Ethiopia: Normalized Difference Turbidity Index (NDTI)

NDVI Anomaly is a geospatial metric used to measure how current vegetation conditions deviate from what is considered "normal" or average for a specific location and time period. It helps identify abnormal vegetation growth, whether better or worse than expected, and is especially valuable in agriculture, drought monitoring, food security, and environmental management. The dataset used for this analysis is the MOD13Q1 V6.1 product, which provides a Vegetation Index (VI) value on a per-pixel basis. For this study, we used MODIS data from July for the past three years, along with historical data spanning from 2010 to 2020.

Dates of Images: May 5, 2022 Date of Next Image: None Summary: Normalized Difference Water Index (NDWI) 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: For NDWI, 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 to the right. WMS: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_sentinel2_mndwi/ImageServer/WMSServer

Dates of Images: May 5, 2022 Date of Next Image: None Summary: Normalized Difference Water Index (NDWI) 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: For NDWI, 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 to the right. WMS: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2601_201809_HURRICANE_FLORENCE/ex2601_sentinel2_ndwi/ImageServer/WMSServer

Dates of Images: Post-Event: August 13, 2026 Pre-Event: August 3, 2026 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 Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. The Normalized Difference Water Index (NDWI) 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. The 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. Suggested Use: The True Color RGB 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. The Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. For 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. 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 Layers below. WMS Endpoint: See individual layer pages below.

Dates of Images: Post-Event: Pre-Event: June 10; 2026, June 13, 2026; June 15, 2026 Summary: Normalized Difference Water Index (NDWI) 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: For NDWI, 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 to the right.

This dataset presents high-resolution satellite-derived Nighttime Lights (NTL) imagery of Ethiopia,a resolution of approximately 5000 mettres ,  acquired from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS). NTL data captures the intensity and distribution of artificial lighting, serving as a proxy for human settlements, infrastructure development, and economic activity.