AndreaBozzo/ceres-open-data-index huggingface dataset:
LANDFIRE 2023 Fuel Disturbance (FDist) CONUS

LANDFIRE disturbance products are developed to provide temporal and spatial information related to landscape change. In the LF 2023 Update (LF 2023) Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2014 to 2023. FDist is created from LF 2023 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities, and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Forest Canopy Cover (CC), Height (CH), Bulk Density (CBD), Base Height (CBH), 13 Anderson Fire Behavior Fuel Models (FBFM13) and 40 Scott and Burgan (FBFM40). 
FDist is developed using the most current aggregated Annual Disturbance products from 2014 to 2023. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://www.landfire.gov/data/lf2023.

Tags: biota, conterminous-united-states, continental-u-s, conus, disturbance, fdist, fires, fuel-disturbance, geographic-information-systems, geospatial-datasets, hazard-preparedness, image-collections, imagerybasemapsearthcover, landfire-2023, lf-2023, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, usgs-672507eed34e4f57573f411a
Organization: Department of the Interior
LANDFIRE 2023 Forest Canopy Height (CH) CONUS

LANDFIRE's 2023 Update (LF 2023) Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Forest Canopy Bulk Density (CBD) and Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create CH, LANDFIRE's Existing Vegetation Height (EVH) product must be produced first. EVH is a continuous scaled product which assigns height to all life forms in the LF data, this product is created using an image-based process (within the Conterminous United States (CONUS)) to assess canopy structure for areas disturbed in the past twenty years. CH is then derived from EVH by assigning bins of 13 height classes for fuel production and use in fire behavior software. In LF 2023, fuel products are created with LF 2016 Remap vegetation in areas that were un-disturbed in the last twenty years. 
To designate disturbed areas where CH is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://www.landfire.gov/data/lf2023.

Tags: biota, canopy-height, ch, conterminous-united-states, continental-u-s, conus, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, image-collections, imagerybasemapsearthcover, landfire-2023, lf-2023, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, usgs-67250789d34e4f57573f40a3
Organization: Department of the Interior
LANDFIRE 2023 Forest Canopy Cover (CC) CONUS

LANDFIRE's 2023 Update (LF 2023) Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. In fire behavior models, CC supplies information to determine the probability of crown fire initiation, provides input in the spotting model, and aids in calculating wind reductions and fuel moisture conditioning. To create CC, LANDFIRE's Existing Vegetation Cover (EVC) product must be produced first. EVC is a continuous scaled product which assigns cover to all life forms in the LF data, this product is created using an image-based process (within the Conterminous United States (CONUS)) to assess canopy structure for areas disturbed in the past twenty years. CC is then derived from EVC by assigning bins of 10% for fuel production and use in fire behavior software. CC is used in the calculation of Forest Canopy Bulk Density (CBD) and Base Height (CBH).  
To designate disturbed areas where CC is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://www.landfire.gov/data/lf2023.

Tags: biota, canopy-cover, cc, conterminous-united-states, continental-u-s, conus, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, image-collections, imagerybasemapsearthcover, landfire-2023, lf-2023, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, usgs-67250725d34e4f57573f4031
Organization: Department of the Interior
Raster Climate Priming Index and supporting data for Alaska and Northwest Canada 1901-2100

The datasets presented here include the Climate Priming Index, degree-day, and seasonal precipitation data used as inputs to the index for the state of Alaska. The data is presented for two time periods: a historic period from 1901-2020, and a projected period from 2000-2100 using 3 climate scenarios. The climate priming index was developed to identify years where the climatic conditions support the initiation of thermokarst processes in areas of ice-rich permafrost. The Climate Priming Index is comprised of 6 components calculated from cumulative distribution functions based on 5 unique variables: freezing degree-days, thawing degree-days, summer precipitation, early winter precipitation, and total winter precipitation. The Climate Priming Index is based on the previous year's values for each of the unique variables plus the current year's thawing degree-day values. Freezing and thawing degree-days were calculated from monthly data using a piecewise cubic hermite interpolating polynomial. Seasonal precipitation was calculated from monthly data using additional inputs from the polynomial used to calculate the degree-day data.

