The Wildland Almanac - CONUS: a 30 m Landsat-derived time series of conterminous-U.S. wildland ecosystem properties across forests, shrublands, and grasslands; decadal snapshots for water years 1990, 2000, 2010, 2020, and 2024. 17 properties spanning five themes - vegetation cover, hydrology, fire hazard, carbon, and past disturbance severity. The Fire_LCP landscape is delivered as eight single-band COGs (fuel model, canopy cover, canopy height, canopy base height, canopy bulk density, plus static elevation, slope, and aspect). Disturbance is cumulative for the period between snapshots. Created using a unified methodology that emphasizes temporal and cross-property consistency, to track change, explore tradeoffs, and support decision-making and scientific discovery. Cloud-Optimized GeoTIFFs with a STAC catalog. CC BY 4.0.
The CONUS release of the Wildland Almanac: an open, 30 m, Landsat-derived record of how the conterminous United States' forests, shrublands, and grasslands have changed over time. Seventeen biophysical properties - vegetation cover and structure, hydrology, fuels and fire hazard, carbon, and disturbance - produced from the Landsat archive through a single cross-consistent pipeline, at decadal snapshots.
Current release: v2026.1 (June 2026). Water years 1990, 2000, 2010, 2020, and 2024, conterminous U.S., all 17 layers. Released under CC BY 4.0.
This directory is the CONUS half of the Wildland Almanac. The California release - annual water years 1985–2025 - is the sibling dataset at
source.coop/wildland-almanac/california. The two share methods and conventions; the main differences are temporal cadence (California annual vs. CONUS decadal snapshots), the disturbance encoding (annual vs. cumulative), and the mask (CONUS masks open water, the area outside the conterminous U.S., and agricultural land).
v2026.1/ - the actual data files (108 COGs across 17 layer directories)WildlandAlmanac_CONUS_Documentation.pdf - the binding reference for units, methods, projections, the cumulative-window definitions, and the UC disclaimer (§6)v2026.1/catalog.json - machine-readable inventory, with 17 collections and 108 itemswildlandalmanac.org../california/ - California coverage (annual, water years 1985–2025)Seventeen properties, five themes, water years 1990, 2000, 2010, 2020, and 2024 (October–September), 30 m resolution, EPSG:5070 (NAD83 / CONUS Albers). All files are Cloud-Optimized GeoTIFFs (COGs). Canopy height, cover, base height, and bulk density are provided as bands of Fire_LCP, not as standalone layers.
Vegetation cover and structure (4)
Veg_TreeFrac/ - fractional tree canopy coverVeg_ShrubFrac/ - fractional shrub coverVeg_HerbFrac/ - fractional herbaceous coverVeg_BareFrac/ - fractional bare/non-vegetated coverHydrology (6)
WaterFlux_AETmax/ - maximum evapotranspiration (vegetation-driven, no drought limitation)WaterFlux_AETrealized/ - realized evapotranspiration (accounting for precipitation)WaterFlux_Soilmoisture/ - end-of-water-year soil moistureWaterFlux_SoilmoistureFrac/ - end-of-water-year soil moisture as a fraction of maximum rooting-zone storageWaterFlux_Runoff/ - annual discharge (precip minus AETrealized)WaterFlux_PminusETmax_SPI0/ - vegetation-driven water yield at long-term-mean precipitationFire hazard (3)
Fire_LCP/ - the components of a FARSITE/FlamMap landscape, delivered as eight single-band COGs: five per-snapshot-year (fuel model, canopy cover, canopy height, canopy base height, canopy bulk density) and three static (elevation, slope, aspect). Clip and stack the bands to assemble a landscape - see the Use It page for the carve-and-stack recipe.Fire_FlamMap_FL/ - FlamMap-predicted flame length (relative hazard, fixed run conditions)Fire_FlamMap_ROS/ - FlamMap-predicted rate of spread (relative hazard, fixed run conditions)Carbon (2)
Carbon_AGB/ - aboveground live biomass (metric tons / hectare)Carbon_GPP/ - gross primary production (g C / m² / yr)Disturbance severity (2) - cumulative loss summed over unequal-length windows ending in each snapshot year (5 / 10 / 10 / 10 / 4 years for 1990 / 2000 / 2010 / 2020 / 2024; see documentation §4.3)
Disturbance_TreeFrac_cumulative/ - cumulative loss of tree fractional cover at disturbed pixelsDisturbance_AGB_cumulative/ - cumulative loss of aboveground biomass at disturbed pixelsFilenames follow WildlandAlmanac_CONUS_{Property}_{WaterYear}.tif. The Fire_LCP bands follow WildlandAlmanac_CONUS_Fire_LCP_{Band}_{WaterYear}.tif (five per-year bands) and WildlandAlmanac_CONUS_Fire_LCP_{Band}.tif (three static topographic bands, no year). See the documentation PDF for full per-layer specifications, units, scaling conventions, methodology, and caveats.
Note on base names.
