Brazil GIS data
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aircraft imagery by T, acquired 2025-10-18 to 2025-10-18, 8.6 cm per pixel, published on OpenAerialMap.
uav imagery by Agência Peixe Vivo, acquired 2025-09-23 to 2025-09-23, 2.8 cm per pixel, published on OpenAerialMap.
uav imagery by Agência Peixe Vivo, acquired 2025-08-27 to 2025-08-27, 3.1 cm per pixel, published on OpenAerialMap.
aircraft imagery by Gabriel Mancilla, acquired 2025-12-14 to 2025-12-14, 6.4 cm per pixel, published on OpenAerialMap.
aircraft imagery by Esteio, acquired 2025-08-21 to 2025-08-21, 75.2 cm per pixel, published on OpenAerialMap.
aircraft imagery by Esdras de Lima Andrade, acquired 2025-08-16 to 2025-08-16, 250.0 cm per pixel, published on OpenAerialMap.
uav imagery by Esdras Andrade, acquired 2025-08-21 to 2025-08-21, 3.9 cm per pixel, published on OpenAerialMap.
Date of Images: Post-Event: April 26, 2024-May 22, 2024 (Daily) Pre-Event: April 2024 (Composite) Summary: These Black Marble Day-Night Band (BRDF-Corrected) images were created by the NASA Black Marble Science team. The images are corrected for atmospheric, terrain, lunar BRDF, and straylight effects, and directly measures light intensity on the ground in units of nanowatts/(steradian centimeter squared). The images are scaled from 0 - 30. The baseline image is from September 2025, generated from all daily atmospheric and lunar-corrected data from that month. There is a layer to display where clouds are present. This comparison between the images is meant as a visual assessment of outage impacts to aid various partners who are working to deliver emergency aids to local communities. Power outage maps like these help disaster response efforts in the short-term as well as long-term monitoring during the crucial stages of disaster recovery. Suggested Use: NASA's Black Marble Nighttime Light product suite is a state-of-the-art daily global collection of standard products for monitoring nighttime lights (NTL). Utilizing the Visible Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) aboard the Suomi-NPP, NOAA-20, and NOAA-21 satellites. The image is in inferno color scale. Yellow represents presence of more light; dark blue less lights. Observations may be obscured by total or partial cloud cover. Other factors such as snow reflectance, moon phase, wildfires, and wildfire smoke may distort light radiance and require further analysis when assessing power outages. Satellite/Sensor: Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP), NOAA-20, and NOAA-21 Resolution: 15 arc-seconds (~500 meters) Credits: NASA Black Marble Science team Please cite the following two references when using this data: Román MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EA, Sun Q, Bell J, Molthan A, Kalb V, Ji C. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PloS one. 2019 Jun 28;14(6):e0218883. Román MO, Wang Z, Sun Q, Kalb V, Miller SD, Molthan A, Schultz L, Bell J, Stokes EC, Pandey B, Seto KC. NASA's Black Marble nighttime lights product suite. Remote Sensing of Environment. 2018 Jun 1;210:113-43. Point of Contact: Ranjay Shrestha NASA Goddard Space Flight Center E-mail: ranjay.m.shrestha@nasa.gov Additional Links: NASA’s Black Marble Product Suite Román, M.O. et al. (2019) Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One, 14 (6). Román, M.O. et al. (2018) NASA’s Black Marble nighttime lights product suite. Remote Sensing of Environment. 210, 113–143. Service URL: See REST Endpoint on the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_blackmarble_brdf/ImageServer/WMSServer
satellite imagery by JONNATHAN NOGUEIRA, acquired 2026-02-11 to 2026-02-12, 1.9 cm per pixel, published on OpenAerialMap.
satellite imagery by Seplag/AL, acquired 2025-09-24 to 2025-09-24, 50.0 cm per pixel, published on OpenAerialMap.
satellite imagery by Municipio de Corupá/SC, acquired 2026-08-05 to 2026-08-05, 10.0 cm per pixel, published on OpenAerialMap.
