[From the U.S. Government Printing Office, www.gpo.gov]








            APPLICATION OF SATELLITE DATA
            FOR MAPPING AND MONITORING WETLANDS
            Fact Finding Report



            Federal Geographic Data Committee
            Wetlands Subcommittee

            Technical Report 1
            September 1992































                                             Federal Geographic Data Committee
                )artment of Agriculture - Department of Commerce - Department of Defense  Department of Energy
                )epartment of Housing and Urban Development    Department of the Interior Department of State
   TA595.5                     Department of Transportation  Environmental Protection Agency
   .U55A66                      I Federal Emergency Management Agency - Library of Congress
   1992          National Aeronautics and Space Administration - National Archives and Records Administration
                                                 Tennessee Valley Authority









                                                      Federal Geographic Data Committee


                   Established by Office of Management and Budget Circular A-16, the Federal Geographic Data Committee
                   (FGDC) promotes the coordinated development, use, sharing, and dissemination of geographic data.

                   The FGDC is composed of representatives from the Departments of Agriculture, Commerce, Defense,
                   Energy, Housing and Urban Development, the Interior, State, and Transportation; the Environmental
                   Protection Agency, the Federal Emergency Management Agency-, the Library of Congress; the National
                   Aeronautics and Space Administration; the National Archives and Records Administration; and the
                   Tennessee Valley Authority. The Departments of Education, Health and Human Services, Justice, and
                   Labor; the General Services Administration; and the National Capital Planning Commission also participate
                   on FGDC subcommittees and working groups. The U.S. Geological Survey chairs the committee on the
                   behalf of the Secretary of the Interior.

                   FGDC subcommittees work on issues related to data categories coordinated under the circular.
                   Subcommittees establish and implement standards for data content, quality, and transfer; encourage the
                   exchange of information and the transfer of data; and organize the collection of geographic data to reduce
                   duplication of effort. Working groups have been established for standards, technology, and liaison with the
                   non-Federal community.

                   For more information about the committee, or to be added to the newsletter mailing fist, please contact:

                                                Federal Geographic Data Committee Secretariat
                                                            U.S. Geological Survey
                                                              590 National Center
                                                            Reston, Virginia 22092

                                                           Facsimile: (703) 648-5755
                                                            Internet: [email protected]



                   For more information about the FGDC wetlands subcommittee contact:


                                                        FGDC Wetlands Subcommittee
                                                         U.S. Fish and Wildlife Service
                                                       1849 C Street, N.W., ARLSO 400
                                                           Washington, D.C. 20240

                                                           Facsimile: (703) 358-2232



                   The following is the recommended bibliographic citation for this publication:
                       Federal Geographic Data Committee. 1992. Application of Satellite Data for Mapping and Monitoring
                   Wetlands - Fact Finding Report; Technical Report 1. Wetlands Subconinuittee, FGDC. Washington, D.C.
                   32 pages plus Appendices.



                                                     Federal Geographic Data Committee
                    Department of Agriculture e Department of Commerce * Department of Defense 0 Department of Energy
                      Department of Housing and Urban Development 9 Department of the Interior * Department of State
                                       Department of Transportation 0 Environmental Protection Agency
                                         Federal Emergency Management Agency 9 library of Congress
                         National Aeronautics and Space Administration * National Archives and Records Administration
                                                          Tennessee Valley Authority










                                                         Contents.


                                                                                                        Pne

               EXECUTIVE SUMMARY               ...........................................                  1


               INTRODUCTION         ......................         ............              ..........


               DISCUSSION       ....................................              ..........   ........     3


               CONCLUSIONS         ................................           .......................       6

               EXAMPLES OF COMBINING SATELLITE AND DIGITAL DATA DERIVED
                      FROM AERIAL PHOTOGRAPHY                   ..................................          8

               FACT FINDING QUESTIONS AND ANSWERS                       ..........................          9
                       1.     Is any data being currently collected over the conterminous United
                              States'. for which no, order has been previously placed?   ...........        9
                       2.     Is any Thematic Mapper data being processed- todjay?      ........            9
                       3.     How much did the last satellite scene cost that your organization
                              purchased and how long did it take to receive it?    ......  I..........     11
                       4.     Is each analysis performed as a unique operation, or can it be
                              performed on a routine basis on different scenes?     ...........
                       5.     Which of the Tbematic Mapper infrared bands, Number 4, 5, or 7,
                              are most important for wetland identification?    ...................        12
                       6.     How many wetland classes have you been able to successfully
                              discern using satellite data? Can you provide a Esting,of these
                              classes'? ..........................         @!  ...........*............    13
                       7.     Which wetland classes are the easiest to discern, and which classes
                              are the hardest? Please provide some statistical insight as to
                              relative accuracies . ......................................                 13
                       8.     Can you provide the committee. with quantitative or qualitative
                              information on wetland identification which is accurately related to
                              wetlaAd size, water regimes, and wetland coverage classesand
                              types?   ......................................                ......        14
                       9.     What do you believe is a reliable minimum mapping unit for
                              forested wetlands, scrub-shrub wetlands, open water ponds?       ........    16
                      10.     What are the problems associated with identifying narrow bands of
                              wetlands such as those found along tidal creeks or riparian wetlands,
                              which are found along streams and are. often very in@portant?    .......     17
                      11.     Dud to the scale of coverage, it has been reported that satellite data
                              consistently underestimate the* acreage of individual wetland basins.
                              If this is true, can a conversion factor be determined? Is the
                              underestimation a function of the size of the wetland basin or the
                              scale at which the satellite senses?  ...........................            18
                      12.     Have you had any success in identification of submerged aquatic
    Gctn
                              vegetation and/or grass flats?    ..............................             19
              US Department of Commerce
              NOAA Coastal Services Center Llbrar]Ki
              2234 South     Robson Avenue                              ftoperty Of c8c Libir"ry
              Charleston, Sc 29405-2413







                                                                                                         Page

                       13.     Can the 10-meter panchromatic data from SPOT help compensate
                               for the lack of Band 5 (1.55 to 1.75 pm) midinfrared radiance?      .....   21
                       14.     Have you had any success in using stereo data from SPOT to
                               increase your accuracy in wetland identification, classification, and
                               delineation?   ...........................................                  22
                       15.     Can a satellite be reprogrammed in flight so as to capture data for
                               different purposes?   ...................      I ...................        23
                       16.     Is georeferencing now sophisticated enough to allow for a pixel by
                               pixel analysis in order to perform change detection?     ...............    24
                       17.     How do you navigate on the ground to locate and identify 1 to 6 or
                               more pixels depicting change?    ................................           27
                       18.     How is National Wetlands Inventory digital data processed so that
                               they can be interfaced with Thematic Mapper digital data used by
                               Ducks Unlimited, and is this process done on a unique basis or a
                               routine basis?   ...........................................                28
                       19.     Do you agree with the following statement made by Dr. Gregory T.
                               Koeln, Director of Ducks'Unhmited's Habitat Inventory Program?         ...  29
                       20.     At what point can we expect to have permanent storage capability
                               so as to maintain captured digital data on an indefinite basis?    ......   30
                       21.     Data Quality Concerns     ....................................              31

                REFERENCE        ................       I......................................            32


                APPENDIXES


                A. Wetland classes used in waterfowl habitat and wetland inventory
                .B. SPOT Image product fee schedule
                C. EOSAT product fee schedule
                D. Acronyms


                                                           Figure

                1. An example of project rating error, where a small area is not registered
                       perfectly in all imagery  ..........................................                25



                                                            Table


                1. Undsat TM scenes being processed by'Ducks Unlimited on January 9, 1992 .... 10







                                                              iv
                                                                                            InOMV-1acisc SU
                                                              ywzdlol zo-2=o2                 ir,7azo') AAON
                                                                              omnevA vo-norl :iJL;02 t'E99











             EXECUTIVE SUMMARY

             The detail and reliability of information derived from satellite data have steadily
             improved. These improvements include advancements in spatial and spectral resolution,
             georeferencing, and digital image processing techniques, along with,growing experience
             using satellite data. Significant strides have been made in integrating ancillary data, such
             as soils and digital elevation models, into the classification of satellite data. This
             integration is dependent upon the use of geographic information system (GIS)
             technology. Stream gauging data and rainfall data are now being used to select the best
             scenes for wetland identification. Even with these improvements, satellite data can not
             match the accuracy of areal extent, classification detail, or reliability that can be
             extracted from conventional aerial photography using manual photo-interpretation
             techniques, such as those used by the U.S. Fish and Wildlife Service's (FWS) National
             Wetlands Inventory (NWI) Project. However, for some regions, satellite remote sensing
             may be the most cost-effective means for conducting reconnaissance wetland surveys.

             The power of satellite imagery lies in its ability to be easily integrated with all other
             sources of data in a GIS, contributing to the accuracy of the GIS. The U.S. Department
             of Agriculture's Soil Conservation Service (SCS) believes that satellite technology can
             help to classify certain administrative classes of wetlands legislated by the Farm Bills of
             1985 and 1990. Many other resource managers have complained that, in practical
             application, the promise of space-based remote sensing has not measured up to NWI
             actual performance. The subcommittee believes satellite data, when used in conjunction
             with NWI digital data produced through the use of aerial photography, can and do ,
             provide a tool for monitoring water levels in wetlands and monitoring the cover change
             of adjacent uplands. Synergistic effects created by combining both satellite data and
             NWI digital data have greater value than using either data source alone. Such data sets
             have the potential to be synoptic and accurate.


             ENTRODUCTION

             The President's Domestic Policy Council's Wetlands Task Force requested that the
             Federal Geographic Data Committee's Wetland Subcommittee produce a report about
             the application of satellite data for mapping and monitoring of wetlands. On January 14
             and 15, 1992, the subcommittee held a meeting to discuss the current application of
             satellite data for mapping and monitoring of wetlands. The subcommittee invited top
             level technical experts from the following organizations to address a pres et list of
             questions and describe their experiences:

                          Earth Observation Satellite Company (EOSAT)
                          SPOT Image Corporation (SPOT)
                          Ducks Unlimited (DU)
                          U.S. Environmental Protection Agency, Environmental Monitoring Systems
                            Laboratory (EPA)
                          National Oceanic and Atmospheric Administration (NOAA) Coast Watch


                                                         1










                              Change Analysis Program (C-CAP)
                                 A. Oak Ridge National Laboratory
                                 B. University of Delaware
                            Earth Satellite Corporation
                            U.S. Geological Survey (USGS), Earth Resources Observation System
                              (EROS) Data Center (EDC)
                            Maryland Department of Natural Resources, Water Resources
                              Administration (MD-DNR)

               On January 15, 1992, the Wetlands Subcommittee met to discuss the information gained
               from the previous days presentations, and to compare notes on the presentation of each
               speaker. The subcommittee drafted a fact-finding report that analyzed and consolidated
               the responses resulting from the January 14, 1992, meeting.

               Upon review of the draft report, SCS reviewers believed that the report did not fully
               reflect the latest findings in the use of satellites for mapping and monitoring wetlands.
               NASA!s Space Remote Sensing Center (SRSC) is conducting research and mapping
               wetlands for SCS in accordance with the Farm Bills of 1985 and 1990. SRSC's
               experience in mapping wetlands with satellite data has been primarily related to
               inventory efforts conducted by the SCS. Accuracy assessments conducted for the States
               of Mississippi and Arkansas by the SCS for every county in the Yazoo basin showed
               results that were superior to the original suggested SCS wetlands mapping techniques.
               As a result, the wetland classification used by SRSC for the Yazoo basin in the States of
               Mississippi and Arkansas is currently being used as baseline data for the SCS. SCS
               personnel have commented that, for this region, satellite remote sensing proved to be the
               only accurate and cost effective means of conducting a wetlands inventory for their
               agency. SRSC's mapping approach has yet to be documented in detail or published in
               the technical literature.


               On May 4, 1992, the Wetlands Subcommittee invited SRSC to make a presentation on
               their applications and to respond to the same questions answered by the speakers at the
               January 14, 1992 meeting. Employees from the SCS's National Cartographic and GIS
               Center (NCG) also made a presentation at the May 4th meeting. The SRSC and NCG
               presenters were not questioned by peer technical experts as were the presenters at the
               January 14, 1992, fact-finding meeting. This report includes the analysis and
               consolidated responses from both the January 14, 1992, and May 4, 1992, meetings.