Disturbance_TreeFracandDisturbance_AGBare annual in the California release and cumulative here (hence the_cumulativesuffix). Because the CONUS windows differ in length, do not compare values across snapshots without normalizing to a per-year rate.
The Almanac uses an archival versioning model:
v2026.1/, v2027.1/, …). Files at a published version URL are stable: once a version has been used in published work, its contents are preserved.v2026.2/) with its own DOI, and the prior version will be retained.Cite the version you used. Each release receives its own DOI. When citing the Almanac in a paper, EIR, plan, or other document where future readers may need to verify the exact values you relied on, cite the specific version (and DOI), not the dataset as a whole. This is what makes the reference chain reproducible.
For analysis within one release: use one version end-to-end. Do not splice snapshots from different versions - every release reprocesses the full set, so values for a given year may differ between versions.
The data are Cloud-Optimized GeoTIFFs served over both S3 and HTTPS. Three access patterns, in increasing order of effort:
Stream it - most common, no download. GIS tools (ArcGIS Pro, QGIS, rasterio, terra) can read COGs directly from cloud storage, transferring only the bytes needed for your current window.
s3://us-west-2.opendata.source.coop/wildland-almanac/conus/v2026.1/{Layer}/WildlandAlmanac_CONUS_{Layer}_{Year}.tif/vsicurl/https://data.source.coop/wildland-almanac/conus/v2026.1/{Layer}/WildlandAlmanac_CONUS_{Layer}_{Year}.tifDownload one file - curl, wget, browser, or PowerShell Invoke-WebRequest against the HTTPS URL above. To clip a lat/long box without downloading the whole file, use gdalwarp -te ... -te_srs EPSG:4326 /vsicurl/<url> clip.tif - GDAL fetches only the tiles overlapping your box. (Because the CONUS grid is large - 105,000 × 160,000 pixels - clipping to an area of interest rather than downloading whole layers is usually the right approach.)
Bulk download - AWS CLI with --no-sign-request (no account needed):
aws s3 sync s3://us-west-2.opendata.source.coop/wildland-almanac/conus/v2026.1/{Layer}/ ./{Layer}/ --no-sign-request
Building a fire-behavior landscape from Fire_LCP - the eight bands are single-band COGs; clip each to your area of interest, then stack them in LCP band order (elevation, slope, aspect, fuel model, canopy cover, canopy height, canopy base height, canopy bulk density). Modern FlamMap reads the GeoTIFF stack directly. The worked recipe is on the Use It page.
Full how-to with worked examples - ArcGIS Pro, QGIS, Python (rasterio), R (terra), and the cloud-native workflow background - is on the website's Use It page. That page is the authoritative how-to reference.
The Wildland Almanac is built to be as useful as the underlying observations allow, and the layers compare favorably with comparable products and with the published literature. But much of this work remains very difficult, and the dataset has real limits. Some pixels are wrong in ways that are known and documented; others are wrong in ways that have not yet been identified. Some layers are better than others; some snapshots are more or less constrained than others; some regions and vegetation types are better characterized than others.
Anyone using these data for a specific decision should look critically at the values for their area of interest, compare against on-the-ground knowledge and independent observations when possible, and consider the documentation's notes on methods and caveats. The CONUS layers are masked for open water, areas outside the conterminous U.S., and agricultural land (NLCD cultivated crops and pasture/hay); developed/urban and barren pixels are retained and should be screened by the user where they are not of interest (see documentation §4.4). The decision to release the data publicly reflects our judgment that it uses the best information of its kind available, that we believe it has reached the point where it can aid planning and research, and that use-with-feedback is the path to improvement. Reports of what looks wrong - pixel-level errors, structural issues, or systematic problems - are the most valuable contribution a user can make.
Released under Creative Commons Attribution 4.0 (CC BY). Free to use, share, and adapt with attribution.
University of California disclaimer. These data are a University of California product, provided "as is" with no warranty; the user assumes all risk of use. Use of the data implies consent to the full University of California disclaimer, reproduced in §6 of the documentation PDF.
Goulden, M.L. (2026). The Wildland Almanac - CONUS (Version v2026.1). Source Cooperative. DOI: [pending - EZID]. Released under CC BY.
When citing analyses based on these data, cite the specific version (above). Different versions reprocess the full snapshot set and may differ in detail; the version DOI is what makes your analysis reproducible.
Found something wrong, or have a use case to share? Please file an issue on GitHub: github.com/wildland-almanac/wildland-almanac-site/issues. Reports of errors and notes on real-world use are tracked there and folded into future releases.
Contact: mgoulden@uci.edu · Department of Earth System Science, University of California, Irvine. The data are offered with no promise of technical support, but feedback on errors and use cases is welcome and shapes future releases.
The Wildland Almanac is an outgrowth of the Center for Ecosystem Climate Solutions (CECS), which was supported by California's Strategic Growth Council. CECS was a multi-year California research program; the CONUS release extends the same methodology nationally. Earlier work and publications referencing CECS share the same project lineage.