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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
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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:
XMin: -97.99934246705534
YMin: 30.294494032297372
XMax: -97.61435574404733
YMax: 30.579219275018076
Spatial Reference: 4326
(4326)
Full Extent:
XMin: -99.89713002
YMin: 29.45738418
XMax: -96.87744402
YMax: 31.02084258
Spatial Reference: 4326
(4326)
Units: esriDecimalDegrees
Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP
Document Info:
Title: uavsar
Author:
Comments: Date of Images:July 9, 2025Date of Next Image:None ExpectedSummaryThese UAVSAR false color RGB images provide a unique look at the Earth's surface that can be used for identifying flooding and inundation under tree canopy. The overlay of the intensities of these three polarization channels allows user to visually classify a scene by its backscattering mechanism, such as surface scattering (strong HH and VV return), volume scattering (strong HV return) and double-bounce scattering (strong HH return). Areas dominated by green (HV) intensity are typically vegetated areas. Areas dominated by shades of pink (HH+HV) intensity are typically inundated forests or vegetated fields. Black and dark grey areas are usually smooth surface (roads, open water, smooth bare ground) where there is very little radar backscatter.Suggested Use:Classified Image:Blue = Open WaterGreen = Flooded VegetationRed = Flooded DevelopedOrange = 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/ags04/services/hurricane_milton_2024/uavsar_stjohn_peace_rivers/MapServer/WMSServerData Download:https://uavsar.jpl.nasa.gov/cgi-bin/download-files.pl
Subject: Classified UAVSAR
Category:
Keywords: NASA,NASA Disasters Program,JPL,Caltech,UAVSAR,Texas,Flood,Flooding
AntialiasingMode: Fast
TextAntialiasingMode: Force
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:
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