Data

This data release includes a file geodatabase with land cover maps for a 313-kilometer segment along the mainstem Klamath River corridor downstream from Iron Gate Dam, CA. The maps were derived from high-resolution (15cm) imagery and topobathymetric elevation data, collected by NV5 Geospatial (formerly QSI, Inc) and published on Open Topography (https://doi.org/10.5069/G9DN436N). Acquisition dates

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This data supports an article that summarizes a new mixed-methods and

Raster data depicting estimated jaguar energy expenditure required to move north from the US-Mexico border to reach important water sources. The data were generated for five scenarios: walled, un-walled crossing and three remediation scenarios: a border crossing through the wall in rugged terrain towards the west end of the wall, a crossing in a dry wash centrally located, one in less rugged terra

Vector data showing areas of dense oil and gas development that mule deer are expected to avoid, for twelve study sites in the Book Cliffs region in Utah.

Here we provide information for the PlanetScope and d Deutsches Zentrum fur Luft- und Raumfahrt (DLR) Earth Sensing Imaging Spectrometer (DESIS) Derived Spectral Library of Agricultural Crops in California which was developed using PlanetScope Dove-R high spatial resolution data and DESIS hyperspectral data acquired for 2020. PlanetScope images are available through Planet Labs (2022). The DESIS i

We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize the frequency of forest change across the conterminous United States (CONUS) between 1985-2020. Data include a raster map of CONUS with pixel values representing the number of years in which it was classified as

Annual (1986-2020) land-use/land cover maps at 30-meter resolution of the Tucson metropolitan area, Arizona and the greater Santa Cruz Watershed including Nogales, Sonora, Mexico. Maps were created using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier in Google Earth Engine. The maps contain 13 classe

This dataset includes raster species distribution models of five pine species in the Madrean sky islands of Mexico and the United States. Models were trained using a large bi-national field dataset (n = 1,416) of pine species observations. Species distribution models were created for the following pine species: P. arizonica (syn. P. ponderosa var. arizonica); P. discolor (syn. P. cembroides var. b

This dataset consists of raster geotiff outputs from modeling habitat change, marsh vertical accretion, and carbon accumulation in the Nisqually River Delta, Washington, USA. These rasters represent projections of future habitat type, change in surface elevation above Mean Sea Level, and total sediment carbon accumulation since 2011 in coastal wetland habitats. Projections were generated in 20-yea

This dataset provides location information and some limited attributes of known and potential cienegas in the Madrean Archipelago ecoregion and closely surrounding area. This was created using point data and information provided by Dean Hendrickson and Thomas Minckley, combined with potential locations derived from analysis of classified raster land cover images and other specialized datasets. Cie

Burn probability (BP) models involve the simulation of multiple individual wildfires across a landscape to obtain estimates of fire likelihood at any given location based on ignition source, local terrain, fuels and weather. We used FlamMap software to generate BP for 10,000 simulated fires under the three ignition scenarios: human ignition scenario (HIS), lightning ignition scenario (LIS) and ran

Spatially explicit maps of annual forest carbon stocks and tabular estimates of land use/land cover change, LULC transitions, carbon stocks and carbon fluxes for selected regions and geographies. Estimates span the period from 2001-2020. Scenarios included are defined with a unique numerical identifier. scn160 = Full Simulation (Land use and Climate Effects) scn155 = Climate Effects only scn156