               In many instances, DU answers and/or experiences are the only ones listed. This is
               because DU's Dr. Gregory Koeln was the first speaker and provided his answers in
               writing. Where subsequent speakers agreed with Dr. Koeln, his answer or experience
               was used. If subsequent speakers had different answers or additional experiences, these
               were included.









                                                         2











               -DISCUSSION

               The current limitations of satellite data that result in diminished utility for and accuracy
               of wetland identification and habitat classification can be categorized into two areas:

                       a.     Spectral Resolution

                              Spectral resolution problems result when the reflected radiance of different
                              land covers are very similar. Different land covers with similar radiance
                              have been placed in the same classification unit; for example, drier
                              forested wetlands being classified as upland forests; wetter scrub-shrub
                              wetlands being classified as either forested wetlands or emergent wetlands;
                              drier scrub-shrub wetlands being classified as upland forests; shadows from
                              forested areas falling onto agricultural lands being classified as emergent
                              wetlands; large, dense formations of tall emergent wetland plants, such as
                              Phragj]@ites spp., being classified as upland grassland or even upland
                              deciduous forests; and high coastal marsh, during low tide, being identified
                              as upland grassland. These problems in spectral resolution occur when the
                              satellite imagery is taken at a very wet time of the year or during a
                              drought. Many of the spectral resolution problems can be resolved or
                              ameliorated by using satellite imagery from several time periods that best
                              display wetland conditions. The process of merging multitemporal scenes
                              would result in profound cost increases for National programs, as well as
                              limit data useability for detecting change.

                       b.     Spatial Resolution

                              Each thematic mapper (TM) pixel represents an area 3        0 by 30 meters.
                              Theoretically, spatial resolution is defined as two pixels -- that is, a box two
                              pixels on a side, or a total of four pixels (approximately 1 acre for TM
                              data). In practice, however, it generally takes a box with three identical
                              pixels on a side (nine pixels or approximately 1.5 acres) to consistently
                              identify an object. If the object being classified does not have a square
                              shape, or if the adjacent land cover has a similar reflected radiance, or if
                              one or more of the pixels has a slightly different radiance, then the number
                              of pixels needed to make a consistently confident determination increases.
                              Although wetlands smaller than the theoretical limit have been accurately
                              delineated, some scientists believe they need as many as 25 pixels.
                              (approximately 5 acres) to be confident about certain classification units.
                              Other scientists believe that 25 pixels is a worse case scenario. Through
                              the uses of ancillary data and visual interpretation, smaller wetlands can be
                              successfully identified in treeless areas when the basin is nonvegetated, full
                              of water, and surrounded by the bare soil of an agricultural field or much
                              drier prairie grass that has a significantly different spectral reflectance.




                                                               3









               Spatial resolution has often been presented as the main shortcoming of wetlands
               mapping by satellite. In reality, the greater concern is the spectral resolution that results
               in the failure to distinguish wetlands from uplands. However, it is the spectral resolution,
               that now allows us to see differences in biomass and may allow us in the future to
               determine the health of wetlands.


               Not all wetland mapping has the objective of assigning habitat classifications to mapped
               wetlands, as does the NWI. For instance, the SCS's Swampbuster Program merely
               attempts to identify wetlands and assign to each entity one of a few operational
               classifications (prior'converted cropland, farmed wetland, wetland,@@ artificial wetland,
               etc.). If the need for mapping U merely to identify- wetlands in farm fields and to update
               wetland maps produced by other- means, then satellite imagery obtained when the
               wetlands are flooded may be appropriate for this use,, especially when supplemented with
               aerial photography; however,'this imagery may not be, appropriate for habitat
               classification.


               After deleting all point and linear wetland data   DU compared wetland basins delineated
               in the DU wetland classification using TM. data for basins identified on wetland maps
               prepared by the NWI on the treeless prairies. With this method, approximately 20
               percent of the wetlands smaller than-  2 acres (9 pixels) were detected; 70 percent of the
               basins between,2 and 5 acres (9-25 pixels) were detected; 91 percent of the basins
               between 5 and 10 acres (23-45 pixels) wore detected; and all basins greater than 25 acres
               (112@pixels) were detected. Manual editing of the DU wetland data has allowed a
               greater number of smaller basins to be detected. DU believes that under optimum
               conditions, blocks of forested w6tland and scrub-shrub wetlands smaller than 10 acres
               cannot be reliably detected using TM. SRSC, however, believes that deciduous forested
               wetlands as small as one acre can be identified with TM data in the Yazoo basin of the
               States of Mississippi and Arkansas. This assumes that multiple dates of imagery are
               evaluated, at least one of which is acquired during a leaf off period when flooding has
               occurred for the proper number of days during the growing season       .or when the flood
               event can be correlated to the appropriate river stage at a local stream gauging station.
               ne criteria for the appropriate river stage is the minimum stage that produces 15 days
               of consecutive flooding with 50 percent occurren   ce, i.e. on the average once in two years.
               Riparian specialists believe that the mapping width of at least 60-90 meters essentially
               precludes the utility of satellite data for mapping most riparian areas.

               Benefits in using satellite data for monitoring wetlands and upland land cover and land
               use include:

                              L.   the synoptic overview of redundant regions;
                                   data'collected in a digital format, which facilitates the use of repeat
                                   coverage to enhance results; -
                              3.   ease of integration of the data,with other digital data themes;
                              4.   repeat coverage, which facilitates monitoring seasonal or yearly
                                   changes and allows data to be tied to rainfall events or river gauge
                                   data;
                              5.   lower cost per acre than aerial photography; faster results in mapping;

                                                             4








                              6.   spectral sensing of mid-infrared bands of TM data, which provide
                                   better wetland detection than data from the multispectral scanner
                                   (MSS) or similar spectral range sensors;
                              7. , combination of the Landsat TM data with NWI data, which provided
                                   better information as to the value of the wetland habitat for waterfowl
                                   than the NWI data used alone.


               Limitations in the use of satellite data for monitoring wetlands and upland habitats are:

                              1.   reduced accuracy and detail-in identifying certain wetland habitat
                                   types when compared to aerial photography; .
                              2.   inability to classify more than a limited number of wetland classes;
                              3.   inability to reliably and,routinely detect forested wetland and scrub-
                                   shrub wetlands;
                              4.   significant problems in trying to identify vegetated wetlands with drier
                                   water regimes;
                              5.   difficulty differentiating emergent vegetation growing in dry basins
                                   from some upland vegetation types;
                              6.   underestimations of the acreage of individual wetlands; the amount of
                                   underestimation is not consistent;
                              7.   difficulty detecting wetland basins less. than 2 acres (even in treeless
                                   areas);
                              8.   very limited ability. to detect by satellite observation alone small
                                   wetland filling on the margins of wetlands ("nibbling");
                              .9.  aggregation of complexes of wetlands with dendritic drainage patterns
                                   and a variety of other wetland classes into one simple, class;
                              10.  inability to map most riparian areas because of spatial resolution;
                              11.  weather conditions preclude data acquisition on desired dates (this
                                   also applies to aerial photography but not to the same extent);
                              12.  clouds, cloud shadows, and, in areas of high relief, terrain shadows
                                   cause spectral signatures that are confused with land cover types;
                              13.  uncertainty as to whether data from Landsat 6 (to be launched in
                                   early 1993) will be collected if there is no order for the data. Such a
                                   practice will reduce the number of scenes that will be collected and
                                   available for use in multi-temporal analysis.

               These limitations apply to wetland classification schemes that are focused on mapping
               wetland habitats. They do not apply to all classification systems. For example,
               limitations 1, 2, 3, 4, 5,.9, and 10 do not apply to mapping conducted as part of the SCS
               Swampbuster Program, which is based primarily on recertification and compliance
               checking of nonvegetated farmed wetlands for the 1985 and 1990 Farm Bills.







                                                             5









               CONCLUSIONS

               Satellite data can be used to monitor water levels of some wetlands and changes in a
               number of habitat types.' and to inventory and determine changes in upland cover.
               Satellite technology cannot be used for inventories of wetlands for the purpose of
               wetland identification and classification without also using other data sources. If there
               are no other data sources available, it can be used for reconnaissance wetland surveys.
               Digital satellite data facilitates integration of multiple data sets in GIS applications.

               The current satellite technology is'most valuable when used in conjunction with digital
               data derived from aerial photography and other sources; this technology cannot be used
               to classify wetland types as defined by the FWS wetland classification system entitled
               "Classification@ of wetlands and deepwater habitats of the United States" (Cowardin and
               others 1979). Most scientists believe that to adequately delineate and classify wetlands,
               one needs 5-meter resolution (or better) color-infrared data viewed stereoscopically. In
               certain instances, satellite information is not only extremely helpful in inventorying
               wetlands, it may be the best or only tool available at any given time. A case in point is
               farmed wetlands located in the Yazoo basin of Mississippi and Arkansas. These
               wetlands have had their natural vegetation removed and hydrology altered. Therefore,
               soils and vegetation offer little in terms of identifying wetland characteristics. The only
               practical way to identify these wetlands is by documenting wetland hydrology from offsite
               information (e.g. stream gauge data, aerial photographs, satellite information, etc.).
               Because aerial photographs are not generally available in a sequence that would depict
               frequency and duration of inundation, their utility is limited in this basin. However,
               satellite data repeat coverage correlated to steam gauge data can provide information of
               frequency and duration of inundation, which can be directly tied to wetland hydrology
               criteria, thus identifying certain types of wetlands. Acquiring cloud-free data during the
               optimum time period (e.g. flooding) for delineating wetlands is at best a hit or miss
               proposition. Even if satellite collection coincides with flooding, lingering clouds often
               reduce data usefulness'.

               The following points must be considered prior to an effort to expand the satellite
               capabilities of the industry.

                      1.    The best technique for initial wetland habitat mapping and inventory is the
                            technique currently used by the FWS's NWI project, which uses aerial
                            photography..

                     2.     Digital NWI data and satellite data are. easily- merged to provide products
                            with greater Wetland evaluation and monitoring capabilities than either
                            type of data used alone. Digital data for all NWI maps @are required. The
                            subcommittee believes it makes little sense to expand the satellite
                            capabilities for wetland monitoring in the U.S. if the NWI process is not
                            accelerated and all NWI final maps are not digitized.




                                                           6









                       3.      An important obstacle in using current satellite technology for wetland
                               monitoring is the lack of cloud-free data acquired during the optimum time
                               period (when all wetlands are inundated or fully saturated to their upland
                               margin and not beyond). During years of normal precipitation, this may
                               only be for a two to three week period each year. Currently, the
                               opportunity to acquire TM data only every 16 days (8 days if you include
                               Landsat 4) is not sufficient., With adjustable viewing. angles, SPOT- has a
                               very high rate of acquisition opportunities, up to,, 11 times- every 26 @ days. -
                               Oblique views, however, will increase the difficulty of ground registration
                               particularly in areas of high relief displacement.    'SPOT also offers radar
                               imagery. Limited resolution of radar data, however, limits its effectiveness
                               for monitoring surface hydrology in wetland areas. There are various
                               means of overcoming this obstacle. One way to increase the odds of
                               obtaining, cloud-free data is. to use multiple satellites. The costs of
                               maintaining multiple satellites will be high, but in the early years of the
                               Landsat program, it was generally accepted that multiple satellites would
                               be needed if acquisition of cloud-free data for operational programs was
                               required. Another means of partially overcoming the problem of cloud
                               cover is to develop satellites that can readily modify the look angle (as
                               SPOT can) to provide more frequent coverage for areas of interest.

                               DU has worked with radar data. Many technical obstacles remain before
                               radar data can be used operationally to monitor wetland inundation and
                               saturation, but DU is encouraged that radar may provide an additional tool
                               for wetland monitoring.     Development of satellite systems with radar
                               capabilities could be one solution foracquiring      cloud-free data at the
                               optimum time for wetland monitoring.

                       4.      In efforts, to promote the expansion of . satellite systems for wetland
                               monitoring, we should de-emphasize the use of today's.satellite systems as
                               the primary source.for wetland inventories and emphasize the use of
                               satellite systems for monitoring wetlands and evaluating wet.land functions
                               in conjunction with other data sources. Wetland mappers          .must make their
                               specifications and data requirements known to the people designing
                               Landsat 7, Which is scheduled for launch in 1991. -Information and data
                               needs should be forwarded through appropriate organizational channels.

