Geosciences and Environmental Change Science Center

Data and Tools

GECSC staff are responsible for the development of data and tools that support global environmental research, landscape change investigations, geologic studies and emergency response activities. 

Filter Total Items: 94
Date published: February 28, 2020

Data for Dust deposited on snow cover in the San Juan Mountains, Colorado, 2011-2016: Compositional variability bearing on snow-melt effects

Light-absorbing particles in atmospheric dust deposited on snow cover (dust-on-snow, DOS) diminish albedo and accelerate the timing and rate of snow melt. Identification of these particles and their effects are relevant to snow-radiation modeling and water-resource management. Laboratory-measured reflectance of DOS samples from the San Juan Mountains (USA) were compared with DOS mass lo

Date published: February 28, 2020

A national dataset of rasterized building footprints for the U.S.

The Bing Maps team at Microsoft released a U.S.-wide vector building dataset in 2018, which includes over 125 million building footprints for all 50 states in GeoJSON format. This dataset is extracted from aerial images using deep learning object classification methods. Large-extent modelling (e.g., urban morphological analysis or ecosystem assessment models) or accuracy assessment with v

Date published: February 4, 2020

Thermochronologic data from the southern Stillwater Range, Nevada

This dataset contains apatite and zircon U-Th(He)data, 4He/3He thermochronologic data, and apatite fission-track data from the southern Stillwater Range, Nevada

Date published: January 1, 2020

Data Release for the Validation of the USGS Landsat Burned Area Product across the conterminous U.S.

Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. We present the BA algorithm and products%

Date published: January 1, 2020

Digital data for three-dimensional geologic framework model of the Rio San Jose groundwater basin, New Mexico

This data release contains a geospatial database related to a digital 3D geologic framework of the Rio San Jose watershed, New Mexico. The geospatial database contains two main data elements: (1) input data to the 3D framework model; (2) interpolated elevations and thicknesses of stratigraphic units as a cellular array. Input surface and subsurface data for 18 stratigraphic units ha

Date published: January 1, 2020

Landsat Burned Area Products Data Release - combined sensor products

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and referenc

Date published: January 1, 2020

Landsat Burned Area Products Data Release - Landsat 7 ETM+ products

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and referenc

Date published: January 1, 2020

Landsat Burned Area Products Data Release - Landsat 5 TM products

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and referenc

Date published: January 1, 2020

Landsat Burned Area Products Data Release - Landsat 8 OLI/TIRS products

The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and referenc

Date published: January 1, 2020

Data Release associated with Data Series - DOI/GTN-P Climate and Active-Layer Data Acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge, 1998-2017

This release provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2017; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this release also describes monitoring, data collection, and quality-control methods. Th

Date published: December 20, 2019

Data Release for Toward ecosystem accounts for Rwanda: Tracking 25 years of change in ecosystem service potential and flows

Ecosystem accounts link national-scale environmental and economic trends, offering an internationally standardized approach to tracking sustainability. We compile ecosystem accounts for Rwanda over a 25-year period, and demonstrate that despite strong economic growth, social development, and high-level commitment to environmental goals, ecosystem services fundamental to Rwanda’s

Date published: December 18, 2019

Data release for Influence of multi-decadal land use, irrigation practices and climate on riparian corridors across the Upper Missouri River headwaters basin, Montana

The Upper Missouri River headwaters (UMH) basin (36 400 km2 ) depends on its river corridors to support irrigated agriculture and world-class trout fisheries. We evaluated trends (1984–2016) in riparian wetness, an indicator of the riparian condition, in peak irrigation months (June, July and August) for 158 km2 of riparian area across the basin using the Landsat nor