude: 743.4 kin Inclination: 98.36 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 7 days and 101 orbits (each spacecraft) Instrument Bands cirrus Band: 1 2 3 4 5 1 6 Spectral range from gm: 0.45 0.52 0.63 0.775 1.55 1.23 to: 0.52 0.60 0.68 0.90 1.65 1.53 Signal to noise ratio: (high radiance) 119 140 123 171 464 (low radiance) 49 50 36 52 133 Ground sample distance in: 10 10 10 10 20 100+ Viewing Geometry Instrument field of view: 15.9 deg Scene dimension at nadir: 205 kin CT x 1-4000 kin AT Instrument field of regard: �40 deg <-> �1270 kin Along-track tilt: �30 deg Stereo capability: yes Precisions Radiometric calibration accuracy: Absolute accuracy <10%; relative accuracy <2%; pol. sensitivity <5% Calibration using Sun and ground targets Atmospheric compensation by cirrus band & ground truth & atm. modeling RMS ground location accuracy: 30 in Collection/Return Capacity Min. revisit time w/cross-track tilt: Twice in 25 min per day at equator; 2-3 times in 25-50 min at 30 lat Twice weekly with nadir view only Onboard storage: 176 Gb Max. contiguous one-pass coverage: 205 kin x 4000 kin = 820 k sq kin Ground network (nominal): 3 stations Avg. land data collection per orbit: 820 k sq kin per satellite System annual land data collection capability: 7,200 M sq kin Technical Contact Name: Victor H. Leonard Title: Manager, System Development Address: Resource2l M/S 8X-59 P.O. Box 3999 Seattle, WA 98124-2499 Phone: 206-393-0098 Fax: 206-393-1080 e-mail: [email protected] 70 Appendix 0 (coritinued) SAC-C MMRS: Arge-n-t"i"n-a Mission/Instrument name: SAC-C / MMRS Operating organizations: Comision Nacional de Actividades Espaciales (CONAE) Operational date: October 1998 - October 2002 Number of satellites: 1 Satellite Orbit Altitude: 601 kni Inclination: 97.3 deg, Sun synchronous Local mean solar time at equatorial crossing: 11:00 [descending?] nodal crossing Ground track repeat interval: 9 days and 14 orbits Instrument Bands VNIR SWIR Band: 1 2 3 4 1 5 Spectral range from gm: 0.48 0.54 0.62 0.77 1.55 to: 0.50 0.56 0.68 0.81 1.70 Signal to noise ratio: 663 710 684 687 2700 Ground sample distance in: 150 150 150 150 150 Viewing Geometry Instrument field of view: 33.35 deg Scene dimension at nadir: 315 kin CT x 315 kin AT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: n/a Precisions Radiometric calibration accuracy: (TBD) RMS ground location accuracy: 2250 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 9 days at equator, 8 days �30 lat Onboard storage: 16 Mb Max. contiguous one-pass coverage: 315 kin by 3500 kin = 1.1 M sq kin Ground network (nominal): 4 stations Avg. land data collection per orbit: 1,000 k sq km System annual land data collection capability: [not provided] M sq kni Technical Contact Name: Juan Yelos Title: CONAE Address: Bajada del Cerro s/n Parque Gral. San Martin 5500 Mendoza ARGENTINA Phone: 54-61-288654 Fax: 5"1-288565 e-mail: 71 Appendix D (comtitiue,@) SICH-1 MSU: Ukraine Mission/Instrument name: SICH-1 / Medium Resolution Scanner MSU-S & Low Resolution Scanner MSU-M Operating organizations: National Space Agency of the Ukraine Operational date: September 1995 Number of satellites: I Satellite Orbit Altitude: 650 kin Inclination: 82.5 deg [97.5 deg?] Local mean solar time at equatorial crossing: [not provided] Ground track repeat interval: [not provided] Instrument Bands MSU-S MSU-M Band: 1 2 1 1 2 3 4 Spectral range from pm: 0.55 0.1 0.5 0.6 0.7 0.8 to: 0.7 1.0 0.6 0.7 0.8 1.0 Signal to noise ratio: Ground sample distance in: 410 410 2000 2000 2000 2000 Viewing Geometry Instrument field of view: Scene dimension at nadir: MSU-S: 1100 km CT MSU-M: 1900 kin