                               Current satellite data and the capabilities of satellite systems in the near
                               future cannot be used to accurately classify the wetland type nor, to
                               accurately delineate the wetland margins for all existing wetlands. Using
                               satellite data in addition to NWI digital data provides a tool for monitoring
                               water conditions of wetlands, examining impacts to wetlands, and
                               ascertaining the point-in-time value of wetlands.

                               In many countries, either the value of wetland has not been recognized or
                               funds for the type of mapping provided by the NWI are not available. DU
                               has worked very successfully in both Canada and Mexico to provide

                                                                 7









                              reconnaissance wetland maps using Landsat TM technology. ne products
                              are not as accurate or detailed as those produced in the United States by
                              the NWI, but in many cases, they represent the best and only source of
                              wetland data over these regions.


               EXAMPLES OF COMEBEqNG SATELLITE AND DIGITAL DATA
               DERIVED FROM AERIAL PHOTOGRAPHY

               The following are examples of how FWS digital NWI data could. be combined with
               satellite data to produce a product having greater value than using either data source
               alone.


                       1.     Maps have been produced for Maryland using SPOT 10-meter data as an
                              image base and using NWI vectors a's an overlay. This combination
                              provides a valuable and cost effective tool for informing and educating the
                              public on wetlands.

                       2.     Many environmental impacts to wetlands result from misuse of the
                              surrounding uplands. Satellite data can be used to analyze these impacts at
                              a lower per acre cost and results can be produced faster than with aerial
                              photogramm.etry.

                       3.     Satellite data can be used to identify regions where rapid changes in
                              wetlands are taking place. As a result, these areas may require frequent
                              updates. Updates should use aerial-photography-based NWI techniques.

                       4.     Current satellite capabilities limit the use of satellite data for updating
                              NWI maps. Some of the satellite systems being pla     -nned may have the
                              capabilities to update NWI maps. However, even with the improved
                              satellite capabilities, it is not certain whether these systems can adequately
                              implement the full FWS wetland classification system, or whether they can
                              implement a simplified version.

                       5.     Satellite technology is a tool to provide current status of water levels in
                              wetlands. Satellite data can readily be used to ascertain' the extent of
                              inundation and saturation of nonvegetated wetlands at a point in time.











                                                             8








             FACT FINDING QUESTIONS AND ANSWERS

             The following questions and answers provide specific insights into the status of mapping
             wetlands using satellite imagery.


             1.   Is any data being currently collected over the conterminous United States (U.S.)
                  for which no order has been previously placed.)

                  Answer: Yes


             EOSAT


             EOSAT's data acquisition, policy is to acquire daytime data on all passes over the
             conterminous U.S. whether or not an order has been placed for it.

             SPOT


             The SPOT satellite is constantly acquiring imagery over the U.S., including Alaska and
             Hawaii. Client acquisition requests are priority. Regardless of client acquisition
             requests, it is SPOT's goal to acquire total area coverage of the U.S. Intelligent archive
             building is used to build a historical database.with the first priority. being near-vertical
             panchromatic 10-meter and multispectral 20-meter data. The second priority is oblique
             panchromatic and multispectral. imagery for change detection and stereoscopic terrain
             modeling.


             2.   Is any TM da ta being processed today?

                  Answer: Yes


             EOSAT


             EOSAT acquires Landsat TM data every day. Customer orders are processed on an
             image generation computer -system designed to process data from Undsats 4, 5, and 6.
             This system became operational on October 1, 1991.

             The Landsat 4 and 5 archive contains 28225 TM scenes in the conterminous United
             States with less than 10 percent cloud cover for the period'July 1982 to January 1991.
             Of these scenes, 1598 were acquired of the East Cost between the months of March. and
             October, inclusive. EOSAT can provide more detailed information about specific
             regions at any time.






                                                   9











               SPO

               SPOT also acquires multispectral data everyday. SPOT imagery is being processed today
               from the SPOT 2 satellite. SPOT 1 has been reactivated to increase acquisition of
               imagery during the growing season, specifically for current clients and for archive
               building in relation to vegetation and wetland studies. The panchromatic 10-meter-
               resolution imagery is being used in forestry, oil and gas research, urban planning,
               communications, and defense applications. The multispectral 20-meter-resolution
               imagery is being used in land cover classifications and vegetative analysis. Multispectral
               imagery is being used by several Federal agencies due to high resolution, rapid- revisit
               capability (capability to acquire 11 images every 26 days), and commercial delivery
               capability.

               SPOT is devoted@ to total quality management in regards to- every step in the delivery of
               its data and service to its clients. There is a 10 line drop minimum data specification in
               its quality control process. Cloud cover rating is confirmed prior to final production of
               all deliveries. Full technical support is provided after delivery of product.


               Ducks Unlimited


               On January 9,.1992, the Landsat TM scenes listed in table 1 were being processed.
               Some of the scenes were being classified, but the majority of the scenes were being
               grouped and edited to wetland and, in. some -cases, upland classes.


                 Table 1. Landsat TM scenes being processed by Ducks Unlimited on January 9, 1992

                   Path   Row Geographic Area                                  Ducks Unlimited Office


                   22     26     Central Ontario                               Winnipeg, Manitoba
                   26     42     Laguna Madre, Mexico                          Long Grove, Illinois
                   26     43     Laguna Madre, Mexico                          Long Grove, Illinois
                   26     42     Laguna Madre, Mexico                          Monterrey, Mexico
                   29     28     North Dakota, South Dakota                    Long Grove, Illinois
                                      Minnesota
                   32     43     Pabellon, Mexico-                             Long Grove, Illinois
                   33     25     Southwest Manitoba                            Winnipeg, Manitoba
                   39.    23     West Central Saskatchewan                     Regina; Saskatchewan
                   40     23     East Central Alberta                          Edmontonj @ Alberta
                   66     14     Yukon Flats, Alaska                           Long Grove, Illinois






                                                           10









                3.     How much did the last satellite scene cost that your organization purchased and
                       how long did it take to receive it?

                       Answer:
                       EOSAT sells a fall, system-corrected scene for $ 4,400. SPOT data costs $2,450
                       per computer-compatible scene, either panchromatic or multispectral. Both
                       EOSAT and SPOT currently deliver products in less than quoted delivery time.
                       Landsat MSS data more than.2 years old is available for $200 from EDC. Special
                       acquisition fees are extra. Scenes take 4-8 weeks for delivery. Standard archived
                       scenes are delivered in less than one week.

                       See Appendixes B and C for SPOT and EOSAT fee schedules and detailed cost
                       information for a variety of formats. When comparing the price lists for SPOT
                       and EOSAT data it is important to realize that a full SPOT scene covers
                       approximately one-eighth the area of a full Landsat TM scene.

                Ducks Unlimited


                In its most recent order, DU purchased three full Landsat TM scenes of Mexico. The
                order was faxed to EOSAT on December 18, 1991. DU received the order 19 days later
                on January 6, 1992. Cost per satellite scene was $2200 (one-half the normal price). DU
                was able. to buy, the data at one-half the normal price because of a sale EOSAT offered
                1991 buyers of satellite data. The.,scenes DU purchased in 1991 will be used to examine
                wetland changes. The scene previously ordered on September 9, 1991; was received. on
                December 7, 1991, more than, 12 weeks later.

                EPA

                It took.the Environmental Protection Agency (EPA) over a year to acquire all 16 scenes
                necessary for the Chesapeake Bay watershed characterization project. The scenes varied
                over a four year time span. This was due to cloud cover problems, even though one base
                year would have been desirable. This experience showed EPA how helpful multiple
                satellites and constant acquisition would have been for obtaining fall study area coverage
                with better date,,consistency.


                4.     Is each analysis perform  ed as a unique operation, or can it be performed on a
                       routine basis on different scenes?


                       Answer:
                       Ea ch data user performs a standard set of operations on raw satellite data as a
                       first step, but each.user performs a different initial set of operations. After the
                       standard operations are complete each user has a set of additional operations or
                       procedures that may or may not be used to draw out the information required
                       from the scene.




                                                              11











              Ducks Unlimited


              DU uses a standard image processing procedure for every one     1of its scenes. For each
              scene DU has a file with 230 spectral classes. These spectral classes are grouped into
              informational classes such as wet meadow, shallow marsh, deep marsh, and open water.
              The grouping is unique for each scene and variable based on the experience of the
              digital image interpreter, time of year that the data were acquired, precipitation patterns,
              available ground truth, and many other factors. Because of spectral class confusion,
              DU's digital image interpreters use their-visual interpretation skills to assure that the
              information group assigned for the pixel agrees with their visual interpretation of the
              data. For example, shadows, whether cast onto the image from clouds, terrain, or forest,
              typically have a spectral signature identical to one of the spectral signatures assigned to
              shallow marsh. Usually the interpreter can visually distinguish a shallow marsh spectral
              class resulting from shadows and will edit these to a non-wetland class. In DU's work in
              Alaska and northern regions of Canada, black spruce may frequently be assigned a
              spectral class that has been assigned to shallow marsh, yet the interpreter can usually
              visually distinguish black spruce from shallow marsh and edit the black spruce pixels
              classified as shallow marsh to a forested class.


              SRSC


              A few preparatory operations can be applied to most satellite scenes regardless of
              location of the scene's coverage. These include such things as image-to-image
              registration, post classification georeferencing, and creating vegetation versus
              nonvegetation masks. The list of preparatory operations increases when the analysis is
              restricted to a geomorphic region with a consistent land-surface form, vegetative cover,
              or regional climate.


              5.     Which of the TM infrared bands, Number 4, 5, or 7, are most important for
                     ,wetland identification?


                     Answer:
                     Band 5 has traditionally been considered the single most important band for its
                     capability to discriminate levels of vegetation and soil moisture. However, a
                     combination of bands is needed for wetland detection.


              Ducks Unlimited

              The capability of Band 5 to detect moisture makes it the most important band for
              wetland identification. However, a combination of TM Bands 3, 4, and 5 usually is the
              best combination of bands for@wetland detection. If water quality is of interest, Band 3
              should be replaced with Band 1. It is possible that Band 1 may also help in separating
              open water from open water with submerged aquatic vegetation (SAV).




                                                          12









                Earth Satellite Coj:poratio

                Band 5 (1.55-1.75 pm) has traditionally been considered the single most important for its
                capability to discriminate levels of vegetation and soil moisture. In Earth Satellite's
                experience, Band 4 (0.76-0.90 jAm) is also important in the classification of vegetative
                communities and vegetation moisture, from which wetlands may be inferred. Earth
                Satellite's approach to land cover classification utilizes all six TM reflective bands in
                order to identify homogeneous classes. Additionally, Earth Satellite utilizes a proprietary
                program, GEOVUE, to simultaneously analyze multiple bands of data, either in a
                multispectral or multitemporal fashion, or in combination.

                SRSC


                In general Band 5 is the most important for wetland identification due to its sensitivity to
                soil and vegetation moisture. But this is not always the case; it depends on what type of
                wetland is being classified. For example, Band 5 was most important for identifying
                standing water and saturated soils associated with farmed wetlands in the Mississippi
                Delta. Band 4 was most important in identifying patches of healthy natural vegetation
                located within recently plowed agricultural fields in the Prairie Pothole region of North
                Dakota. The patches of vegetation are surrogate indicators of temporary wetlands where
                the potholes were filled with water when the farmer began plowing the field. Because
                these potholes were filled with water, the farmer simply plowed around the potholes. At
                the time the satellite scene was acquired the open water in the pothole had evaporated
                and the natural vegetation now growing in the pothole contrasted both spectrally and
                spatially with the surrounding bare soil.

                NCG

                NCG has found that TM Bands 5 and 7 to be extremely useful in differentiating
                vegetation.


                6.     How many wetland classes have you bee n* able to successfully discern using
                       satellite data? Can you provide a listing of these classes?

                       Wetland classes used in waterfowl habitat and wetland inventory.
                       (See Appendix A for categories identified by DU and SRSQ


                7.     Which wetland classes are the easiest to discern, and which classes are the
                       hardest? Please provide some statistical insight as to relative accuracies.

