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DISASTERS_202405_FLOOD_BRAZIL/2407_opera_dswx_hls (ImageServer)

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Service Description:

Date of Images:

During Event: 5/6/2024

Pre-Event: 4/21/2024

Summary:

The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory and California Institute of Technology derived the surface water extent flood maps using the OPERA Dynamic Surface Water Extent (DSWx) from NASA Harmonized Landsat Sentinel-2 (HLS) products.

The results posted here are preliminary and unvalidated results, primarily intended to aid the field response and people who wanted to have a rough first look at the inundation extent.

ARIA/OPERA flood map derived from DSWx-HLS

The ARIA/OPERA flood map is derived from two OPERA DSWx-HLS images taken on April 21, 2024 and May 06, 2024. These maps depict areas of new water detection that is interpreted as flood. The flood map was created by reclassifying the DSWx-HLS data into two new classes (1) water and (2) not water then taking the difference between the two images. The new water class includes DSWx-HLS classes for open water, partial surface water, and HLS snow/ice. We note the HLS snow/ice mask often misclassified sediment rich water as snow/ice. This reclassification was necessary to capture flood extent. The new not water class includes DSWx-HLS classes not water and HLS cloud/cloud shadow.

OPERA DSWx-HLS

OPERA DSWx-HLS data was used to identify surface water using the B01_WTR layer. Two images were examined 1) April 21, 2024 and 2) May 6, 2024. Each image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file.

OPERA DSWx-HLS data availability

The post-processed products are available to download at https://aria-share.jpl.nasa.gov/202405-RioGrandeSul_Brazil-floods/. The OPERA DSWx-HLS products have been in production since April 2023, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the OPERA project and other products, visit https://www.jpl.nasa.gov/go/opera.

For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite

For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov

Suggested Use:

The OPERA DSWx-HLS Water product classifies the Harmonized Landsat Sentinel-2 (HLS) input imagery into "not water", "open surface water", and “partial surface water”. The "HLS cloud/cloud shadow" and "HLS snow/ice" layers are direct inputs from the HLS FMask.

Areas with "open water" are dark blue and "partial surface water" are light blue in the OPERA WTR layer.

Areas with clouds or cloud shadows are light gray. An area identified as cloud, cloud shadow, or adjacent to cloud/cloud shadow according to input HLS quality assurance (QA) data.

Areas with no water detected are white. An area with valid data that is not water, snow/ice, cloud/cloud shadow, or ocean masked.

This layer is meant to provide users with a quick view for water/no-water. Invalid data classes (cloud/cloud shadow along with adjacent to cloud/cloud shadow) are also provided to indicate areas in which the classification does not provide water/no-water classification.

Note: Sediment rich water is sometimes misclassified as snow/ice by the HLS QA mask.

For more information about how the OPERA DSWx-HLS Water product classifies data: https://d2pn8kiwq2w21t.cloudfront.net/documents/ProductSpec_DSWX_URS309746.pdf

Satellite/Sensor:

Harmonized Landsat Sentinel-2 (HLS)

MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites

Resolution:

30 meters

Credits:

NASA JPL-Caltech ARIA Team, NASA, NASA Disasters Program

Esri REST Endpoint:

See URL section on right side of page

WMS Endpoint:

https://maps.disasters.nasa.gov/ags04/services/brasil_flood_2024/ARIA_Water_Maps_derived_from_OPERA_DSWx_product_suite_for_Brasil_Flooding_and_Landslides/MapServer/WMSServer

Data Download:

https://aria-share.jpl.nasa.gov/202405-RioGrandeSul_Brazil-floods/DSWx-HLS/



Name: DISASTERS_202405_FLOOD_BRAZIL/2407_opera_dswx_hls

Description:

Date of Images:

During Event: 5/6/2024

Pre-Event: 4/21/2024

Summary:

The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory and California Institute of Technology derived the surface water extent flood maps using the OPERA Dynamic Surface Water Extent (DSWx) from NASA Harmonized Landsat Sentinel-2 (HLS) products.