CT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: n/a Precisions Radiometric calibration accuracy: [not provided] RMS ground location accuracy: [not provided] Collection/Return Capacity Min. revisit time w/cross-track tilt: (TBS) Onboard storage: [not provided] Max. contiguous one-pass coverage: [not provided] Ground network (nominal): [not provided] Avg. land data collection per orbit: [not provided] System annual land data collection capability: [not provided) Technical Contact Name: Victor Zubko, Title: Chief of NSAU Address: Remote Sensing Dept. 11, Bozhenka Stn 252022, Kyiv-22 UKRAINE Phone: 380-44-261-08-27 Fax: 380-44-269-50-58 e-mail: [email protected] 72 Appendix D (contimued) SPACE IMAGING Mission/Instrument name: Space Imaging; Commercial Remote Sensing System Operating organizations: Space Imaging, Inc. Operational date: December 1997 Number of satellites: 2 Satellite Orbit Altitude: 628 kin Inclination: 98.1 deg, Sun synchronous Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 11 days and 161 orbits Instrument Bands PAN VNIR Band: 1 1 2 3 4 5 Spectral range from gm: 0.45 0.45 0.52 0.63 0.76 to: 0.90 0.52 0.60 0.69 0.90 Signal to noise ratio: >10 >10 >10 >10 >10 Ground sample distance m: 1 4 4 4 4 Viewing Geometry Instrument field of view: 0.93 deg Scene dimension at nadir: 11 kin CT x 100+ kin AT Instrument field of regard: �45+deg <-> 680+ kin Along-track tilt: �45+deg <-> 680+ kin Stereo capability: Both fore/aft and cross-track Precisions Radiometric calibration accuracy. External calibration, �4.5% linearity, relative accuracy �4.3%, absolute -+9.5/o RMS ground location accuracy: 6 m Collection/Return Capacity Min. revisit time w/cross-track tilt: 11 days at equator, 9-10 days at �30 lat (at 109/6 tilt) Onboard storage: 64 Gb Max. contiguous one-pass coverage: 72 krn by 140 km = 10,080 sq km Ground network (nominal): 3 statons assumed, 4 expected Avg. land data collection per orbit: 22 k sq kin System annual land data collection capability: 110 M sq kin Notes Signal to noise ratio: SNR is peak to peak at Nyquist for 30 deg solar elevation, 10% low reflectivity & 2:1 contrast ratio at entrance aperture Min revisit time: Revisit time substantially less with tilt > 10 deg Technical Contact Name: Fran Gerlach Title: Director, Program Analysis and Performance Evaluation Address: Space Imaging 9351 Grant Street Thornton, CO 80229 Phone: 303-254-2051 Fax: 303-254-2211 e-mail: [email protected], 73 Appemdix D (oontinucJ) SPIN-2 KVR-1000, TK-350: RUS91A & commercial s7p-pliers Mission /Instrument name: SPIN-2 / KVR-1000 Panoramic Camera & TK-350 Topographic Camera Operating organizations: Interbranch Association "SOVINFORMSPUTNIK" Operational date: Regular launches since 1987 with 2+ months collection per mission Number of satellites: 1 Satellite Orbit Altitude: 190-270 km Inclination: 65 deg Local mean solar time at equatorial crossing: not applicable Ground track repeat interval: 8-15 days and 130-240 orbits Instrument Bands Instrument: KVR-1000 TK-350 Spectral range from gm: 0.58 0.58 to: 0.72 0.72 Signal to noise ratio: n/a n/a Ground sample distance m: 2 10 Viewing Geometry KVR-1000 TK-350 Instrument field of view: 10 deg AT x 40 deg CT 75 deg [diagonal ?] Scene dimension at nadir: 40 krn AT x 160 km CT 300 km AT x 200 kni CT Instrument field of regard: nadir ctr, pan scan fixed nadir Along-track tilt: fixed fixed nadir Stereo capability: none 60% or 80% AT overlap Precisions Radiometric calibration accuracy: not applicable RMS ground location accuracy: not applicable Collection/Return Capacity Min. revisit time w/cross-track tilt: 8-15 days at equator, 6-12 days at �30 lat Onboard storage: