ArcGIS REST Services Directory Login
JSON | SOAP | WMS

DISASTERS_202405_FLOOD_BRAZIL/2407_bmhd (ImageServer)

View In:   ArcGIS JavaScript   ArcGIS Online Map Viewer   ArcGIS Earth

Service Description:

Date of Image:

Pre-Event: March 2024

Post-Event: 5/7/2024, 5/8/2024, 5/9/2024, 5/10/2025, 5/11/2024, 5/12/2024, 5/15/2024

Date of Next Image:

Unknown

Summary:

These Black Marble High-Definition (BMHD) images were created by the NASA Black Marble Science team, with directed funding the NASA-Google Partnership program. The images map the impact of the major flooding in Rio Grande do Sul on electric grids in Porto Alegre. The baseline image (before the floods) was from May 2024, a cloud-free, moon-free composite, and the “after" image was from May 7, 2024. There is a layer to display where clouds are present in the "after" images. This comparison between the two images is meant as a visual assessment of outage impacts from the flooding to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery.

Suggested Use:

NOTE: Black Marble HD images are downscaled from NASA’s Black Marble nighttime lights product (VNP46), and as such are a “modelled” or “best guess” estimate of how lights are distributed at a 30m resolution. These images should be used for visualization purposes, not for quantitative analysis.

The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights.

Satellite/Sensor:

The primary data source, NASA’s Black Marble nighttime lights product suite (VNP46), utilized to generate this product is derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP) along with high resolution base layers - Landsat derived normalized index products (NDVI and NDWI) and OpenStreetMap (OSM) derived road layer

Resolution:

Scaled resolution of 30 meters

Credits:

NASA Black Marble Science team

Please cite the following two references when using this data:

Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883.

Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43.

Point of Contact:

Ranjay Shrestha

NASA Goddard Space Flight Center

E-mail: ranjay.m.shrestha@nasa.gov

Additional Links:

NASA’s Black Marble Product Suite

Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6).

Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143.

Esri REST Endpoint:

See URL section on right side of page.

WMS Endpoint:

https://maps.disasters.nasa.gov/ags03/services/brasil_flood_202405/blackmarble_hd/MapServer/WMSServe



Name: DISASTERS_202405_FLOOD_BRAZIL/2407_bmhd

Description:

Date of Image:

Pre-Event: March 2024

Post-Event: 5/7/2024, 5/8/2024, 5/9/2024, 5/10/2025, 5/11/2024, 5/12/2024, 5/15/2024

Date of Next Image:

Unknown

Summary:

These Black Marble High-Definition (BMHD) images were created by the NASA Black Marble Science team, with directed funding the NASA-Google Partnership program. The images map the impact of the major flooding in Rio Grande do Sul on electric grids in Porto Alegre. The baseline image (before the floods) was from May 2024, a cloud-free, moon-free composite, and the “after" image was from May 7, 2024. There is a layer to display where clouds are present in the "after" images. This comparison between the two images is meant as a visual assessment of outage impacts from the flooding to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery.

Suggested Use:

NOTE: Black Marble HD images are downscaled from NASA’s Black Marble nighttime lights product (VNP46), and as such are a “modelled” or “best guess” estimate of how lights are distributed at a 30m resolution. These images should be used for visualization purposes, not for quantitative analysis.

The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights.

Satellite/Sensor:

The primary data source, NASA’s Black Marble nighttime lights product suite (VNP46), utilized to generate this product is derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP) along with high resolution base layers - Landsat derived normalized index products (NDVI and NDWI) and OpenStreetMap (OSM) derived road layer

Resolution:

Scaled resolution of 30 meters

Credits:

NASA Black Marble Science team

Please cite the following two references when using this data:

Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883.

Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43.

Point of Contact:

Ranjay Shrestha

NASA Goddard Space Flight Center

E-mail: ranjay.m.shrestha@nasa.gov

Additional Links:

NASA’s Black Marble Product Suite

Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6).

Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143.

Esri REST Endpoint:

See URL section on right side of page.

WMS Endpoint:

https://maps.disasters.nasa.gov/ags03/services/brasil_flood_202405/blackmarble_hd/MapServer/WMSServe



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 12.368068330603972

Pixel Size Y: 12.368068330603972

Band Count: 3

Pixel Type: U8

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

Mensuration Capabilities:

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Resampling: false

Copyright Text: USRA/NASA Black Marble Science team

Service Data Type: esriImageServiceDataTypeRGB

Min Values: 0, 0, 0

Max Values: 255, 243, 131

Mean Values: 6.262274526550119, 2.2949078638608196, 4.264988476441029

Standard Deviation Values: 30.369806011440556, 12.833242280808312, 18.147786512922565

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   Measure   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