Tags: alaska, climate, climate-change, climatologymeteorologyatmosphere, environment, geoscientificinformation, geospatial-datasets, permafrost, thermokarst, usgs-67506d4dd34ea60e89434a68, yukon-territory
Organization: Department of the Interior
LANDFIRE 2023 Historical Disturbance (HDist) Puerto Rico US Virgin Islands

LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. Historical Disturbance (HDist) is developed from the base annual LF disturbance products, and attribute code system, to represent the history of disturbance for a 10-year span. Each year's disturbance scenarios are checked against time relevant LF vegetation products to check for logical inconsistencies. Errant codes are flagged and updated to a discard code with the remaining disturbance types cross-walked/aggregated to Fuel Disturbance (FDist) types.  
HDist includes the year of disturbance that is recorded for that pixel (see the HDIST_YR column in the attribute table). The HDist attribute table also contains an HDIST_ID field that is the disturbance year combined with the disturbance code. See the HDIST_CAT column for the FDist code combined with the disturbance code.

Tags: biota, disturbance, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, hdist, historical-disturbance, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2023, lf-2023, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-673f646dd34e565ca5dd0a39
Organization: Department of the Interior
LANDFIRE 2023 Fuel Vegetation Height (FVH) HI

LANDFIRE's 2023 Update (LF 2023) Fuel Vegetation Height (FVH) product represents the LF Existing Vegetation Height (EVH) product, modified to represent pre-disturbance EVH in areas where disturbances have occurred over the past 10 years. In LF 2023, vegetation products are created through an image-based process (within the Conterminous United States (CONUS)) that assesses canopy structure (Forest Canopy Height (CH) and Cover (CC)). EVH is mapped as continuous estimates of canopy height for tree, shrub, and herbaceous lifeforms with a potential range of 0-100m. Continuous EVH values are binned to align with fuel model assignments when creating FVH. FVH is an input for fuel transitions related to disturbance and fuel products in LF 2023 were created with LF 2016 Remap vegetation in non-disturbed areas. 
To designate disturbed areas where FVH is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023.

Tags: biota, evh, existing-vegetation-height, fires, fuel-vegetation-height, fvh, geographic-information-systems, geospatial-datasets, hawaii, hazard-preparedness, hi, image-collections, imagerybasemapsearthcover, landfire-2023, lf-2023, oconus, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, usgs-673bb5c4d34ee39d4683a668
Organization: Department of the Interior
Natural color aerial imagery and structure-from-motion data products from Uncrewed Aircraft System (UAS) 2D Mapping flights at the Marsh-Felch Quarry in Garden Park Fossil Area, Colorado, July 2024

The U.S. Geological Survey (USGS) National Uncrewed Systems Office (NUSO) supported the USGS National Cooperative Geologic Mapping Program’s Geoheritage Sites of the Nation Project in July of 2024 with the collection of UAS-based high-resolution imagery of the Marsh-Felch Quarry site at the Bureau of Land Management (BLM) Garden Park Fossil Area. One of the most complete dinosaur skeletons ever unearthed was found here. These discoveries around present-day Garden Park Fossil Area sparked the “Bone Wars” of the late 1800s and inspired the selection of Colorado's state fossil, the Stegosaurus. Three-dimensional (3D) scan flights were conducted at the fossil site using a Skydio X10 UAS, in which the aircraft autonomously determined where to capture photos to achieve coverage across a volume of interest. The natural color UAS images were processed in photogrammetry software to generate a 3D model of this fossil site for inclusion in the Geoheritage web application. A two-dimensional (2D) mapping scan with the Skydio X10 UAS flown at 300 feet above ground level was also conducted to capture the topography of the surrounding area.
This portion of the data release presents raw natural color images collected during the 2D mapping flights over the fossil site. Over the course of one 21-minute flight, a Skydio X10 UAS with an integrated VT300-Z Narrow sensor mapped a 36,483 square meter area and captured 456 natural color red, green, blue (RGB) photos to achieve 75% overlap and 75% sidelap. The images are provided here in a zip file to facilitate bulk download.
Structure-from-motion (SfM) Digital Surface Model (DSM) and Orthomosaic data products were generated by processing these 2D Mapping images in photogrammetry software. These data products are provided here in .tif format zipped with supporting files. These DSM and orthomosaic data products were generated for visualization of the environment surrounding the quarry site.