film Max. contiguous one-pass coverage: continuous running Ground network (nominal): n/a Avg. land data collection per orbit: n/a System annual land data collection capability: n/a Notes Ground sample distance: applies to the digitally scanned output Orbital elements: may be adjusted during mission lifetime to collect desired scenes Annual land data collection: test. 2A M sq kin per mission of 2-3 months] Technical Contact Name: David Baraniak Name: VN. Lavrov Title: President Title@ Deputy General Director Address: Lambda Tech International Address: Interbranch Association "SOVINFORMSPUTNIK" W239 N1812 Rockwood Drive, Suite 100 47 Leningradskiy Prospect Waukesha, WI 53188 125167 Moscow RUSSIA Phone: 414-523-1215 Phone: 7-09-594-30757 Fax: 414-523-1219 Fax: 7-50-194-30585 e-mail: [email protected] e-mail: [email protected] Name: George Palesh Name: James M. Newlin Title: Title: Manager, Russian Imagery Sales Address: DBA Systems Inc., Commercial Imagery Address: Autometric Inc. P.O. Drawer 550 5301 Shawnee Road 1200 S. Woody Burke Alexandria, VA 22312-2333 Melbourne, FL 32902 Phone: 407-727-0660 Phone: 703-658-4000 Fax: 407-727-7019 Fax: 703-658-4426 e-mail: gpalesh(Rdba-sys.com e-mail: [email protected] 74 Appendix 0 (continued) SPOT HRV, HR-VIR, HRG: France Mission/Instrument name: SPOT (Satellite Pour l'Observation de la Terre) / HRV (Haute Resolution Visible), HRVIR, & HRG Operating organizations: Centre Nationale des d'Etudes Spatiales (CNES) & SPOT Image Operational date: February 1986 to 1998+ (SPOT-1/2/3); Late 1997 to 2002+ (SPOT4); 2000 to 2010+ (SPOT-5A/B) Number of satellites: 3 (SPOT-1/2/3) with 2 HRV; 1 (SPOT4) with 2 HRVIR instruments; 2 (SPOT-5A/B) with 3 HRG on each Satellite Orbit Altitude: 832 kin Sun synchronous Inclination: 98.7 deg Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 26 days and 369 orbits Instrument Bands Band: 1 2 3 4 1 PAN Spectral range from gm: 0.50 0.61 0.79 1.58 0.51 to: 0.59 0.68 0.89 1.75 0.73 Signal to noise ratio HRV measured: 190-240 140-250 250-270 n/a 130-205 HRVIR specified: 165 140 170 127 100 BRG specified: 120 100 120 130 120 Ground sample distance HRV in: 20 20 20 n/a 10 BRVIRm: 20 20 20 20 20 HRG in: 10 10 10 20 5 Viewing Geometry HRV, HRVIR HRG Instrument field of view: 2x 4.13 deg 3 x 4.13 deg Scene dimension at nadir: 60kmCTx6OkmAT Instrument field of regard: �27 deg <-> �870 kin Along-track tilt: fixed nadir �19.2 deg & nadir Stereo capability: cross-track both along-track & cross-track Precisions Radiometric calibration accuracy: < 10% RMS ground location accuracy: 300 - 500 in Collection/Return Capacity Min. revisit time w/cross-track tilt: 2.9 days at equator, 2.4 days 30 lat Onboard storage: HRV 132 Gb = 2 x 22 min x 50 Mbps; BRVIR 240 Gb 2 x 40 min x 50 Mbps; HRG 90 Gb Max. contiguous one-pass coverage: HRVHRVIR 120 x 2000 kin = 240 k sq kin HRG 180 x 2500 kin = 450 k sq kin Ground network (nominal): BRV 15 stations; HRVIR 15-18 stations; HRG 15-20 stations Avg. land data collection per orbit: HRV 260 k sq kin; HRVIR 300 k sq km; HRG 400 k sq kin System annual land data collection capability: HRV 1200 M sq km; HRVIR 1500 M sq km; HRG 2000 M sq kin Notes Signal to noise ratio: HRV: Computed from real images HRVIR, HRG: Specification; real performance should be better Annual collection: HRV. 3,300,000 images from 1986-1995; 1200 M sq kin per year - 180 M cloudfree sq km per year HRVIR: Estimate 1500 M sq kin per year - 200 M cloudfree sq kin per year BRG: Estimate 2000 M sq km per year - 300 M cloudfree sq kin per year Technical Contact Name: Alain Baudoin Name: Terry Busch Title: Earth Observation Group Title: Address: CNES Address: SPOT