                       Answer:
                       Although quantitative statistical data are not available, the consensus is that the
                       easiest classes to discern are permanently flooded or intermittently exposed open
                       water ponds (pahistrine unconsolidated bottoms). Tle difficulty increases, moving
                       through the wettest to driest marshes, deciduous forested wetlands, evergreen

                                                           13









                    forested wetlands, and any type of scrub-shrub wetlands. Mangroves are an
                    exception; due to their unique spectral reflectance, they are the easiest vegetated
                    wetland type to identify. For coastal wetlands the ease and ability depends on
                    tide conditions. With appropriate tide conditions, mangroves are the easiest class
                    to discern, then moving to salt marshes to forested wetlands with scrub-shrubs
                    (other than mangroves) being the hardest class to discern.

             Ducks Unlimited


             DU's work in the Prairie Pothole region found that shallow marsh, deep marsh, and
             open water classes are the easiest to discern without any editing. The open water classes
             are always easy to discern; spectral class confusion has never been a problem with these
             classes. In general, the deep marsh class is as easy to discern as the open water class;
             seldom has spectral class confusion been a problem with the deep marsh class. Wetter
             shallow marsh classes are nearly as easy to discern as the deep marsh classes.

             Dry shallow marsh classes frequently have a great deal of spectral class confusion. For
             these spectral classes, which typically describe the temporary basins or the margins of
             seasonal or semipermanent wetlands, spectral class confusion is often a problem.
             Spectral classes which discern temporary wetlands and wetland margins of seasonal and
             semipermanent wetlands often will cause commission errors, identifying moist areas in
             fields as wetlands. DU removes these commission errors using its image editing
             procedures.

             For example, E10W (estuarine subtidal open water), LlOW (lacustrine limnetic open
             water), and POW (palustrine open water) are spectrally identical and must be edited to
             these classes based upon location and size of wetland. In a similar manner, emergent
             vegetation of estuarine, lacustrine, and palustrine systems are spectrally identical and
             must be separated by an editing or post-processing step.


             8.     Can you provide the committee with quantitative or qualitative information on
                    wetland identification which is accurately related to wetland size, water regimes,
                    and wetland coverage classes and types?

                    a.     Wetland size


                    Answer:
                    ne accuracy of satellite data for identifying wetlands is heavily dependent on
                    collecting satellite data when the wetlands are inundated. A multiacre temporary
                    basin that is dry and cultivated when the satellite data are collected usually cannot
                    be identified using satellite data. However, stock ponds (or dugouts) in Montana
                    range land are readily identified using Landsat TM data even though these ponds
                    represent very small areas (10 ft by 20 ft) of open water.




                                                          14










               Ducks Unlimited


               Using Landsat TM data collected in late May 1986, and employing DU's 1987 image
               processing procedures, which did not include an interactive editing step, only 22 percent
               of the wetland basins (identified from NWI data) less than 2 acres in size were classified
               as wetlands as shown below:


                              Wetland basin                      Percent classified by
                              size (acres)                       thematic mapper data
                                 0-1.9                                    22
                                 2-4.9                                    70
                                 5-9.9                                    91
                                 10-24.9                                  96
                                 > 25                                      100


               The drought of the 1980's severely impacted the available habitat for waterfowl. By the
               end of May 1986 most of the temporary basins were dry and many of the seasonal and
               some of the semipermanent basins were dry. Also during the 1980's, many temporary
               and seasonal basins were cultivated, making wetland detection very difficult, even using
               conventional aerial photography techniques.


                      b.      Water regimes

                              Answer:
                              In the Prairie Pothole region, satellite data collected in late April or very
                              early May in years of normal precipitation are ideal for delineating
                              wetlands. However, it is difficult to ascertain from spectral information if a
                              wetland has a temporary, seasonal, semipermanent, or permanent water
                              regime. Satellite data collected late in the year provides information on
                              water regimes, but can make wetland detection very difficult.


                       C.     Wetland coverage classes and types (i.e. forested, scrub-shrub, emergent,
                              etc.)

                              Answer:
                              DU's biologists, using their habitat inventory products derived from
                              satellite data, have been pleased with the separation of shallow marsh,
                              deep marsh, and open water when using data collected from mid-May to
                              June. When using late April or early May data, deep marsh typically has a
                              spectral signature that is difficult to separate from open water. DU
                              frequently debates the trade-off between using late April or early May data
                              to improve detection of temporary and seasonal wetlands or mid-May to
                              June data to improve separation of wetland types.



                                                              15











               SRSC


               An important factor in the size question is how much spectral contrast there is between
               pixels of certain wetland classes and surrounding pixels of other land cover classes. In
               the Prairie Pothole region of North Dakota SRSC had success in classifying open water,
               deep marsh and shallow marsh as small as one-half acre in size using SPOT multispectral
               data. It should be pointed out that SRSC believes wetlands were detected at this size
               because of optimum conditions: open water was generally surrounded by the bare soil of
               an agricultural field or much drier prairie grass vegetation which bad a significantly
               different spectral reflectance. The same could be said for the deep marsh and shallow
               marsh. Since SRSC has only conducted one wetlands study in the Prairie Pothole region,
               they can not state with certainty that satellite remote sensing is capable of repetitively
               identifying wetlands at this size. But they are encouraged by these early results and
               intend to do further wetlands research in this region. The SRSC mapping procedures
               have not been documented in detail or published in the technical literature where they
               would be subjected to peer review of the process and map products. Quantitative testing
               against NWI digital wetland data will be performed -on other maps in the Prairie Pothole
               region.


               9.     What do you believe is a reliable minimum mapping unit for forested wetlands,
                      scrub-shrub wetlands, open water ponds?

                      Answer: No definite answers were provided.

               NOAA-C-CAP

               Jerry Dobson, of Oak Ridge National Laboratory, reported that on the Salisbury,
               Maryland 1:100,000 scale USGS quad, his initial analysis only identified 30 percent of the
               forested wetlands. This accuracy was doubled to 60 percent after some. initial field work
               using a fall satellite scene. Accuracy was further improved to 67 percent through
               additional field work and the use of a spring scene.

               EPA

               Ross Lunetta, of EPA, has used a wetland/upland mask developed through the use of
               satellite information gathered during the leaf-off wet season of a normal year to help
               identify deciduous forested wetlands in subsequent data gatherings. He has not tried this
               technique on evergreen forested wetlands. The wet season scene is selected using
               rainfall data and/or river stage data.

               SRSC

               SRSC has successfully classified hardwood forested wetlands in the Yazoo basin as small
               as one acre using TM data. This assumes the use of multiple dates of imagery and
               acquiring scenes when the hardwoods were inundated with flood water. This does not


                                                            16








               imply that they can map all forested wetlands down to one acre. Quantitative testing
               against other wetland mapping efforts have yet to be performed.

               Ducks Unlimited

               DU has had only minimum experience in delineating scrub-shrub and forested wetlands.
               From their limited experience, they believe that these features may be two of the most
               difficult habitat types to accurately delineate using satellite data. These habitats are best
               identified in leaf-off periods when the soil is fully inundated or saturated. Even under
               these optimum conditions, blocks of forested and scrub-shrub wetlands smaller than 10
               acres cannot be reliably detected.

               Earth Satellite Corporatio

               Earth Satellite Corporation believes that a minimum mapping unit of 5 to 10 acres is
               possible for detection of forested and shrub-scrub wetlands by digital methods using
               satellite imagery. Thissize may be reduced by using additional data sources, GIS data,
               and/or other visual (monoscopic and/or stereoscopic) data; the presence of spectrally
               unique wetland forest species in an area, e.g., mangrove, would also help reduce this size.

               Emergent wetlands and deep water habitats are detectable to as little as 3-5 acres,
               depending upon water regime at the time of imagery. Smaller than 3 acres, with current
               spatial resolutions, the accuracy of classification decreases rapidly.


               10.    What are the problems associated with identifying narrow bands of wetlands such
                      as those found along tidal creeks or riparian wetlands, which are found along
                      streams and are often very important?

                      Answer:
                      The drier the adjacent upland the easier it is to identify riparian wetlands. In
                      general the riparian strips need to be at least 60-90 meters wide to be identified.
                      Most riparian specialists believe that a minimum mapping width of 60-90 meter
                      essentially precludes the use of satellite data for mapping many riparian areas.

               Ducks Unlimited


               DU's work in Alaska found that most narrow drainages. have varying widths of sedge,
               small willows scattered amongst the sedges, or sedges primarily dominated by small
              .willows or small coniferous shrubs. If the linear feature is narrow (90 m wide or less),. it
               can be very difficult to properly classify. Also, many of the drainages have small slow-
               flowing creeks that are often not delineated by NWI. Drainage without such creeks offer
               little value for waterfowl except as nestirig habitat. However, drainage with slow-flowing
               creeks have value for waterfowl. Even though these creeks are often not displayed by
               NWI on their 1:63,360 scale maps, DU's Landsat TM data have enabled the display of
               these narrow ribbons of water.



                                                           17








                 One additional problem with delineating narrow linear features using satellite data is the
                 mixed pixel problem. A narrow band of water in a creek surrounded by upland grasses
                 may be erroneously classified as a shallow marsh. In this situation, water may cover one-
                 third of a pixel while upland grasses cover the remaining two-thirds of the pixel. The
                 spectral response for this pixel will be a mixture of water and vegetation, which is
                 identical to the spectral response of shallow marsh.

                 SPOT


                 Mapping of a 60-meter wide swath would be possible with SPOT multispectral (3 pixels
                 wide) or with merged panchromatic and multispectral. (6 pixels wide), provided these
                 wetlands are not obstructed by upland overstory. If overstory is present and is composed
                 of deciduous trees, imagery can be acquired during the spring wet season, before leaf-out
                 occurs.


                 SRSC


                 Using ancillary data such as digital line graph (DLG) hydrography data and digital
                 elevation models (DEM's), a mask can be developed that identifies areas that are a
                 predetermined elevation above the nearest water source. Using this mask the feature
                 space over which spectral analyses are performed can be reduced. A classification can
                 be done on the reduced area, which facilitates delineation of narrow bands of wetlands.
                 Applying this technique along with other techniques should permit the identification of
                 riparian areas less than 90 meters wide using satellite imagery in certain geomorphic
                 regions.


                 11.    Due to the scale of coverage, it has been reported that satellite data consistently
                        underestimate the acreage of individual wetland basins. If this is true, can a
                        conversion factor be determined? Is the underestimation a function of the size of
                        the wetland basin or the scale at which the satellite senses?


                        Answer:
                        Satellite data consistently underestimate the acreage of individual wetland basins.
                        There is ongoing debate as to whether an expansion factor or factors, can be
                        developed to convert these underestimates.

                 Ducks Unlimited

                 Satellite data consistently underestimate the acreage of individual wetland basins because
                 the drier margins of these wetland basins are inaccurately classified as upland habitat. In
                 classification of satellite data the analyst is constantly making trade-offs between
                 omission and commission errors. Commission errors (i.e., identifying a wet area in an
                 upland field as a wetland class) are increased as omission errors (i.e., identifying the dry
                 margin of a wetland as an upland class) are decreased. Typically when grouping spectral
                 data for wetlands,-those spectral classes representing dry wetland margins are not


                                                               18








                  assigned as a wetland class. If they were, considerable commission error would occur
                  and nonwetlands (moist areas in fields) would be assigned as wetlands.

                  Labor intensive techniques can be used  ' such as DU's image editing procedures to help
                  reduce this problem. In addition, all spectral classes that represent not only wetland
                  margins, but also nonwetland areas, can be identified and wetlands can be allowed to
                  11grow" into these margins.

                  A conversion factor developed for a Prairie Pothole scene would likely be   meaningless in
                  other geographic regions. Conversion factors could possibly be developed for other
                  wetland types in different regions but would be scene-specific due to water conditions at
                  the time of data capture.

                  Correction factors could possibly be used to correlate the actual acreage of wetlands
                  mapped using aerial photography to satellite-derived wetlands acreage. For a
                  representative sample of wetland basins in the study area, various dependent variables
                  from the satellite data are needed such as area of basin, length of basin perimeter, shape
                  index, and square and cubic transformations of these variables. Using the actual
                  acreage of the wetland basins as the independent variable and using regression analysis
                  techniques, it is possible to ascertain an appropriate regression model to correct the
                  acreage of wetland basins as derived from satellite data.

