ArcGIS REST Services Directory Login
JSON | SOAP | WMS

texas_flood_202507/uavsar (MapServer)

View In:   ArcGIS JavaScript   ArcGIS Online Map Viewer   ArcGIS Earth   ArcMap   ArcGIS Pro

View Footprint In:   ArcGIS Online Map Viewer

Service Description:

Dates of Images:

July 9, 2025

Date of Next Image:

None Expected

Summary:

These maps show the results of a machine learning classification applied to UAVSAR data to identify open water flooding and inundation under tree canopy.  Colored areas in the image show detected flooding, where the color shows the type of landcover which was flooded (see legend below).  Non-flooded areas are transparent.  The classification uses a U-Net machine learning algorithm which was trained using UAVSAR data from previous flood events.  UAVSAR provides polarimetric synthetic aperture radar data from which different types of scattering mechanisms can be observed, which provides information on the type of flooding.  For example, flooding underneath vegetation produces strong double-bounce scattering from the water surface and tree trunks.  However, strong double-bounce scattering from urban areas aligned with the radar viewing direction, such as in Austin, TX, can produce erroneous classifications.  Non-flooded vegetation is generally dominated by volume scattering from the forest canopy.  In comparison, open water flooding exhibits weak radar returns in all polarizations.

Suggested Use:

Classified Images:

Satellite/Sensor:

UAVSAR airborne L-band synthetic aperture radar (SAR) aboard a NASA Gulfstream C-20A jet.

Resolution:

10 meters

Credits:

UAVSAR data courtesy of NASA/JPL-Caltech

Esri REST Endpoint:

See URL section on right side of the page

WMS Endpoint:

https://maps.disasters.nasa.gov/ags03/services/texas_flood_202507/uavsar/MapServer/WMSServer

Data Download:

https://uavsar.jpl.nasa.gov/cgi-bin/download-files.pl



Map Name: uavsar

Legend

All Layers and Tables

Dynamic Legend

Dynamic All Layers

Layers: Description: Dates of Images:July 9, 2025Date of Next Image:None ExpectedSummary:These maps show the results of a machine learning classification applied to UAVSAR data to identify open water flooding and inundation under tree canopy.  Colored areas in the image show detected flooding, where the color shows the type of landcover which was flooded (see legend below).  Non-flooded areas are transparent.  The classification uses a U-Net machine learning algorithm which was trained using UAVSAR data from previous flood events.  UAVSAR provides polarimetric synthetic aperture radar data from which different types of scattering mechanisms can be observed, which provides information on the type of flooding.  For example, flooding underneath vegetation produces strong double-bounce scattering from the water surface and tree trunks.  However, strong double-bounce scattering from urban areas aligned with the radar viewing direction, such as in Austin, TX, can produce erroneous classifications.  Non-flooded vegetation is generally dominated by volume scattering from the forest canopy.  In comparison, open water flooding exhibits weak radar returns in all polarizations.Suggested Use:Classified Images:Blue   = Open WaterRed    = Flooded DevelopedGreen  = Flooded VegetationOrange = Flooded CropSatellite/Sensor:UAVSAR airborne L-band synthetic aperture radar (SAR) aboard a NASA Gulfstream C-20A jet.Resolution:10 metersCredits:UAVSAR data courtesy of NASA/JPL-CaltechEsri REST Endpoint:See URL section on right side of the pageWMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/texas_flood_202507/uavsar/MapServer/WMSServerData Download:https://uavsar.jpl.nasa.gov/cgi-bin/download-files.pl

Service Item Id: 9e27403324db46ffacd8cf28018387a0

Copyright Text: NASA/JPL-Caltech UAVSAR Team

Spatial Reference: 4326  (4326)


Single Fused Map Cache: false

Initial Extent: Full Extent: Units: esriDecimalDegrees

Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP

Document Info: Supports Dynamic Layers: true

Resampling: false

MaxRecordCount: 2000

MaxImageHeight: 4096

MaxImageWidth: 4096

Supported Query Formats: JSON, geoJSON, PBF

Supports Query Data Elements: true

Min Scale: 0

Max Scale: 0

Supports Datum Transformation: true



Child Resources:   Info   Dynamic Layer

Supported Operations:   Export Map   Identify   QueryLegends   QueryDomains   Find   Return Updates