Image Corporation 2 place Maurice Quentin 1897 Preston White Drive 75039 Paris Cedex 01 Reston, VA 22091-4368 FRANCE Phone: 33-1-4476-7810 Phone: 703-715-3125 or 800-275-7768 Fax: 33-1-4476-7867 Fax: 703-648-1813 e-mail: e-mail: [email protected] 75 Appendix P (comtinue6i) !Sru I Vegetation: France Mission/Instrument name: SPOT (Satellite Pour l'Observation de la Terre) / VEGETATION Operating organizations: Centre Nationale des d'Etudes Spatiales (CNES) & SPOT Image Operational date: Late 1997 to 2010+ Number of satellites: 3 (SPOT-4/5A/B) Satellite Orbit Altitude: 832 kin Sun synchronous Inclination: 98.7 deg Local mean solar time at equatorial crossing: 10:30 descending nodal crossing Ground track repeat interval: 26 days and 369 orbits Instrument Bands Band: 1 2 3 4 Spectral range from gm: 0.43 0.61 0.78 1.58 to: 0.47 0.68 0.89 1.75 Signal to noise ratio spec: 134 234 279 222 Ground sample distance in: 1150 1150 1150 1150 Viewing Geometry Instrument field of view: �50.5 deg Scene dimension at nadir: 2200 kin CT Instrument field of regard: fixed nadir Along-track tilt: fixed nadir Stereo capability: n/a Precisions Radiometric calibration accuracy: absolute: <5%; interband & multitemporal <3% RMS ground location accuracy: 1000 in (spec); 500 in (goal) Collection/Return Capacity Min. revisit time w/cross-track tilt: 1.3 days at equator, 1 day at 30 lat Onboard storage: 2.2 Gb Max. contiguous one-pass coverage: 2200 krn x 20,000 kin Ground network (nominal): 1 primary + (TBD) local stations Avg. land data collection per orbit: 15Msqkm System annual land data collection capability: 70 G sq kin Notes Satellite: To be confirmed on SPOT-5A, to be decided on SPOT-513 Signal to noise ratio: Specification; real performance should be better Technical Contact Name: Alain Baudoin Name: Terry Busch Title: Earth Observation Group Title: Address: CNES Address: SPOT Image Corporation 2 place Maurice Quentin 1897 Preston White Drive 75039 Paris Cedex 01 Reston, VA 22091-4368 FRANCE Phone: 33-1-4476-7810 Phone: 703-715-3125 or 800-275-7768 Fax: 33-1-4476-7867 Fax: 703-648-1813 e-mail: e-mail: [email protected] 76 Appendix 0 (continued) Band Center Width IFO Purpose (nm. or um) (nm or um) (m) Land & Cloud Boundaries 1 645 50 250 Veg chlorophyll abs land cover trans 2 858 35 250 Cloud & vegetation land cover trans Land & Cloud Properties 3 469 20 500 Soil, veg differences 4 555 20 500 Green vegetation 5 1240 20 500 Leaf canopy properties 6 1640 24.6 500 Snow/cloud differences 7 2130 50 500 Land & cloud properties Ocean Color 8 412 15 1000 Cholorphyll 9 443 10 1000 Cholorphyll 10 488 10 1000 Cholorphyll 11 531 10 1000 Cholorphyll 12 551 10 1000 Sediments, atmosphere 13 667 15 1000 Sediments 14 678 10 1000 Cholorphyll fluorescence 15 748 10 1000 Aerosol properties 16 869 15 1000 Aerosol, atmos. properties Atmosphere/Clouds 17 905 30 1000 Cloud/atm properties 18 936 10 1000 Cloud/atm properties 19 940 50 1000 Cloud/atrn properties Thermal 20 3.750 0.180 1000 Sea surface temp 21 3.959 0.060 1000 Forest fires, volcanoes 22 3.959 0.060 1000 Cloud/ sft temp 23 4.050 0.060 1000 Cloud/ sft temp 24 4.465 0.065 1000 Trop temp/cld fract 25 4.515 0.067 1000 Trop temp/cld. fract 26 1.375 0.030 1000 Trop temp / cld. fract 27 6.715 0.360 1000 Upper-trop humidity 28 7.325 0.300 1000 Mid-trop humidity 29 8.550 0.300 1000 Sfc temp 30 9.730 0.300 1000 Total ozone 31 11.030 0.500 1000 Cloud/sfc temp, 32 12.020 0.500 1000 Cloud/sfc temp 33 13.335 0.300 1000 Cld. height & fraction 34 13.635 0.300 1000 CId height & fraction 35 13.935 0.300 1000 CId height & fraction 36 14.235 0.300 1000 CId height & fraction IIIIIHIIIIIIIII 3 6668 14100 7494