habitat classification

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    Essential fisheries habitatEssential fisheries habitat

    classification in the Lowerclassification in the Lower SongkhramSongkhram

    River BasinRiver Basin using Remote Sensing andusing Remote Sensing andGIS techniquesGIS techniques

    SeksanSeksan DuangsriDuangsri

    UbolratanaUbolratana SuntornratanaSuntornratana

    ThihaThihaAnupongAnupong SanitchonSanitchon

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    1.Introduction1.Introduction Songkhram River Basin are a famous for fisheriesSongkhram River Basin are a famous for fisheries

    production.production.

    Department of Fisheries and MRC conduct the riverDepartment of Fisheries and MRC conduct the rivermanagement .management .

    Remote sensing can be defined as the scienceRemote sensing can be defined as the sciencetechnology and art of obtaining information abouttechnology and art of obtaining information aboutobjects from a distance.objects from a distance.

    Remote sensing help fisheries study throughRemote sensing help fisheries study throughinvestigating spatial distribution of habitats importantinvestigating spatial distribution of habitats important

    for fisheries production and management in integrationfor fisheries production and management in integrationwith GIS technology.with GIS technology.

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    The Lower Songkhram River Basin

    Area StudyThe lower Songkhram River Basin inthe northeastern of Thailand.

    Cutting area come from Landsat imageof WRS path 127 and row 48

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    2. Objectives2. Objectives

    Supporting the Songkhram River FisheriesSupporting the Songkhram River Fisheries

    managementmanagement ProgrammeProgramme

    Using remote sensing images classifyUsing remote sensing images classify

    habitats mappinghabitats mapping

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    3.Methodology3.Methodology3.1 Data sources3.1 Data sources

    DownloadDownload LandsatLandsat ETM+ images of WRS fromETM+ images of WRS fromMichigan State University atMichigan State University at www.landsat.orgwww.landsat.org

    18 March 2003 (dry season)18 March 2003 (dry season)

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    Download from Global Land Cover Facility atDownload from Global Land Cover Facility at

    http://glcfapp.umiacs.umd.edu:8080/esdi/http://glcfapp.umiacs.umd.edu:8080/esdi/

    17 September 2000 (wet season)17 September 2000 (wet season)

    6 November 1992 (master image)6 November 1992 (master image)

    MethodologyMethodology

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    MethodologyMethodology

    Geo-referencing

    Master6Nov1992

    Co-registration

    software

    ERDAS

    Wet/dryimages

    Wet/dryimages

    Wet/dry

    images

    Topo-map

    scale 1:50,000

    software

    ENVI

    Subset transformed images

    Each geo-referencing used at least 20

    ground control points and resulted in a

    total RMSE of less than half a pixel (15

    meters)

    Wet/dryimages

    Transform UTM

    3.2 Image Pre-processing

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    Remote sensing data

    30x30 m28-Sep-04**Landsat 7, ETM+

    30x30 m6-Nov-92*Landsat 5, TM13.2 m30x30 m18-Mar-03Landsat 7, ETM +

    12.8 m30x30 m17-Sep-00Landsat 7, ETM +

    RMSR

    (Root Mean Square Error)

    Ground

    resolution

    Acquisition

    date

    Satellite and sensor

    * = Master image used for image-coregistration of all ETM+ images

    ** = Scan Line Corrector (SLC) off image

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    3.3 Habitat type classification

    A self-developed habitat classification that was based on field

    observations and researchers familiarity with the area

    Reference materials: topographic maps (scale 1:50,000) and

    Landsat images

    Image subsets of Lower Songkram River basin were classified

    into ten habitats.

    Survey for ground truthing

    using : GPS Garmin 60

    time : July-August 2006

    MethodologyMethodology

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    Topographic map for GroundTopographic map for Ground truthingtruthing waypointwaypoint

    scale 1:50,000Ground truthing Waypoint

    July 2006 25 waypoints

    August 2006 27 waypoints

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    3.4 Processing (Image classification)

    Using software ERDAS , ArcView

    Both thematic maps produced simple statisticanalysis of area of each habitat type.

    Wet/dry

    images

    Subset transformed images

    From Geo-referencing

    Data set ground truthing

    ERDAS ArcView

    Thematic map

    MethodologyMethodology

    Inundated flood map

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    4.Outputs4.Outputs

    Total 10 different habitatsTotal 10 different habitats Two habitat maps showing major habitats for

    fisheries

    Inundated Flood Thematic mapInundated Flood Thematic map

    Area statistics for each habitat

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    Permanent water bodies(main rivers and streams)

    Permanent water body (Non-channel type)

    Habitats

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    Riparian mixed vegetation

    Barren land

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    Mixed vegetation Inundated flood

    Paddy rice flied

    Settlement

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    Wet and dry season habitats in Lower Songkhram River basin

    Wet seasonDry season

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    DryDry -- Wet seasonWet season

    Inundated Flood Thematic mapInundated Flood Thematic map

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    Habitat Area (ha) Percentage Area (ha) Percentage

    Permanent water body (river and stream) 5,990 1.71 2,037 0.58

    Permanent water body (non-channel type) 11,262 3.22 11,406 3.25

    Inundated floods 53,486 15.28 - 0.00

    other habitats 279,411 79.79 337,117 96.17

    total 350,148 100.00 350,560 100.00

    Wet season Dry season

    Area statistics for each habitat thematic map

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    5.Problem and limitation5.Problem and limitation Low spatial resolutionLow spatial resolution

    Cloud cover in some areaCloud cover in some area

    Image of September 2004 was not goodImage of September 2004 was not good

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    6.Recommendation6.Recommendation

    The classified habitat maps are subject to accuracyThe classified habitat maps are subject to accuracyassessment to evaluate the correctness of eachassessment to evaluate the correctness of each

    habitat.habitat.

    Ground truth data are necessary for classify habitats.Ground truth data are necessary for classify habitats.

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