                  NCG

                  NCG believes there are scientifically valid sampling and estimation procedures whereby
                  adjustments can be made to figures generated by 100 percent mapping, but it is not
                  likely that several simple adjustment factors will provide desired reliability.

                  EPA

                  Although a conversion factor may aid applications that require only acreage totals over
                  broad areas, it is unlikely that a conversion factor could improve mapping of individual
                  wetland boundaries.



                  12.    Have you had any success in identification of SAV and/or grass flats?

                         Answer:
                         No. The satellite can "see" some percentage of the SAV, but no verification
                         studies have been performed. The USGS estimates that using TM data, they have
                         been able to identify approximately 70 percent of the submerged aquatic beds in
                         the tidal Potomac River that can be detected using 1:24,000 scale photographs.
                         Best results are gained when both the satellite imagery and aerial photography are
                         captured at low tide. As with aerial photography, the ability of satellite imagery
                         to identify SAV is heavily influenced by wind conditions, depth, and turbidity.
                         Even small ripples on the water can prevent identification of SAV. Turbidity in
                         the water conceals much such vegetation.

                                                              19










              Ducks Unlimited


              In some DU study areas in Alaska, spectral classes were identified that had a degree of
              correlation with areas identified as aquatic beds on the available NWI maps. Also, one
              of the scenes DU used in Mexico provided data for parts of southern Texas that NWI
              maps cover; some spectral classes appeared to correlate with L2AB (lacustrine littoral
              aquatic bed) on the NWI map. DU researchers do not believe that satellite data actually
              detects the SAV. They believe they are detecting shallow water that could be providing
              adequate conditions @water depth and light penetration) for the growth of SAV.

              Maryland Department of Natural Resources

              The Maryland Department of Natural Resources (MD-DNR) delineated and classified
              SAV using SPOT satellite multispectral. digital data (acquisition date of SPOT data,
              September 27, 1987). The results of the effort are published in a report entitled
              "Delineation and classification of submerged aquatic vegetation (SAV) using SPOT
              satellite multispectral digital data." The following is from a report that was written by
              Dr. K. Peter Lade of Salisbury State University under contract to MD-DNR:

                     "Aerial photography has been, to date, the principal data source other than field
                     verification. There is little question that good quality aerial photography, taken
                     under the right circumstances, at the right scale, and supplemented by good field
                     testing, can better serve the purpose of documenting the distribution of SAV than
                     any other data collection method.

                     Satellite data are, perhaps, the next most obvious data source. Synoptic in its
                     coverage, digital in format, satellite data have the potential of not only automating
                     much of the tedious process of matching "photography" to standard orthographic
                     projections, but has the further advantage of being comparatively inexpensive.
                     The disadvantage is mostly one of resolution.

                     SAV bedsWere identified on the SPOT satellite data of September 27, 1987, by
                     displaying segments of the satellite tract on screen for computer aided analysis.
                     In each case, it was assumed that a bed density of less than 25 percent would
                     probably not be visible at the 20 meter resolution of the multispectral satellite
                     data. A screen cursor was used to point at SAV colonies and the computer was
                     permitted to suggest additional locations of submerged aquatic vegetation within
                     the experimental frame.

                     The effect of this method was to reduce the total estimate of SAV in two ways.
                     First there is the -loss of statistics for those beds with low density. Since there is
                     no reliable method for estimating the total contribution of low density beds as a
                     fraction of total acreage for higher density beds, there will inevitably be an error
                     that may account for as much as 10 percent of the potential acreage of SAV in
                     the Chesapeake Bay and tributaries. Second, area calculations were not based on
                     polygons circumscribing an area of identified SAV, but rather on the point
                     distribution of targeted SAV coverage. This resulted in a more nearly accurate

                                                            20








                      mapping of aerial "tent of SAV, as opposed to the representational mapping of
                      previous studies where polygons were circumscribed around observed SAV beds.
                      In this case, the lower acreage figures to be expected through feature mapping of
                      the satellite data would, in fact, be a better estimate of the actual distribution of
                      SAV than the photo-mapping of previous years."

               SPOT


               The National Park Service has used SPOT multispectral imagery to locate and track the
               movement of large blooms of SAV, specifically hydrilla, which are causing navigational
               problems on the Potomac River. SPOT was able to acquire imagery at very specific
               times, which coincided with low tides and maximum SAV exposure.

               SPOT multispectral imagery was used as a rapid and accurate means of making long-
               term measurements of biomass for monitoring purposes. The imagery allowed for the
               detection of small changes in vegetation and environmental characteristics. The ability
               to acquire the imagery at specific times was critical to the study. Spartina alterniflor
               within the Great Marsh near Lewes, Delaware, was studied to correlate changes in
               wetlands biomass distribution with precipitation. Three SPOT scenes, approximately one
               year apart, were digitally compared. A supervised classification was performed to
               identify those wetland areas dominated by Spartina alterniflora. A vegetation index,
               based on the relative reflectance values of the Spartina, was then developed and used to
               automatically map Spartin according to relative density, and thus biomass. This proved
               to be a highly accurate, nondestructive, and rapid means of assessing and monitoring
               biomass distribution.



               13.    Can the 10-meter panchromatic data from SPOT help compensate for the lack of
                      Band 5 (1.55 to 1.75 gm) midinfrared radiance?

                      Answer:
                      The 10-meter panchromatic data from SPOT cannot identify wetlands as well as
                      the 30-meter TM data with Band 5. But this is not a fair question because 10-
                      meter panchromatic SPOT data are not a replacement for Landsat Band 5 data.
                      Neither is Landsat Band 5 data a replacement for 10-meter SPOT data. Both
                      make valuable and unique contributions in extracting information about ground
                      cover. They do not replace each other, but are viewed by most users as
                      complementing each other.

                      TM's midinfrared bands. (especially Band 5) have unique capabilities for detecting
                      wetlands. Wetlands that are completely vegetated and not inundated, and dry
                      mud Rats are very difficult to classify as wetlands using panchromatic data alone.
                      A combination of visual and near-infrared data, or panchromatic data in
                      combination with visual and near-infrared data are needed. Mapping of a swath
                      at least 60-meters wide would be possible with SPOT multispectral (3 pixels wide)
                      or with merged panchromatic and multispectral (6 pixels wide), provided these
                      wetlands are not obstructed by upland overstory. H overstory is present and is

                                                             21








                      composed of deciduous trees, imagery can be acquired during the spring wet
                      season, before leaf-out occurs. If mid-infrared data were available at 10-meter
                      resolution, SPOT would have a very powerful tool for wetland detection.

               Ducks Unlimited


               DU has successfully combined 10-meter panchromatic data from SPOT with TM data
               (including Band 5). They believe that spectral classifications using combined data
               provided little improvement over using TM data alone. The visual enhancement of data
               allowed DU's digital image interpreters to slightly improve their editing decision. For
               this technique, DU used TM Bands 3, 4, and 5, and a hue, saturation, and intensity
               transformation. The result of this transformation was a three band file. One band
               depicted values for hue, the second band depicted values for saturation, and the third
               band depicted values for intensity. The intensity band was replaced by the values from
               the panchromatic band. Using a reverse transformation, the hue, saturation and intensity
               files were transformed to a 3-band file representing red, green, and blue. This 3-band
               file was used for the classification procedure.

               SRSC


               SRSC has developed a proprietary method of merging SPOT panchromatic data with
               SPOT multispectral data. Unlike some of the traditional merging techniques (i.e.
               intensity hue saturation transformation) SRSC's method of data integration does not
               significantly change the original digital number (DN) values of the SPOT multispectral
               data. This method reportedly gives their analysis the best of both worlds by producing a
               data product that has the improved spatial resolution of the panchromatic data and
               retaining the spectral resolution of the SPOT multispectral data. SRSC is in the process
               of classifying wetlands in the Prairie Pothole region of North Dakota. Early results have
               indicated that the merged product has identified open water ponds, deep marshes, and
               shallow marshes as small as between one-quarter and one-half acre. Many of these
               small wetlands were not classified when analyzing SPOT multispectral data (20-meter
               resolution) over these same areas. SRSC believes that for this unique geomorphic
               region, the SPOT panchromatic data merged with the SPOT multispectral data using
               SRSC method may compensate for the lack of a middle infrared band because of its
               improved spatial resolution. SRSC plans to conduct more research with the merged data
               in this region and will determine if classification of potholes is improved significantly
               over classification with SPOT multispectral data. Quantitative testing against NWI
               digital wetland data will be performed.


               14.    Have you had any success in using stereo data from SPOT to increase your
                      accuracy in wetland identification, classification, and delineation?

                      Answer: No experience at all.
                      Theoretically, if stereo air photos were not available for a desired time period and
                      suitable SPOT stereo pairs were available, they could be used in film or print


                                                          22









                        form, or in digital form in a digital stereoplotter workstation to provide stereo
                        data.



                 15.    Can a satellite be reprogrammed in flight so as to capture data for different
                        purposes?

                        Answer:
                        The SPOT satellite viewing angles can be reprogrammed to acquire imagery. The
                        viewing angles can be adjusted as much as 27' on either side of nadir (54' angle
                        of adjustment) to acquire imagery anywhere within a 1000 krn swath.

                 SPOT


                 The uniqueness and strength of the SPOT satellite system is based partially on the
                 capability to program the satellite upon request. A conterminous U.S. acquisition
                 request must be received one week prior to the start date. A programming request must
                 be received three weeks prior to the start date for Alaska and Hawaii.

                 Specific project requests can be accommodated with only one day notice to program the
                 satellite (e.g. to monitor flood waters and capture a scene at highest flood level to
                 update the one-hundred-year flood plain).

                 The SPOT satellite has two high-resolution visible sensors (HRV's) enabling
                 programming of a twin pass. A twin pass can provide coverage of 117 kilometers (two
                 scenes overlap). The HRV's can be programmed to acquire a scene within a + 27*
                 swath. The ability to program the satellite enables SPOT to capture a particular point
                 on the earth three times a week.


                 EOSAT


                 Landsats 4 and 5 have fixed data strearns; the 85-megabit-per-second seven-band TM
                 data and the 15-megabit-per-second four-band multispectral. scanner data. EOSAT
                 believes there is no ability to reprogram for different purposes.

                 EOSAT transmits two days of commands to each satellite every day. The commands for
                 the second day are made as insurance against loss of transmission capability. EOSAT
                 experiences extremely few such losses. The command loads include the start and stop
                 transmission times for transmitting all seven bands to all ground stations.

                 Inclination adjustments necessary to maintain the satellite over the Landsat world
                 reference system paths need to be performed less than once per year. Orbit adjustments
                 for altitude correction are performed during satellite nighttime orbit without interrupting
                 service to the ground stations. EOSAT does not acquire data during periods of orbit
                 adjustment or when they are outgassing the cold focal plane (about once every four
                 months).


                                                             23









             16.    Is georeferencing now sophisticated enough to allow for a pixel by pixel analysis in
                    order to perform change detection?

                    Answer:
                    Yes, but with some qualifications. Relative positional accuracy of a geocoded
                    satellite image is a function of spatial resolution (pixel size), the quality and
                    accuracy of the paper maps used for ground control points, the global positioning
                    system (GPS) setup if used (differential GPS is the most accurate), the skill of the
                    image analyst, and the quality and appropriateness of the computer algorithms
                    used to process the data. It is easier to get high accuracy for flatter, well surveyed
                    areas, although a properly orthocorrected image can be highly accurate. In
                    general, root mean square (RMS) errors can be as low as 0.5-1 pixel (5-10 meters
                    for SPOT panchromatic, 10-20 meters for multispectral) for most U.S. areas.
                    When SPOT reports error(s) on a product, it usually is referring to the
                    specification, which indicates the greatest error allowable. In the case of
                    SPOTView 7.5-minute quadrangles, which are panchromatic data orthocorrected
                    using 7.5-minute quadrangles digital elevation models, the error specification is 15
                    meters, or 1.5 pixels.

