Imagery and land cover data

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-06-01 to 2025-06-01, 105.7 cm per pixel, published on OpenAerialMap.

uav imagery by Hawkinson Aerial Photography, LLC, acquired 2025-06-02 to 2025-06-02, 2.7 cm per pixel, published on OpenAerialMap.

satellite imagery by Maxar, acquired 2025-06-02 to 2025-06-02, 30.8 cm per pixel, published on OpenAerialMap.

satellite imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-06-04 to 2025-06-04, 100 cm per pixel, published on OpenAerialMap.

uav imagery by Dylan Tillman, acquired 2025-06-05 to 2025-06-05, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2025-06-06 to 2025-06-06, 32.7 cm per pixel, published on OpenAerialMap.

uav imagery by Lake Piso Solutions, acquired 2025-06-08 to 2025-06-08, 5.1 cm per pixel, published on OpenAerialMap.

uav imagery by Pete the Geek, acquired 2025-06-09 to 2025-06-10, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-10 to 2025-06-10, 3.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-10 to 2025-06-10, 3.3 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-10 to 2025-06-10, 4.1 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-10 to 2025-06-10, 3.8 cm per pixel, published on OpenAerialMap.

aircraft imagery by Roy Hill Survey, acquired 2025-06-12 to 2025-06-12, 47.7 cm per pixel, published on OpenAerialMap.

uav imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-06-13 to 2025-06-13, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Lakshyajeet Jalal, acquired 2025-06-14 to 2025-06-15, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-18 to 2025-06-18, 0.9 cm per pixel, published on OpenAerialMap.

uav imagery by Faine Greenwood, acquired 2025-06-19 to 2025-06-19, 2.8 cm per pixel, published on OpenAerialMap.

uav imagery by Own Work, acquired 2025-06-21 to 2025-06-21, 5.0 cm per pixel, published on OpenAerialMap.

satellite imagery by yandex, acquired 2025-06-20 to 2025-06-21, 1.9 cm per pixel, published on OpenAerialMap.

uav imagery by TOT, acquired 2025-06-23 to 2025-06-23, 3.7 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-24 to 2025-06-24, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by Western North LUSPA RCC, acquired 2025-06-26 to 2025-06-26, 4.4 cm per pixel, published on OpenAerialMap.

uav imagery by Digital Mapper Indonesia, acquired 2025-06-25 to 2025-06-26, 7.5 cm per pixel, published on OpenAerialMap.

uav imagery by GIS, acquired 2025-06-26 to 2025-06-26, 2.7 cm per pixel, published on OpenAerialMap.

Dates of Images: Post-Event: May 19, 2026 Pre-Event: May 11, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Landsat datasets at 30m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Check fire containment and image dates for further context on image timing. Suggested Use: NBR is commonly used as a proxy to indicate areas which have charred vegetation. Darker areas (more negative values) in the NBR image more strongly represent the presence of burned vegetation. Since the dNBR considers the condition of the scene before the fire occurred, the resulting value has been used as a proxy for burn severity. Higher dNBR values represent a proxy for greater burn severity. Negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post imagery. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR may not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure). This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Service URL: See individual Layers. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_KS/202608_landsat_nbr/ImageServer/WMSServer

uav imagery by WebODM, acquired 2025-06-27 to 2025-06-27, 6.8 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-06-27 to 2025-06-27, 6.6 cm per pixel, published on OpenAerialMap.

satellite imagery by Vantor, acquired 2025-06-28 to 2025-06-28, 59.3 cm per pixel, published on OpenAerialMap.

uav imagery by Own work, acquired 2025-06-29 to 2025-06-29, 5.0 cm per pixel, published on OpenAerialMap.

uav imagery by NowItSky Nikolai, acquired 2025-06-28 to 2025-06-28, 4.7 cm per pixel, published on OpenAerialMap.

uav imagery by GPS Land, acquired 2025-07-01 to 2025-07-01, 1.3 cm per pixel, published on OpenAerialMap.

uav imagery by Rodolfo Vargas Chile. GEÓGRAFO, acquired 2025-07-02 to 2025-07-02, 8.0 cm per pixel, published on OpenAerialMap.

Dates of Images: Post-Event: May 16, 2026 Pre-Event: May 11, 2026 Date of Next Image: None 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. 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. 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 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_KS/202608_sentinel2/ImageServer/WMSServer

uav imagery by Bousché Ecologie, acquired 2025-07-04 to 2025-07-04, 2.0 cm per pixel, published on OpenAerialMap.

satellite imagery by Nikolay Nowitsky, acquired 2025-07-05 to 2025-07-06, 3.2 cm per pixel, published on OpenAerialMap.

uav imagery by WebODM, acquired 2025-07-08 to 2025-07-08, 3.4 cm per pixel, published on OpenAerialMap.