Skysat Imagery (NDVI) for the Kansas Fires May 2026
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✦ Suggested by OrionAIDates of Images Post-Event: 5/21/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. 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. 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. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
Dates of Images Post-Event: 5/17/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. 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. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
Dates of Images Post-Event: 5/21/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. 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. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Skysat. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
NOTE: Due to the higher resolution of this data, it may be slow to load or require the user to zoom to a smaller area of interest. Date of Images: Post-Event: 7/11/2026, 7/12/2026 Pre-Event: Date of Next Image: Unknown Summary: Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. 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. Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. 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. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space and may show damage caused by severe weather. 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. A 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. Resolution: ~1 meter Esri REST Endpoint: See URL section on right side of page of individual layers below.
NOTE: Due to the higher resolution of this data, it may be slow to load or require the user to zoom to a smaller area of interest. Date of Images: Post-Event: 7/11/2026, 7/12/2026 Pre-Event: Date of Next Image: Unknown Summary: Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. 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. Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. 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. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space and may show damage caused by severe weather. 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. A 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. Resolution: ~1 meter Esri REST Endpoint: See URL section on right side of page of individual layers below.
Dates of Images Post-Event: 8/3/2026 Summary Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. 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. Resolution ~1 m Credits NASA Disasters Program, Processing from MSFC, Planet. For derived products: “Includes copyrighted material of Planet Labs PBC. All rights reserved.” This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) program.
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