             EOSAT


             EOSAT provides map-oriented precision-corrected imagery which is accurate to within
             .:L 15 meters (one standard deviation) with respect to a map, exclusive to terrain effects.
             Within a scene, the pixel-to-pixel distances are accurate to less than one meter, also
             exclusive of terrain effects. Many users perform change detection using two such scenes.

             If elevation effects are important, EOSAT can provide map-oriented terrain-corrected
             data, which is corrected using control points from maps and digital elevation maps. The
             algorithms used in correcting Landsat data are designed to the specification of plus-or-
             minus one-third pixel for scene-to-scene registration. These specifications are for the
             entire scene; they are not random errors at each pixel within a scene.

             Ducks Unlimited


             DU typically registers full scenes of TM data to the Universal Transverse Mercator
             (UTM) grid system using 20 to 30 control points and a linear transformation. For
             regions where accurate UTM coordinates for the control points are available from
             published maps or using a GPS, DU can obtain RMS errors of less than 30 meters.
             (Obtaining UTM coordinates for control points in Mexico using the 1:50,000-scale map
             sheets results in a RMS error of 40 to 45 meters.) For example, using these techniques
             in the U.S. and Canada, DU would register   -two different scenes to the UTM grid system,
             and the overlay of these two images would not be a perfect fit.

             Pixel-to-pixel registration is not required to identify wetland change. Registration of
             pixel-to-pixel or its near neighbor is readily achieved in the simple georeference
             procedures used by DU. In its wetland change detection procedures, by using connective


                                                        24









                components techniques, DU identifies all pixels from either scene that are connected to
                the wetland basin. For example, a small temporary basin may have 4 pixels of shallow
                marsh in one scene and four pixels of shallow marsh in the other scene, but because of
                project rating error, only two of these pixels are identified as shallow marsh in both
                scenes (see figure 1).



                                                  X10 0                      1
                                                  X 0.0

                                                      T_             I



                Figure 1. An example of project rating error, where a small area is not registered
                perfectly in all imagery. (Each box represents one pixel; X, small area in one scene;
                0, same small area in comparison scene.)


                Another procedure is similar to the procedure DU is using, but replaces the linear
                transformation with a high-order polynomial transformation. The number of control
                points required is dependent upon the order of the polynomial transformation used. DU
                is not using the polynomial transformation but believes that when 100 or more of its
                control points are collected and a third or fourth order polynomial is used, pixel-to-pixel
                registration can be obtained.

                Using connective components techniques, the basin in figure 1 would be identified as a
                six-pixel basin. In the Ent year, four pixels are wet and two pixels are dry. In the
                comparison year, the same four pixels are wet and two are dry. Consequently, no change
                has occurred in the wetland. Even if small change is reported because of registration
                errors or classification errors, only those basins exceeding a threshold of change would
                be classified as changed basins.

                Earth Satellite Co=ratio

                For imagery acquired over the U.S., using the most recent USGS 1:24,000-scale
                topographic quadrangles, image georeferencing RMS errors can be often less than one-
                half pixel (5 to 15-meters, depending upon image source). Earth Satellite Corporation
                routinely georeferences imagery to subpixel accuracies. Earth Satellite's standard
                procedure in change detection activities is to georeference the first image to the best
                available map source, then to register the second image to the first via image-to-i
                                 LI I                                       H





                                                            25









            correction. This minimizes displacement to as little as one-half pixel between the image
            dates. Theoretically, a pixel-by-pixel analysis could be conducted; in reality, one would
            expect to encounter edge differences of up to one-half pixel on unchanged parcels
            between image dates.

            To avoid numerical problems with the polynomial approach and remove the dorhiinant
            error source, ephemeris error, along with smaller errors such as clock error, attitude bias,
            and spacecraft-instrument misalignment bias, the Earth Satellite Corporation uses the
            following procedure:

                   0      Perform a systematic geometric correction on a single band (usually
                          Band 4).

                   0      Use USGS (or customer-supplied, non-U.S.) maps to identify control points
                          within the scene.

                   0      Given the error in location of the control points from their correct
                          position, determine the errors in the ephemeris of the spacecraft.

                   0      Correct the ephemeris error and regenerate the geometric correction
                          model coefficients.


            SRSC


            As the first step in the georeferencing process, SRSC generally performs image-to-image
            registration. One image is chosen as the base and the remaining images are registered
            to that base. This is different from georeferencing each scene to a base map, where a
            half-pixel error in one scene and a half-pixel error in another scene could potentially
            result in a composite error of one pixel, which can be significant when doing change
            detection. By performing image-to-image registration, any error that occurs during the
            georeferencing process is consistent for all the images since they all now overlay each
            other and the same georeferencing equation is used for all scenes.

            Secondly, SRSC georeferences data using a nearest neighbor resampling routine after the
            raw data has been classified. Georeferencing after the classification ensures that pixel
            values have not been altered to such a degree that small areas and borders cannot be
            correctly classified. But even when using a nearest neighbor resampling routine, SRSC's
            analysts check the georeferenced classified image against the nongeoreferenced classified
            image to check for potential alterations produced by the georeference transformation.

            NCQ

            NCG has rectified SPOT and TM data to an RMS error of 0.7 pixels or less using three
            or four ground control points per quad, classified respective scenes, performed change
            detection on as many as four scenes over the same area, and experienced no known
            registration related problems. Film-based orthophotoquads are preferred for picking
            ground control points. Ground registration is the most time consuming step in

                                                       26








             processing satellite data because of the amount of time required to select ground control
             points.


             17.    How do you navigate on the ground to locate and identify 1 to 6 or more pixels
                    depicting change?

                    Answer:
                    Identifying the precise location of one to six pixels on the ground can be very
                    difficult. Pixels adjacent to readily identifiable fixed features (such as the
                    intersection of section lines) can be readily identified. However, trying to use the
                    shape of a wetland on the ground to identify a particular pixel is difficult and can
                    lead to errors. The wet border of wetland can rapidly change from week to week
                    and certainly changes seasonally and annually. Such borders are not usable to
                    identify a particular pixel on the ground.

             Ducks Unlimited


             Use of the GPS offers a potential for pixel identification on the ground. One of DU's
             employees using the GPS in Alaska felt that he could indeed identify the location of
             individual pixels. Other employees used a GPS in Mexico and felt that they could not
             rely on the GPS to identify the location of individual pixels. In Mexico, DU employees
             identified various road intersections and obtained the UTM coordinates for the road
             intersections using the GPS. They also obtained the UTM coordinates for the same road
             intersections from various published map sheets at a scale of 1:50,000. Differences
             between the UTM coordinates obtained from a Mexican map and from the GPS ranged
             from 26 meters to over 1200 meters. Using the GPS in Alaska, it only took a few
             minutes to obtain the UTM coordinates. In Mexico, employees frequently waited 15
             minutes or longer before data from three GPS satellites were obtained. The longest wait
             before obtaining data from three GPS satellites occurred early in the mornings and late
             in the afternoons. The signals from the GPS satellites may have been degraded by the
             U.S. Department of Defense when DU was in Mexico. By using two GPS receivers, one
             located on a benchmark, it should be possible to determine the location of pixels on the
             ground.

             Earth Satellite Colporation

             Earth Satellite Corporation has successfully identified change polygons using
             georeferenced imagery. Pixel column and row locations of a wetland polygon centroid
             are translated into their UTM or latitude and longitude coordinates. Using GPS
             receivers and maps and imagery for corollary reference, it is then possible to locate the
             pixels on the ground within the accuracy of the GPS receiver. In the case of curvilinear
             or oddly shaped wetlands, where the centroid falls outside the polygon, a GIS editing
             step would be used to move the coordinate inside the polygon. This GIS edit step could
             also select any particular points or clusters that are of specific interest to the analyst
             from visual examination.



                                                      27









              18.    How is NWI digital data processed so that they can be interfaced with TM digital
                     data used by DU, and is this process done on a unique basis or a routine basis?

                     Answer:
                     DU has interfaced NWI digital data with satellite data in two ways. For primarily
                     visual comparisons, DU overlays the NWI vector data directly onto its raster data.
                     These types of overlays of vector data onto raster data are less than ideal when
                     using a monitor on which one raster cell is presented as one pixel on the monitor.
                     Using these techniques, the NWI vectors totally obscure the raster data of small
                     wetlands. Using a plotter, however, each raster cell of the satellite data can be
                     represented by a 2 by 2, 3 by 3, 4 by 4, or greater block of plotter pixels. The
                     NWI vector lines only require a single plotter pixel. Therefore, fewer of the cells
                     from the raster satellite data will be obscured by the NWI vectors.

                     For analytical work, DU converts NWI data to raster format at the same
                     resolution as its raster satellite data. Using NWI data as fact, DU determines the
                     maximum extent of each wetland basin. For each wetland basin, DU measures
                     the acreage of various NWI wetland types and the acreage of wetland types
                     derived from satellite data. These data are maintained in a wetland basin data
                     base. By using both the NWI data and the satellite-derived wetland information,
                     DU can better evaluate the wetland as waterfowl habitat. As an example, two
                     hypothetical basins of the same size might be reported by NWI as 100 percent
                     PEMC (palustrine, emergent, seasonally flooded). For basin A, DU's satellite
                     data recorded 60 percent of the basin as shallow marsh and 40 percent of the
                     basin as deep marsh. For basin B, DU's satellite data reported 60 percent of the
                     basin as shallow marsh and 40 percent as nonwetland. Basin A, at the time that
                     the satellite data were collected, was providing better waterfowl habitat than basin
                     B.

                     SPOT's smaller pixel size for 20-meter multispectral data would help to alleviate
                     the problem that DU reported when overlaying vector data over raster data. A
                     one-pixel wetland area interpreted from Landsat TM 30-meter data would most
                     likely occupy from two to four pixels with SPOT 20-meter data. A rasterized
                     polygon boundary (from vector data) of one-pixel SPOT 20-meter data would no
                     longer obscure an entire one-pixel TM 30-meter wetland.

                     A merged and properly georeferenced data set incorporating SPOT panchromatic
                     (10-meter) with Landsat TM (30-meter) data would allow for easier and more
                     accurate registration of satellite data with the NWI vector data base, due to the
                     enhanced geometric fidelity of the satellite data.

              Mar3LIand Department of Natural Resources

              In April 1989, the State of Maryland enacted the Nontidal Wetlands Protection Act.
              This law established a program to prevent net losses of nontidal wetlands. One of the
              program's first requirements was creation of new maps showing nontidal wetlands and
              relating them to identifiable ground features. The maps also needed to show areas that

                                                         28









              were designated as Wetlands of Special State Concern that contain rare, threatened, or
              endangered species, or that have unique habitat value. In December 1989, the MD-
              DNR completed a project using SPOT panchromatic imagery as a georeferenced base
              and overlaid it with NWI digital wetlands data.

              It was not possible to create a series of orthophoto base maps for the State in this period
              of time. It would have been inappropriate to use uncorrected aerial photography. SPOT
              10-meter panchromatic data provided imagery in time to meet project deadlines and at a
              lower cost than aerial photography. SPOT imagery can be printed at 1:24,000 scale and
              provides ground resolutions that allow the average person to orient themselves on the
              ground and identify features with which they are familiar.

              The full scenes provided by SPOT were reformatted to match the USGS 7.5-minute
              topographic quadrangle series for Maryland. This process involved extraction of the
              individual quad images, rotation to true north, and registration to existing map vector
              data sets. Where the overlap between scenes was not great enough to allow extraction
              of a full 7.5-minute quad from one scene, portions of two or three scenes were extracted
              and merged to create one 7.5-minute base map. The NWI data files, as well as files of
              the transportation network, hydrology, and place names were procured in 7.5-minute
              quadrangle format. These data layers were plotted into the image. raster and then
              converted to a print file that could be used for on-demand printing of paper maps using,
              an electrostatic printer.

              This work was, a one-time effort that provided the basis for a tum-key GIS that is
              currently in use for project review and planning purposes.


              19.    Do you agree with the following statement made by Dr. Gregory T. Koeln,
                     Director of DU's Habitat Inventory Program?

                     "Satellite data are best used as a monitoring tool for wetlands and are a poor tool
                     for establishing baseline data on wetlands. Combining NWI digital data with
                     satellite data provides much greater information than either product used alone."

                     Answer:
                     Most people would agree in general with Dr. Koeln's statement.

