ORTOFOTO_UFBA_ONDINA_FEDERAÇÃO
ORTOFOTO_UFBA_ONDINA_FEDERAÇÃO is raster data on imagery and land cover covering Brazil, 2026, published by Drone Mapper Inspeção e Mapeamento LTDA. Licence: CC BY 4.0.
BrazilAbout this dataset
Imagery details
Questions about this data
What does ORTOFOTO_UFBA_ONDINA_FEDERAÇÃO contain?
ORTOFOTO_UFBA_ONDINA_FEDERAÇÃO is raster data about imagery and land cover. Resolution: 3.6 cm.
What area and years does it cover?
It covers Brazil. The data is from 2026.
Can I use it commercially?
Yes: its licence is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), which allows commercial use with attribution where the licence requires it.
How do I cite it?
Drone Mapper Inspeção e Mapeamento LTDA. ORTOFOTO_UFBA_ONDINA_FEDERAÇÃO. Retrieved from OpenAerialMap via OrionGIS.
How do I load it into a map?
Sign in to OrionGIS (free) and choose "Open in map" to load it into Map Studio or add it to a project, or download it to use in QGIS, ArcGIS or any GIS. The source format is GeoTIFF (COG).
Related datasets
Dates of Images: 5/4/2024, 5/5/2024, 5/7/2024 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 Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels, allowing for the ability to see areas impacted from the fires. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. 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 Short Wave Infrared (SWIR) RGB is a product that can provides value in flood detection. Areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta, snow will appear as a bright blue/cyan, and bare soils being multicolor dependent on their makeup. Compare pre-event imagery to post-event imagery to identify potential flooding. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: Sentinel-2: 20 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_202405_FLOOD_BRAZIL/2407_sentinel2/ImageServer/WMSServer
satellite imagery by Filipe Manso Valença, acquired 2025-08-20 to 2025-08-20, 4.9 cm per pixel, published on OpenAerialMap.
aircraft imagery by Perito Paulo Rafael, acquired 2026-07-16 to 2026-07-16, 3.4 cm per pixel, published on OpenAerialMap.
aircraft imagery by Perito Paulo Rafael, acquired 2026-04-30 to 2026-04-30, 2.9 cm per pixel, published on OpenAerialMap.
aircraft imagery by Filipmanso11, acquired 2025-08-21 to 2025-08-21, 4.9 cm per pixel, published on OpenAerialMap.
satellite imagery by Eraldo Moura das Chagas, acquired 2025-04-13 to 2025-04-13, 2.0 cm per pixel, published on OpenAerialMap.
Indexed by OrionGIS from OpenAerialMap. Data is loaded from the publisher's own server when you use it. Permanent link