Tags: bureau-of-land-management, canon-city, colorado, drone, fremont-county, geoheritage-sites, geosciences-and-environmental-change-science-center, geospatial-datasets, geotourism, late-jurassic, morrison-formation, national-natural-landmark, natural-color, paleontology, photogrammetry, remote-sensing, rgb, skydio-x10, stegosaurus, structure-from-motion, u-s-geological-survey, uas, uncrewed-aircraft-system, united-states, usgs, usgs-674f562fd34e09a37b8884a5
Organization: Department of the Interior
LANDFIRE 2023 Forest Canopy Height (CH) HI

LANDFIRE's 2023 Update (LF 2023) Forest Canopy Height (CH) describes the average height of the top of the canopy for a stand. CH is used in the calculation of Forest Canopy Bulk Density (CBD) and Base Height (CBH). CH supplies information for fire behavior models, such as FARSITE (Finney 1998), that can determine the starting point of embers in the spotting model, wind reductions, and the volume of crown fuels. To create CH, LANDFIRE’s Existing Vegetation Height (EVH) product must be produced first. EVH is a continuous scaled product which assigns height to all life forms in the LF data. CH is then derived from EVH by assigning bins of 13 height classes for fuel production and use in fire behavior software. In LF 2023, fuel products are created with LF 2016 Remap vegetation in areas that were un-disturbed in the last twenty years. 
To designate disturbed areas where CH is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023.

Tags: biota, canopy-height, ch, fires, geographic-information-systems, geospatial-datasets, hawaii, hazard-preparedness, hi, image-collections, imagerybasemapsearthcover, landfire-2023, lf-2023, oconus, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, usgs-673bbbbdd34ee39d4683a746
Organization: Department of the Interior
LANDFIRE 2023 Existing Vegetation Cover (EVC) Puerto Rico US Virgin Islands

LANDFIRE's (LF) 2023 update (LF 2023) Existing Vegetation Cover (EVC) represents the vertically projected percent cover of the live canopy for a 30-m cell. EVC is produced separately for tree, shrub, and herbaceous lifeforms. Training data depicting percentages of canopy cover are obtained from plot-level ground-based visual assessments and lidar observations. These are combined with Landsat imagery (from multiple seasons), to inform models built independently for each lifeform. Tree, shrub, and herbaceous lifeforms each have a potential range from 10% to 100% (cover values less than 10% are binned into the 10% value). The three independent lifeform datasets are merged into a single product based on the dominant lifeform of each pixel. The EVC product is then reconciled through QA/QC measures to ensure lifeform is synchronized with Existing Vegetation Height (EVH). 
In LF 2023 Conterminous United States (CONUS) extent, LF will map the lifeform, cover, and height of existing vegetation in areas that were mapped as disturbed over the last twenty years (see LF Annual Disturbance products) using machine learning methods. These disturbed areas were the focus because they are the areas that have changed the most since LF 2016 Remap. To learn more about this new methodology for LF EVC, EVH, and Existing Vegetation Type (EVT) go to https://landfire.gov/data/lf2023.

Tags: biota, evc, existing-vegetation-cover, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2023, lf-2023, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-673f65b3d34e565ca5dd0a54
Organization: Department of the Interior
LANDFIRE 2023 Fuel Vegetation Height (FVH) Puerto Rico US Virgin Islands

LANDFIRE’s 2023 Update (LF 2023) Fuel Vegetation Height (FVH) product represents the LF Existing Vegetation Height (EVH) product, modified to represent pre-disturbance EVH in areas where disturbances have occurred over the past 10 years. EVH is mapped as continuous estimates of canopy height for tree, shrub, and herbaceous lifeforms with a potential range of 0-100m. Continuous EVH values are binned to align with fuel model assignments when creating FVH. FVH is an input for fuel transitions related to disturbance and fuel products in LF 2023 were created with LF 2016 Remap vegetation in non-disturbed areas. 
To designate disturbed areas where FVH is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023.

