landsat_indices_202625

✦ DISCOVERED BY ORIONAIRASTERpatrick_reaImagery and land coverUnited States of America
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About this dataset

Dates of Images: Post-Event: Pre-Event: 9/18/2026, 9/19/2026, 9/28/2026 Date of Next Image: Unknown Summary: NDVI: The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: NDVI: Dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page

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sentinel2_ndvi_202625

Dates of Images: Post-Event: 10/12/2026 Pre-Event: 9/23/2026, 9/18/2026, 9/19/2026, 9/15/2026, 10/1/2026 Date of Next Image: Unknown Summary: NDVI: The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: NDVI: Dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page

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Dates of Images: Post-Event: 5/8/2024; 5/15/2024 Pre-Event: 4/6/2024; 4/21/2024 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_landsat_ndvi/ImageServer/WMSServer

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(EXERCISE - DaNCE March 2026) mNDWI Imagery (Landsat 9) for the Brazil Floods May 2024

Dates of Images: Post-Event: 5/8/2024; 5/15/2024 Pre-Event: 4/6/2024; 4/21/2024 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landsat_mndwi/ImageServer/WMSServer

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Landsat Imagery for the US Severe Weather April 2025

Dates of Images: Post-Event: 4/14/2025; 4/15/2025 Pre-Event: 4/8/2025 Date of Next Image: Unknown Summary: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. Modified Normalized Difference Water Index (MNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: True Color: provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. NDVI: dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. mNDWI: areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI), Landsat 8 Resolution: 30 meters Credits: NASA/MSFC, USGS Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=3b491d2372d94c4cbc8bac96407e68e8 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202504_SEVEREWX_SOUTHEASTUS/2505_landsat/ImageServer/WMSServer

Imagery and land cover · rachel.vershel
(EXERCISE - DaNCE March 2026) mNDWI Imagery (Landsat 9) for the Red River Flooding May 2022

Dates of Images: Post-Event: 5/24/2022 Pre-Event: 5/16/2022 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_landsat_mndwi/ImageServer/WMSServer

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ex2603_landsat_mndwi

Dates of Images: Post-Event: 5/24/2022 Pre-Event: 5/16/2022 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_landsat_mndwi/ImageServer/WMSServer

Water · patrick_rea

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