Date of Images: Dates used for landslide mapping: April 20, 2024; April 21, 2024; May 6, 2024; May 7, 2024; May 8, 2024 Dates of Planet Imagery: 4/20/2023, 5/6/2024, 5/7/2024 Summary: The NASA GSFC landslides team manually mapped landslide initiation points after the April 29, 2024 heavy rainfall in Rio Grande do Sul, Brasil. The landslide initiation points were derived from PlanetScope imagery. This is only a portion of the region where landslides occurred, and areas covered with clouds were not included. More landslides will be mapped in coming days. NOTE: This is a rapid response product. These landslides were manually mapped using different dates of PlanetScope imagery, but all are presumed to have been triggered by the 4/29/2024 heavy rainfall event. As clouds cleared, more landslides were identified. This PlanetScope imagery captured by Planet Labs Inc. in May 2024 shows landslides following the heavy rainfall in Brasil. True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB s produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. Suggested Use: 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: PlanetScope Resolution: 3 meters Credits: NASA Disasters Program, NASA GSFC, Includes copyrighted material of Planet Labs PBC. All rights reserved. Esri REST Endpoint: See Layers below. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landslide_points/MapServer/WMSServer
aircraft imagery by PMSMJ, acquired 2026-09-14 to 2026-09-14, 1.7 cm per pixel, published on OpenAerialMap.
aircraft imagery by PMSMJ, acquired 2026-09-14 to 2026-09-14, 3.0 cm per pixel, published on OpenAerialMap.
aircraft imagery by PMSMJ, acquired 2026-09-14 to 2026-09-14, 2.8 cm per pixel, published on OpenAerialMap.
aircraft imagery by PMSMJ, acquired 2026-09-14 to 2026-09-14, 2.7 cm per pixel, published on OpenAerialMap.
aircraft imagery by PMSMJ, acquired 2026-09-13 to 2026-09-13, 5.0 cm per pixel, published on OpenAerialMap.
aircraft imagery by PMSMJ, acquired 2026-09-13 to 2026-09-13, 2.3 cm per pixel, published on OpenAerialMap.
satellite imagery by Victor Nogueira Antunes, acquired 2026-07-05 to 2026-07-05, 4.0 cm per pixel, published on OpenAerialMap.
uav imagery by Prefeitura, acquired 2025-09-27 to 2025-09-27, 8.9 cm per pixel, published on OpenAerialMap.
Buildings Existing Before the May 2024 Rio Grande do Sul Floods. This dataset contains buildings and destroyed buildings mapped as part of the HOTOSM Rio Grande do Sul Floods Activation mapping project.
This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2. Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Brazil: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons. Fields available: SID: A unique storm identifier (SID) assigned by IBTrACS algorithm. ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss) BASIN: Basin of the current storm position SUBBASIN: Sub-basin of the current storm position NATURE: Type of storm (a combination of the various types from the available sources) NUMBER: Number of the storm for the year (restarts at 1 for each year LAT: Mean position - latitude (a combination of the available positions) LON: Mean position - longitude (a combination of the available positions) WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.
This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long
Sea ports, harbours and ferry terminals. Useful for maritime logistics, supply-chain analysis, and coastal access planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: industrial=port, harbour, port, amenity=ferry_terminal, building=ferry_terminal - Part of the country exports on HDX by HOT
Building footprints across the area: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: building - Part of the country exports on HDX by HOT
Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, building - Part of the country exports on HDX by HOT
Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: tourism, amenity, historic, heritage - Part of the country exports on HDX by HOT
Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: railway - Part of the country exports on HDX by HOT
Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity - Part of the country exports on HDX by HOT
Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: aeroway, building, emergency - Part of the country exports on HDX by HOT
Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: amenity, healthcare - Part of the country exports on HDX by HOT
Road network across the area tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: highway - Part of the country exports on HDX by HOT