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tonga_volcano_tsunami_202201/ARIA_DPMa_color_Sentinel_1_D102_tif (ImageServer)

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Service Description:

Date of Image:

1/15/2022

Date of Next Image:

None Expected

Summary:

The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology, and University of California Los Angeles in Southern California created this preliminary amplitude-based Damage Proxy Map (DPMa) depicting areas that are likely damaged in the Vava'u and Ha'apai islands of Tonga due to the eruption and tsunami of Hunga Tonga-Hunga Ha'apai volcano on 15 Jan. 2022. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) from 10 December 2021 to 15 January 2022.

Suggested Use:

The color variation from pale yellow to red indicates increasingly more significant surface change (drop in radar reflections). Blue tones are increased radar reflections.

This damage proxy map from the radar amplitudes (VH polarization) should be used as guidance to identify damaged or flooded areas, and is most reliable over vegetated areas where trees or buildings were replaced by water or smooth sand. For example, the scattered colored pixels over vegetated areas may be radar noise, and the lack of colored pixels does not necessarily mean no damage. This map is most sensitive to vegetation changes, but small-scale change or partial structural damage may not be detected by this map. Areas of low radar reflection were masked out so this map does not provide information on the Hunga Tonga-Hunga Ha'apai islands.

Satellite/Sensor:

Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)

Resolution:

30 meters

Credits:

Sentinel-1 data were accessed through the Google Earth Engine. The product contains modified Copernicus Sentinel data (2021-2022), processed by ESA and Google Earth Engine, and analyzed by the NASA-JPL/Caltech ARIA team. Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program.

For more information about ARIA, visit: http://aria.jpl.nasa.gov

Esri REST Endpoint:

See URL section on right side of page

WMS Endpoint

Data Download:

https://aria-share.jpl.nasa.gov/202201_Tonga_HungaTonga_Volcano/DPM/



Name: tonga_volcano_tsunami_202201/ARIA_DPMa_color_Sentinel_1_D102_tif

Description:

Date of Image:

1/15/2022

Date of Next Image:

None Expected

Summary:

The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology, and University of California Los Angeles in Southern California created this preliminary amplitude-based Damage Proxy Map (DPMa) depicting areas that are likely damaged in the Vava'u and Ha'apai islands of Tonga due to the eruption and tsunami of Hunga Tonga-Hunga Ha'apai volcano on 15 Jan. 2022. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) from 10 December 2021 to 15 January 2022.

Suggested Use:

The color variation from pale yellow to red indicates increasingly more significant surface change (drop in radar reflections). Blue tones are increased radar reflections.

This damage proxy map from the radar amplitudes (VH polarization) should be used as guidance to identify damaged or flooded areas, and is most reliable over vegetated areas where trees or buildings were replaced by water or smooth sand. For example, the scattered colored pixels over vegetated areas may be radar noise, and the lack of colored pixels does not necessarily mean no damage. This map is most sensitive to vegetation changes, but small-scale change or partial structural damage may not be detected by this map. Areas of low radar reflection were masked out so this map does not provide information on the Hunga Tonga-Hunga Ha'apai islands.

Satellite/Sensor:

Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)

Resolution:

30 meters

Credits:

Sentinel-1 data were accessed through the Google Earth Engine. The product contains modified Copernicus Sentinel data (2021-2022), processed by ESA and Google Earth Engine, and analyzed by the NASA-JPL/Caltech ARIA team. Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program.

For more information about ARIA, visit: http://aria.jpl.nasa.gov

Esri REST Endpoint:

See URL section on right side of page

WMS Endpoint

Data Download:

https://aria-share.jpl.nasa.gov/202201_Tonga_HungaTonga_Volcano/DPM/



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 2.7775793413461623E-4

Pixel Size Y: 2.777667139041189E-4

Band Count: 4

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "", "help": "" }]}

Mensuration Capabilities: Basic

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: NASA-JPL/Caltech ARIA Team, ESA, Copernicus

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: N/A

Max Values: N/A

Mean Values: N/A

Standard Deviation Values: N/A

Object ID Field:

Fields: None

Default Mosaic Method: Center

Allowed Mosaic Methods:

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Nearest

Max Record Count: null

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: null

Max Mosaic Image Count: null

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: false

Supports Advanced Queries: false

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Statistics   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Identify   Measure   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project