Tags: biota, evh, existing-vegetation-height, fires, fuel-vegetation-height, fvh, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2023, lf-2023, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-673f66e5d34e565ca5dd0a65
Organization: Department of the Interior
Data for Fatal interactions: Pneumonia in bighorn lambs following experimental exposure to carriers of Mycoplasma ovipneumoniae

We hypothesized that bighorn sheep ewes with chronic nasal Mycoplasma ovipneumoniae carriage are the source of infection that results in fatal lamb pneumonia. We tested this hypothesis in captive bighorn ewes at two study facilities over a 5-year period, by identifying carrier ewes and then comparing lamb fates in groups that did (exposed pens) or did not (non-exposed pens) include one or more carrier ewes. This data set describes the outcomes of those experiments.

Tags: bighorn-sheep-mycoplasma-ovipneumoniae-epizootic-pneumonia-chronic-carriage-captive-exposure-so, biota, usgs-67462349d34e6d1dac3abda4
Organization: Department of the Interior
STATSGO Cloud Optimized GeoTIFFs for the Continental US

This data release reformats data fields from the STATSGO soil characteristics dataset (Schwarz and Alexander, 1995) as cloud-optimized GeoTIFFs (COGs). The COG format allows standard software tools to efficiently access the datasets over an internet connection. Please refer to the documentation of the source archive (Schwarz and Alexander, 1995) for additional details on the underlying dataset.
This data release includes COGs for the KF-factor (KFFACT) and soil thickness (THICK) data fields. KF-factors are defined as the saturated hydraulic conductivity of the fine soil (&lt; 2mm) fraction in units of inches per hour. The soil thickness dataset has units of inches.
Each COG raster spans the continental US at a nominal 30 meter resolution. The spatial reference is EPSG:5069. Each COG uses a float32 precision, and the NoData value (NaN) indicates raster pixels not covered by the original STATSGO dataset. The COGs also include non-physical values of -0.1, which were used by the source STATSGO archive to mark large water bodies.
The COG format uses compression internally to reduce file size. As such, reading large portions of a COG into memory can require much more RAM than the nominal file size. The COGs in this dataset will require ~60GB of memory to read in full.
This dataset can be reproduced by running the included `rasterize_statsgo.py` Python script. Please refer to the script for documentation and usage instructions.
Disclaimer: 
Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 
References:
Schwarz, G.E. and Alexander, R.B., 1995, Soils data for the Conterminous United States Derived from the NRCS State Soil Geographic (STATSGO) Data Base. [Original title: State Soil Geographic (STATSGO) Data Base for the Conterminous United States.]: U.S. Geological Survey data release, https://doi.org/10.5066/P94JAULO.

Tags: cloud-optimized-geotiff, geoscientificinformation, kf-factor, raster, soil-characteristics, soil-thickness, statsgo, usgs-675083c6d34ea60e894354ad
Organization: Department of the Interior
LANDFIRE 2023 Fuel Vegetation Type (FVT) Puerto Rico US Virgin Islands

LANDFIRE’s 2023 Update (LF 2023) Fuel Vegetation Type (FVT) product represents the LF Existing Vegetation Type Ecological Systems (EVT) product modified to represent pre-disturbance EVT in areas where disturbances have occurred over the past 10 years. Due to shifting EVT codes and labels throughout the years, the FVT codes are based on an early version of EVT codes translated from the current version. FVT is an input for fuel transitions related to disturbance and fuel products in LF 2023 were created with LF 2016 Remap vegetation in non-disturbed areas. 
To designate disturbed areas where FVT is modified, the aggregated Annual Disturbance products from 2014 to 2023 in the LF Fuel Disturbance (FDist) product are used. All existing disturbances between 2014-2023 are represented in LF 2023, and the products are intended to be used in 2024 (the year of release).  
When using any product from the LF 2023 fuel product suite, users should consider adjusting fuel layers for disturbances that occurred after the end of the 2023 fiscal year (after October 1st, 2023). Disturbances that occurred after the end of the 2023 fiscal year are not accounted for within LF 2023 fuel products. Learn more about LF 2023 at https://landfire.gov/data/lf2023.

Tags: biota, evt, existing-vegetation-type, fires, fuel-vegetation-type, fvt, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2023, lf-2023, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-673f67bdd34e565ca5dd0a72
Organization: Department of the Interior