The results posted here are preliminary and unvalidated results, primarily intended to aid the field response and people who wanted to have a rough first look at the inundation extent.

ARIA/OPERA flood map derived from DSWx-HLS

The ARIA/OPERA flood map is derived from two OPERA DSWx-HLS images taken on April 21, 2024 and May 06, 2024. These maps depict areas of new water detection that is interpreted as flood. The flood map was created by reclassifying the DSWx-HLS data into two new classes (1) water and (2) not water then taking the difference between the two images. The new water class includes DSWx-HLS classes for open water, partial surface water, and HLS snow/ice. We note the HLS snow/ice mask often misclassified sediment rich water as snow/ice. This reclassification was necessary to capture flood extent. The new not water class includes DSWx-HLS classes not water and HLS cloud/cloud shadow.

OPERA DSWx-HLS

OPERA DSWx-HLS data was used to identify surface water using the B01_WTR layer. Two images were examined 1) April 21, 2024 and 2) May 6, 2024. Each image consists of multiple MGRS tiles that were merged together for a composite image saved as a GeoTIFF file.

OPERA DSWx-HLS data availability

The post-processed products are available to download at https://aria-share.jpl.nasa.gov/202405-RioGrandeSul_Brazil-floods/. The OPERA DSWx-HLS products have been in production since April 2023, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the OPERA project and other products, visit https://www.jpl.nasa.gov/go/opera.

For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite

For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov

Suggested Use:

The OPERA DSWx-HLS Water product classifies the Harmonized Landsat Sentinel-2 (HLS) input imagery into "not water", "open surface water", and “partial surface water”. The "HLS cloud/cloud shadow" and "HLS snow/ice" layers are direct inputs from the HLS FMask.

Areas with "open water" are dark blue and "partial surface water" are light blue in the OPERA WTR layer.

Areas with clouds or cloud shadows are light gray. An area identified as cloud, cloud shadow, or adjacent to cloud/cloud shadow according to input HLS quality assurance (QA) data.

Areas with no water detected are white. An area with valid data that is not water, snow/ice, cloud/cloud shadow, or ocean masked.

This layer is meant to provide users with a quick view for water/no-water. Invalid data classes (cloud/cloud shadow along with adjacent to cloud/cloud shadow) are also provided to indicate areas in which the classification does not provide water/no-water classification.

Note: Sediment rich water is sometimes misclassified as snow/ice by the HLS QA mask.

For more information about how the OPERA DSWx-HLS Water product classifies data: https://d2pn8kiwq2w21t.cloudfront.net/documents/ProductSpec_DSWX_URS309746.pdf

Satellite/Sensor:

Harmonized Landsat Sentinel-2 (HLS)

MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites

Resolution:

30 meters

Credits:

NASA JPL-Caltech ARIA Team, NASA, NASA Disasters Program

Esri REST Endpoint:

See URL section on right side of page

WMS Endpoint:

https://maps.disasters.nasa.gov/ags04/services/brasil_flood_2024/ARIA_Water_Maps_derived_from_OPERA_DSWx_product_suite_for_Brasil_Flooding_and_Landslides/MapServer/WMSServer

Data Download:

https://aria-share.jpl.nasa.gov/202405-RioGrandeSul_Brazil-floods/DSWx-HLS/



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 30.0

Pixel Size Y: 30.0

Band Count: 1

Pixel Type: U8

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

Mensuration Capabilities: None

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Resampling: false

Copyright Text: NASA JPL-Caltech ARIA Team, NASA, NASA Disasters Program

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: 0

Max Values: 253

Mean Values: 93.79882807826829

Standard Deviation Values: 122.12675564230445

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Northwest

Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

Default Resampling Method: Bilinear

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: true

Allow Analysis: true

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Histograms   Statistics   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Query   Identify   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query GPS Info   Find Images   Image to Map   Map to Image   Measure from Image   Image to Map Multiray   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project