UmaTerra
One Earth to all.
A set of open source geospatial analysis tools for understanding the interactions between land, climate and society in Brazil and other countries — land cover, biodiversity, indigenous territories and conservation units, rural cadastre and climate risk, all from the same satellite data and public records. This portal is not a commercial product, but rather a research and open source development initiative, with the goal of sharing knowledge, resources and technology for territorial and environmental management.
Naturametrics, Camposcope and Yvynation each have a Brazil version and a Canada version, built on different data sources and cadastres. On this page they open in the Canada version, in English; the link under each panel opens the Brazil version.
Study interface: analysis point, MapBiomas layers and the National Forest Inventory.
Naturametrics
Land use history and landscape analysis
Reconstructs land-use history and the state of the vegetation around any point on the map, in concentric radii up to 10 km.
- Canada
- AAFC Annual Crop Inventory (2009–2025), NTEMS forest stand age and Hansen forest loss, at radii from 1 to 10 km. The crop inventory is agricultural and stops at about 58° N.
- Brazil
- MapBiomas land cover (1985–2024), the National Forest Inventory, vegetation age and IBGE biomes, at radii from 0.5 to 10 km; drawn areas too.
Who it's for
- Forestry & ecological research
- Land use analysis
- National Forest Inventory
Example use: Compare land cover between 1985 and 2024 within a 10 km radius around a farm.
Open Naturametrics (Canada) →Open Brazil in English
Search by CAR code, coordinate, or municipality, with CAR and IBGE biome layers.
Camposcope
Rural properties in public cadastres
Finds a rural property in the public cadastre and analyses land cover, forest loss and fire inside it and in rings out to 5 km. It describes what the data show and issues no verdict.
- Canada
- British Columbia only: ParcelMap BC parcels, searched by PID, coordinate or municipality; AAFC crop inventory, NTEMS stand age, biomass and MODIS burned area. Clicks off a parcel fall back to protected areas.
- Brazil
- Brazil's Rural Environmental Registry (CAR): search by CAR code, coordinate or municipality; MapBiomas, 2008 SPOT imagery, and the series split at the property's registration date.
Who it's for
- Rural landowners
- Communities
- General public
Example use: See how much forest was lost around a property before and after its registration.
Open Camposcope (Canada) →Open Brazil in English
Home panel, with the four available analysis paths.
Yvynation
Indigenous lands, conservation units and protected areas
Combines satellite imagery, land-cover data and forest-loss detection (Hansen/GLAD) to analyse land use and ecosystem dynamics in protected territories, with maps, charts and reports.
- Canada
- Protected and conserved areas from the federal CPCAD register, starting with British Columbia: AAFC crop inventory, VLCE2 land cover (1984–2022), Hansen forest loss, forest age, biomass and fire; areas made of several parts can be analysed part by part. Canadian Indigenous lands are not analysed, in keeping with the First Nations principles of OCAP®.
- Brazil
- Indigenous lands (FUNAI) and conservation units: MapBiomas, Hansen/GLAD forest loss and land-cover transitions; drawn areas too, and batch processing of many areas at once.
Who it's for
- Indigenous land managers
- Conservation units
- Researchers and journalists
Example use: Follow forest loss year by year inside a protected area and in the land around it, and export a report.
Open Yvynation (Canada) →Open Brazil in English
Impact analysis: the circle, the climate model's cell and the exposure story.
muda-clima
Climate exposure of land use, point by point
Click anywhere in Brazil or Canada: muda-clima reads the land use around it (MapBiomas), the terrain (fire, slope, low ground) and measurements (drought, rain, gusts) and crosses them with three CMIP6 climate models to show which area is exposed to more heat, drought and heavy rain in 2041–2070. Deforestation alerts, ENSO and Sentinel-2 imagery remain as supporting tools.
Who it's for
- Governments & policy
- Conservation efforts
- Communities & NGOs
- Researchers and journalists
Example use: See how many hectares of cropland and forest within 10 km face more days above 35 °C and longer dry spells under SSP2-4.5.
Open muda-clima (Canada) →Open Brazil in English
Support UmaTerra
All four tools are open and free: no ads, no sign-up, no data sold. The code is open source and the sources are public — MapBiomas, Hansen/GLAD, Copernicus, IBGE, INMET and SICAR. What keeps the project running is volunteered time and a cloud bill.
Cost transparency
- Compute for the four tools (Cloud Run)
- ~US$ 34/mo
- Database, container images and storage
- ~US$ 18/mo
- Google Earth Engine — 350 to 700 EECU-hours
- ~US$ 150–300/mo
- True cost of running it
- ~US$ 200–350/mo
None of this is billed today: the infrastructure runs on Google Cloud Research Credits and Earth Engine is used under a noncommercial-use registration, within the free quota. Institutional support is what carries the project when those programmes change — and what keeps the tools free, open and ad-free.
What would this analysis cost?
Open source doesn't mean cost-free.
UmaTerra's tools are free to use. Below is an estimate of what the same processing would cost if you had to pay for it — the value the platform absorbs to keep research and knowledge accessible.
- Earth Engine processing
- Equivalent Earth Engine cost
- Equivalent server cost
- Covered by the platform
- You pay
- US$ 0
An estimate, not an invoice. Derived from the platform's own measured usage: US$ 0.42 per Earth Engine EECU-hour and US$ 0.24 per server hour, assuming roughly 4 analyses per hour of use and a per-analysis cost that grows with area. Longer time series and larger areas consume more.
Ways to help
Institutional support
Universities, NGOs, institutes and public agencies can back the project with an annual contribution. Access stays free and open to everyone — supporters are credited on this page and help set what comes next.
Talk about institutional support →Individual support
Recurring contributions help cover the infrastructure once the research credits run out.
GitHub Sponsors →Cite and credit
If you use data, charts or figures in research, teaching or reporting, cite the platform and the original sources. Each tool ships ready-to-use citation text.
Contribute code
Fixes, translations, bug reports and new analyses are welcome in the open repositories.
Repositories on GitHub →
Supported by
- Google Cloud Research CreditsCloud infrastructure
- Google Earth EngineNoncommercial-use registration
- UBC graduate study grantsResearch funding
- Climate Action and Awareness Fund (Canada)Research funding
- inma.gov.brTechnical validation & feedback
- mgi.gov.brTechnical validation & feedback
- florestal.gov.brTechnical validation & feedback
- MapBiomasLand use and cover data
- GLAD / Global Forest Watch (University of Maryland)Land use and cover data
Institutional supporters are credited here.