              Ducks Unlimited


              Dr. Koeln replied "Yes, but I wish I had better stated my point. I am not certain of the
              source of the above statement, but I have expressed the sentiment of this statement
              many times. Perhaps. I can better describe my views thus:

                     'Current satellite capabilities are best used for monitoring wetlands and evaluating
                     selective functions of wetlands (i.e., evaluating waterfowl habitat). As a
                     monitoring and evaluation tool of wetlands functions, satellite data are best used
                     in conjunction with NWI digital data. Combining NWI digital data with satellite

                                                         29









                     data for evaluating wetland functions provides much greater information than
                     either product used alone. Current satellite technology cannot delineate and
                     describe wetland types as accurately as the procedures used by NWI. Where NWI
                     data does not exist, the currently available satellite technology should not be used
                     if the objective is wetland delineation. However, if the objective is to evaluate
                     wetland functions at a point in time (i.e., available waterfowl habitat at the time
                     the data were collected), current satellite technology offers an economically
                     feasible solution for rapidly appraising selected wetland functions."'

              SRSC-

              SRSC's biggest objection to Dr. Koeln's statement deals with his comment that satellite
              data "is a poor tool for establishing baseline data on wetlands." SRSC kindly disagrees
              with this statement, because the SCS is now using SRSC's wetland classifications for the
              States of Mississippi and Arkansas as their wetland base for administering the 1.990 Farm
              Bill. Also, their preliminary'work in North Dakota demonstrated the possibility that
              satellite data could be used to establish a wetland base, especially in the agricultural
              prairie areas where wetlands have not been inventoried. SRSC cannot yet provide any
              statistical insight into the comparison of their mapping efforts with those of NWI, but
              they believe their wetland mapping compares favorably with the NWI effort in the SRSC
              study area in North Dakota. They also believe that satellite data are a useful tool for
              monitoring change in wetlands because they have done this work for the SCS to identify
              converted wetlands. The idea of integrating satellite data with NWI data is appealing
              because the NWI Would serve as an excellent mask to locate wetlands prior to processing
              the satellite data.



              20.    At what point can we expect to have permanent storage capability so as to
                     maintain captured digital data on an indefinite basis?

                     Answer:
                     CD-ROM technology offers the greatest potential for maintaining near-permanent
                     storage of digital data.

                     Until there is a storage media capable of lasting a human lifetime or longer, there
                     will always be a need to perform archive maintenance. EDC has a project to
                     copy the Landsat 4 and 5 archive to a helical scan magnetic tape. This activity
                     will begin in October 1992. The computer system is now being built to perform
                     this activity.

                     EOSAT will be working with EDC personnel in this project and expect to initiate
                     a similar project for EOSATs own data in the near future. Landsat 4 and 5 data
                     will be available from 1982 to present.

                     There have been recent advances in recording media. There is now an optical
                     -tape that has a very long predicted shelf life. It is in use at Landsat's Canadian


                                                           30








                     receiving station and is about to be installed in the European Space Agency
                    -facilities.


                     The tradeoffs usually considered in archive media are long term costs and
                     retrieval speed. At the moment, tradeoff studies are making EOSAT lean toward
                     helical scan tape recording.

              EDC

              EDC believes the issue is not the existence of near-permanent storage media, but rather
              media with a moderate lifetime (e.g. 10-20 years) from which data can be rapidly and
              cheaply transcribed to the next generation of storage media, and for which hardware
              necessary for the transcription can be readily available. EDC expects that no matter
              what media are chosen today for archive storage, a new, more desirable media. will be
              available in 10-20 years, and it will want to then convert to that media. EDC's biggest
              problem with the existing Landsat archive has not been media performance, but rather,
              the fact that very specialized hardware was required to transcribe the data and, in the
              case of the older Wide-Band Video tapes, the hardware system is no longer functional.

              EDC hopes to have converted all @Landsat 1 through 5 data to helical scan magnetic tape
              within the next five years. Once that is accomplished, subsequent transcriptions will be
              easier, as the new media will greatly reduce the volume of the data and increase the
              speed with which the data can be transcribed.

              SPOT


              SPOT is now implementing an archiving program that uses CD-ROM. A study is
              currently underway at SPOT that will likely result in an in-house capability to deliver
              products on CD-ROM later this year. Already several projects on CD-ROM have been
              delivered to clients, using outside vendors to convert the data to CD.


              21.    Data Quality Concerns

              Ducks Unlimited


              DU returned the EOSAT TM tape they had received on December 7, 1991. The scene
              was, returned because of numerous line drops and extensive salt-and-peppering. The
              replacement tape had not been received by DU as of January 14, 1992.

              DU typically receives a product from EOSAT 6 to 8 weeks after the order is placed.
              DU is greatly concerned over scenes received with line drops or salt-and-pepper data
              gaps. Rather than return nearly every scene recently purchased, they have found it more
              efficient to correct these problems in-house. When an unacceptable TM tape is
              immediately returned to EOSAT for replacement, the replacement typically takes longer
              to receive than did the original order. DU has waited nearly a year for some of its
              replacement scenes, and often the replacement scene had numerous line drops and salt-

                                                        31









              and-pepper data gaps. Fortunately, the data gaps in the first delivery did not occur at
              the same location as the data gaps in the replacement, and DU was able to patch an
              acceptable scene together.

              DU returned many of the scenes that it had purchased from 1984 through 1986 because
              of data gaps. EOSAT always provided a replacement and after one or more
              replacements, DU was usually able to create a complete image. From 1987 through
              1989, DU returned few if any scenes, thinking this problem had been resolved. In 1990,
              however, these data gaps started to occur again.

              EPA

              Ross Lunetta, at EPA, reported he had similar problems and told the group he did not
              plan to purchase any TM data until it was available from Landsat 6. He thought the
              data problem was with the satellite itself. Dr. David Fischel, Chief Scientist for EOSAT,
              responded that the problem was not with the satellite, but with the processing unit.

              EOSAT


              The EOSAT computer system in use until October 1, 1991, was the original system built
              in 1982. Many of the problems associated with the bad data were caused by this aging
              equipment. The salt-and-pepper effect was principally caused by a deteriorating array
              processor. EOSAT has experienced a dramatic decrease in rejects since October 1, 19.91.
              In the new system, EOSAT is able to perform considerably more quality assurance
              checks to catch bad data before it goes to the customer, but EOSAT is still shaking out
              some insidious bugs. The following problems remain:

                           Dropped scan lines (about 16 output image lines), which can occur for
                           scans that are acquired with the antenna looking close to the horizon.
                           Some salt-and-pepper also occurs with low antenna angle.

                           Dropped "minor frames" (16 lines high and 16 to 32 pixels long), which are
                           usually caused by tape aging.

              The TM tape DU received from EOSAT on December 7, 1991, was produced during the
              turnover to the new system. Just before EOSAT turned the new system on, the old
              system failed. The data set that took so long to process was on a particularly
              obstreperous tape. EOSAT occasionally comes across a tape that is very difficult to read
              correctly.


              REFERENCE


              1. Cowardin, Lewis M., and others, 1979, Classification of wetlands and deepwater
                  habitats of the United States: Washington, D.C., U.S. Government Printing Office.



                                                        32








                                                            Appendix A

             Wetland Classes Used in Waterfowl Habitat and Wetland Inventory

          Ducks Unlimited


          Listed below are the wetland classes that DU uses in its waterfowl habitat inventory
          work in the Prairie Pothole region of Canada and the United States. These classes
          cannot be separated strictly by their spectral characteristics. DU uses ancillary data and
          visual interpretation of the data using their software system, DISP/TRAIN/EDIT. For
          example, mud flats may be confused spectrally with various other types of bare soil;
          however, using visual interpretation skills and the DISP/TRAIN/EDIT software, skilled
          image interpreters can delineate bare soil categories adjacent to wetlands or occurring on
          known wetland areas (from ancillary data) as mud flats.

               WETLAND CODE          DESCRIPTION


                   Wetland


                   100               Undetermined Wetland
                   110               Open Fresh Water
                   ill.              Open Saline Water
                   112               Open Turbid Water
                   120               Deep Marsh
                   130               Shallow Marsh
                   140               Wet Meadow
                   150               Mud Flat
                   160               Dry Wetland
                   170               Forested Wetland
                   180               Riverine Water


                   Bogs

                   200               Undetermined Bog
                   210               Open Bog
                   220               Treed Bog

          In the last six months, DU began a waterfowl habitat inventory program in Alaska. They
          currently try to use the following wetland cover classes, a simplification from Cowardin
          and others (1979):

               WETLAND CODE          DESCRIPTION

                   ElAB              Estuarine Subtidal Aquatic Bed
                   E10W              Estuarine Subtidal Open Water
                   E2EM              Estuarine Intertidal Emergent


                                       A-1









          DU wetland cover classes for waterfowl habitat inventory program in Alaska (continued)

               WETLAND CODE            DESCRIPTION


                    E217L              Estuarine Intertidal Flats
                    L10W               Lacustrine Linmetic Open Water
                    L2AB,              Lacustrine. Littoral Aquatic Bed
                    L2FL               Lacustrine Littoral Flats
                    PAB                Palustrine Aquatic Bed
                    PEMFL              Palustrine Emergent-Flat
                    POW                Palustrine Open Water
                    PUBX               Palustrine Unconsolidated Bottom
                                        Excavated
                    R                  Riverine
                    RX                 Riverine Excavated
                    UPAGR              Upland Agriculture
                    UPBAR              Upland Barren
                    UPDEV              Upland Developed
                    UPRAN              Upland Range
                    UPSS               Upland Scrub-Shrub



          SRSC


          Listed below are the wetland classes used by SRSC.

          Delta Region of Mississippi and Arkansas

                    Farmed Wetlands
                    Natural Wetlands
                    Converted Wetlands
                    Prior Converted Wetlands


          Prairie Pothole region of North Dakota

                    Open Water
                    Deep Marsh
                    Shallow Marsh
                    Shallow Marsh (located in buffer zone from open water)
                    Vegetated Potholes (natural vegetation patches surrounded by bare soil of.
                    an agricultural field)

          Coastal Plain of South.Carolina

                    Palustrine Emergent
                    Palustrine,Woody


                                        A-2,







                                                                                                                                   Appendix B

                                                      SPOT Image Product Fee Schedule
                    When comparing the price lists for SPOT and EOSAT data it is important to realize that
                    a fufl SPOT scene covers approximately one-eighth the area of a M Landsat scene.
                                    SPOT Product Fee Schedule                                                              Effective March, W2

                        1. Standard SPOT Products
                                                                                                                    Panchromatic/Muitfspectral


                            Computer Compatible                 Level IA. IB (Full Scene)                                        $2.450
                            Tapes (CC71                                 6250 or 1600 bpi

                            Film                                Level 1A, 16
                            (30% discount w/corre-                      1:400.000 (Full Scene)                                   $1,800
                                                                        1200,000 (Full Scene)                                    $1.Soo
                            sponding CCT)                               1200,000 (1/4 Scene)                                     $1,800
                                                                        1:100,000 (1/4 Scene)                                    $1,800


                                                                When ordered alone                                                 $950
                            Photographic Prints
                                                                When ordered with corresponding                                    $300
                                                                Level 1 CCT or film


                       2. SPOTView@                        GIS related products
                                                                                                  Dlgftal                   Photographic Print

                            7.5 - (corresponds to USGS 7.5 minute                                 $950                                 $950
                            map series)                                                                                          (1:24,000 7.5 XS
                            P - Panchromatic XS - Munispectral                                                                     not available)

                            15 - Four 7.5 minute SP0TVlews                                        $2.000                             $2,000
                            creating 15 x 15 minute area                                                                           (1:50,000 6-r
                            P - Panchromatic XS - MuRLSWral                                                                         1:63,360)

                            FS - Full SPOT scene                                                  $3.000                             $3,000
                            (37 x 37 miles)                                                                                        (1:100,000)
                            P - Panchromatic XS - Multispectraj


                      I Other SPOT Products
                                                                                                Digital                 P ho tographt FlimlPrint

                            SPOT Digital Terrain Model (OTM)
                            (604/6-100% of full scene size/                                     $15.000
                            minimum of 820 sq. mi.)

