Land Change Science Program

Data and Tools

The land cover and land surface data developed by the Land Change Science program is vital to various types of research and management applications, including assessing the impacts of climate change, evaluating ecosystem status and health, understanding spatial patterns of biodiversity, and informing land use planning.

Global Croplands

Global Ecosystems

Multi-Resolution Land Characteristics

Filter Total Items: 14
Date published: April 13, 2021

Fire Danger GACC Regional Forecast Graphs

The GACC Regional Forecast Graphs provide a look at the most recent fire risk outlook in comparison to historical information.

Date published: April 13, 2021

Fire Danger OGC Services

Fire Danger map services are available as Open Geospatial Consortium (OGC) Web Map Service (WMS) services.

Date published: April 13, 2021

Fire Danger Map and Data Products

The Map and Data Products page offers bulk download of the Fire Danger Forecast data suite.

Date published: February 18, 2021

Temperature, relative humidity and cloud immersion data for Luquillo Mountains, eastern Puerto Rico, 2014-201

Supplementary data for studies conducted in the Luquillo Experimental Forest (LEF), eastern Puerto Rico include measurements of temperature, relative humidity and cloud immersion at 30-minute resolution. Temperature and relative humidity were measured at five sites; two primary sites have records from March 2014 to June 2019; other sites have shorter records within that period.

Date published: February 19, 2019

33 high-resolution scenarios of land use and vegetation change in the Upper Missouri River Basin

A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Upper Missouri River Basin region of the northern Great Plains. 

Date published: January 1, 2019

Mangrove Data Collected from J.N. "Ding" Darling National Wildlife Refuge, Sanibel Island, Florida, United States

Mangrove inventory data from J.N. Ding Darling National Wildlife Refuge, Sanibel Island, Florida, USA collected in 2016 and 2017. Plot data includes X and Y downed dead wood count, mangrove species information and site descriptions. Tree data includes the three species found on the refuge: Avicennia germinans (Black mangroves), Laguncularia racemosa (White mangroves) and Rhizo

Date published: December 21, 2018

Fire Danger Forecast Viewer

The Viewer Application provides a dynamic platform for multi-temporal data visualization of the Fire Danger Forecast data suite and supports user defined data subsetting and downloads.

Date published: December 17, 2018

33 high-resolution scenarios of land use and vegetation change in the Prairie Potholes of the United States

A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Prairie Potholes region of Great Plains.

Date published: December 17, 2018

Modeled Historical Land Use and Land Cover for the Conterminous United States: 1938-1992

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country.

Date published: December 17, 2018

The Relative Impacts of Climate and Land-use Change on Conterminous United States Bird Species from 2001 to 2075

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. 

Date published: December 12, 2018

Pothole Hydrology Linked Systems Simulator (PHyLiSS)

PHyLiSS is a generalized coupled hydrologic and hydrogeochemical model of prairie-pothole wetland ecosystems. The current version of PHyLiSS has the capability to simulate wetland hydrology and salinity. Future iterations will be able to simulate the impacts of changing hydrology and salinity on biota.