                            SPOT Quarter scene DTM                                              $10.000



                            SPOT BasinViewrm - complete
                            coverage of any geologic basin in the world                      $1.80/sq. mi.
                                           B/W only                                     minimum 2,500 sq. mi.                                       W








                        4. Almaz Radar Image Products

                           Standard Product - Approx. 1:100,000 scale photographic                                            $1,600 each
                                   print - mosaic of 6 image strips covering 40 x 40 km area


                           Specialty Products -
                                   Level A CCT                  1600 bpi density                                              $1,600 each
                                   Level 8 CCT                  6250 bpi density                                              $2.400
                                   Level C CCT              1                                                                 $2.800
                                   9" x 9' negative of level B AJmaz image                                                    $2,400
                                   9" x 9' negative of level C Almaz image                                                    $2,800



                        5. Promotional Products

                                       Promotional Data Sets                                       Digital                        Photographic


                           SPOT Education and Evaluation Data Set (S.E.E.D.S.)                       $900                       $ 90 (slides)
                               (33 subscene set)


                           spor Art-                                                                                            $300 (unmounted)
                                                                                                                                S400 (mounted)


                           SPOT Posters                                                                                         $25 (in mailing tube)




                           SPOT User's
                                         Handbook (3 volumes) - $150


                        6. Satellite Acquisition Programming
                                                                                                 Standard                          High Priority

                                                                                                                                      $2,000+
                           Programming Fee                                                      $6001scene                         $3001attempt
                            (does not include final product price)                                                               (up to 10 attempts)






                                                                        Fees DO NOT include Shipping.
                                          AD licensed SPOT Data YAN be delivered 'FOB SPOT image Corporation.* (Reston, VA).
                                                        Scene shiMng for all standard products included at no charge.
                                    Call for information on duplicate copy prices, rush services. processing options, photographic scales
                                                                           and non-standard products.

                                            Additional information can be found in the document SPOT Prodticts and Services.
                                                            Please note: All prices subject to change without notice.
                                                                                  SPOT Image CoMoration
                                                                   1897 Preston White Drive Reston, Virginia 22091-4368
                                                                             (703) 620-2200 - Fax (703) 648-1813



                                                                                      B-2








                                                                                                                                      Appendix C

                                                              EOSAT Product Fee Schedule

                      When comparing the price lists for SPOT and EOSAT data it is important to realize that
                      a fall SPOT scene covers approximately one-eighth"the area of a full Landsat scene.
                                                                               PRODUCTS PRICE SHEET
                                                                                             (Effective octotw 1. 1991)



                                                                      Observation Satellite ComPany - 4M Forbes Boulevard     Lanham, MO 2OMS-9954

                                                                DIGITAL PRODUCTS MAP ORIENTED

                                                                                   Product Code                  Price                     Copy

                                    FuH Scene - Terrain Corrected

                                    6250 Bpi CCr                                  TWMr6F                      $5950                   $90
                                    gmm Cartridge                                 TM"NF                       5950                    90

                                    Full Scene - Precidan Corrected

                                    6250 Bpi CC`r                                 TMFT6F                      $55M                    S90
                                    8aun Cartridge                                TNMNF                       5500                    90

                                    Full Scene - System Corrected

                                    6250 Bpi CC`r                                 TMST6F                      $4400                   $90
                                    8nun Cartridge                                TMS8NF                      4400                    90
                                                                                                        -------------
                                    S-nb-sm-neTic;@     - - - - - - - - - - - - - - -
                                                       X 100. km) - Terrain Corrected

                                    6250 Bpi CCr                                  TMIT6Q                      $4650                   $90
                                    1600 Bpi Ccr                                  TmTnQ                       5115                    90
                                    8rrun Cartridge                               TMTSNQ                      4650                    90

                                    Subscene (100 km X 100 km) - Precision Corrected

                                    6250 Bpi CC`r                                 TM?T6Q                      $4200                   S90
                                    1600 Bpi CC`r                                 TmprriQ                     4620                    90
                                    8mm Owaidge                                   TMPSNQ                      4200                    00

                                    Subscene (100 km X 100 km) - System Corrected

                                    6250 Bpi CCT                                  TMST6Q                      S3100                   $90
                                    1600 Bpi CC`r                                 TMSTIQ                      3410                    90
                                    Sam Cartridge                                 TMS8NQ                      3100                    90
                                    ----------------------------------
                                    Map Sheet - Terraix Corrected

                                    6250 Bpi CC`r                                 TNw6M                       $4=                     $90
                                    1600 Bpi CCT                                  TMTMM                       4455                    90
                                    grain Cartridge                               TMnNM                       4050                    90

                                    Map Shed - Precidon Corrected
                                    6250 Bpi C&                                   TN[FT6?A                    $3600
                                    1600 Bpi CCT                                  TMPTIM                      3960                    90
                                    Sam Catidge                                   TMPSN'M                     3600                    90

                                    Map Sheet - System Corrected

                                    6250 Bpi CC`r                                 TMS`T6M                     S2500                   S90
                                    1600 Bpi CC`r                                 ThfSTIM                     2750                    90
                                    gazin Cartridge                               TMS8NM                      2500                    90


                                                                                      C-1















                                                             DIGITAL PRODUCTS PATH ORIENTED


                                                                                Product Code                         Price                      Copyt
                                    Full Scene - System Corrected
                                    6250 Bpi CCT                                        TPST6F                       S4400                      $90
                                    1600 Bpi CCT                                        TPSTIF                       S4840                      90
                                    8mm Cartridge                                       TPS8NF                          4400                    90

                                    Subscene (100 km X 100 km) - System Corrected

                                    6250 Bpi CCT                                        TPST6Q                       $3100                      $90
                                    1600 Bpi CCT                                        17STIQ                          3410                    90
                                    8mm Cartridge                                       TPS8NQ                          3100                    90


                                                               PHOTO PRODUCTS MAP ORIENTED

                                    Color Film Subscene (100 km X 100 km) - System Corrected

                                    1:500,000 Positive and NegativeTransparencies       TMSCTQ                       $2700
                                    1:500,000 Print                                     TMSCIQ                          2W*
                                    1:250,000 Print                                     TMSC2Q                          200*
                                    1:100,000 Print                                     TMSC5Q                          2000

                                    Must Mullen Trmgpam= first
                                                             PHOTO PRODUCTS PATH ORIENTED

                                    Color Film Full Scene - System Corrected

                                    1: 1,000,000 Positive and Negative Transparencies TPSCTF                         $2700
                                    1: 1,000.000 Print                                  TPSCIF                          200@
                                    1:500,000 Print                                     TPSC2F                          2W*
                                    1:250,000 Print                                     TPSC4F                          2W*

                                    Must Mashase Tymungarency fint



                                                     MULTI SPECTRAL SCANNER (MSS) PRODUCTS
                                        ORBIT-PATH ORIENTED, SYSTEM CORRECTED ONLY. FULL SCENE ONLY

                                    DIGITAL

                                    625D Bpi     Onease specify BSQ or BL)              NfPST6F                         slim
                                    16M Bpi      Mleew specify BSQ or BIL)              hdPSTIF                         1.000              90

                                    PHOTOGRAPHIC PRODUCTS

                                    1: 1.000.OW Color Positive Transpitlency            NMC77                           $600               $120
                                    1:250,000 Color Print                               NMSC4F                          LOW                 2w
                                    1: 1,000.000 B/W Positive Transparency              hVSBTF                          155                  31
                                    1: 1,000.000 B/W Negative Transpuency               h1PSBNF                         175                  35
                                    1: 1.000,000 B/W Print                              N4PSBlF                           95                 19


                                    NOTE' MW prim listed above for MSS          a*y to data aoqukW within 24 mondis of do date am oider is receive&
                                    For Price quoudow derived ftm older MSS dwa. caum SWAT Cuawmer Services.


                                    t Copy Prke appose whem Go d  W" "111mal lw@w@
                                    All priew are ps  led Is U.S. Deasm









                                                                                            C-2


EOSAT'S PRODUCT LINE DEFINITIONS

With the introduction of the new image processing system on October 1, EOSAT changed its product codes and its product
descriptions to better reflect the system's capability. The product catalog uses the new names; the box highlights the major
changes. The terms are explained further below.

		OLD						NEW

	Standard					Path Oriented, System Corrected
	Geocoded					Map Oriented, Precision Corrected
	Movable Scene				Floating Scene
	Quarter Scene Or Quadrant Scene	Subscene (100 X 100km)
	(100 X 85km)


Names have been chosen to encourage customers to tailor their orders to their individual needs. Every order is a custom
order. The phrase "non-standard product" has been banished; if EOSAT can produce the requested item, the order will be
filled. The more popular products are listed on the current price sheets available from Customer Services.

Scenes, Subscenes - Digital TM products are available as full scenes, subscenes and map sheets. TM photo products are
	available as full scenes and subscenes, and MSS products are sold as full scenes.

Floating scenes - Scenes crossing row boundaries are floating scenes, identified by row numbers with decimals. Path 34/
	row 34.2 begins 20% below the top of path 34/row 34. Except for MSS photographic products, a customer may
	order data from any area within a path.

Imagery orientation - Landsat products are correlated to the Earth's surface in one of two ways:
	Path-oriented products have the spacecraft's orbital orientation, with north off to one side of the image. the
	category includes what used to be called the standard digital product.

	Map-oriented products are usually north up. This adjustment facilitates co-registration of Landsat imagery with
	other digital data, as a geographic information system. The customer can select pixel size, map projection and
	Earth ellipsoid model.

Data corrections - Three lecels of Landsat data correction are available.
	System-corrected - All products, digital and photographic, are radiometrically and geometrically corrected. Radio-
	metric corrections are made within a band so that a given detector value always represents the same radiance level
	for the scene. Geometric corrections reorient the image data to compensate for the Earth's rotation and variations in
	spacecraft position and altitude. Landsat data has always been system corrected.

TM Map Oriented Digital Products can be geometric adjusted to two additional levels of positional accuracy.

	Precision-corrected data incorporates ground control points such as road intersections to relate the spacectaft's
	predicted position to its actual geodetic position. This kind of data used to be called geocoded data. EOSAT has
	ground control points for areas within the United States. Customers must furnish topographic maps of 1:50,000 scale
	or better for all other areas. Maps will be returned.

	Terrain-corrected data eliminates the distortion that results from recording a three-dimensional view in two
	dimensions by including relief adjustments from a digital elevation model; this kind of correction is especially
	helpful if the height difference across a scene is more than 500 feet. EOSAT has models for areas within the United
	States. For other areas of the world, customers must supply digital terrain model.


																January 1993




									C-3







                                                                   Appendix D

                                 Acronyms

                      C-CAP              Coast Watch Change Analysis Program, NOAA
                      DEM                digital elevation model
                      DLG                digital line graph
                      DN                 digital number
                      DU                 Ducks Unlimited
                      EDC                EROS Data Center, USGS
                      EOSAT              Earth Observation Satellite Company
                      EPA                U.S. Environmental Protection Agency
                      EROS               'Earth Resources Observation Systems
                      FGDC               Federal Geographic Data Committee
                      FWS                U.S. Fish and Wildlife Service, U.S. Department
                                           of the Interior
                      GIS                geographic information system
                      GPS                global positioning system
                      HRV                high resolution visible (refers to sensors in SPOT
                                          satellite)
                      In                 meter
                      MD-DNR, DNR        State of Maryland, Department of Natural
                                          Resources
                      MSS                multispectral. scanner
                      NASA               National Aeronautics and Space Administration
                      NCG                SCS National Cartographic and GIS Center
                      NWI                National Wetlands Inventory
                      NOAA               National Oceanic and Atmospheric
                                          Administration, U.S. Department of Commerce
                      PRE                project rating error
                      RMS                root mean square
                      SAV                submerged aquatic vegetation
                      SCS                Soil Conservation Service, U.S. Department of
                                          Agriculture
                      SPOT               Satellite Pour I'Observation de la Terre
                      SRSC               Space Remote Sensing Center, NASA
                      TM                 Thematic Mapper
                      U.S.               United States of America
                      USGS               U.S. Geological Survey, U.S. Department of the
                                          Interior
                      UTM                Universal Transverse Mercator (a grid system
                                          based on the transverse mercator map
                                          projection)
                      /4m                micrometer or micron (one-millionth of a meter)




                                           D-1











































































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