Land Resources

Data and Tools

Filter Total Items: 47
Date published: December 12, 2018

Topobathymetric Model for the Southern Coast of California and the Channel Islands, 1930 to 2014

To support the modeling of storm-induced flooding, the USGS Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for the Southern California Coast and Channel Islands. 

Date published: December 11, 2018

Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) Viewer

Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) Viewer Notes

The viewer uses extensive JavaScript and frames which means some browsers may not be able to support full interactive capabilities.

Additionally, the viewer may be difficult for some users to interpret. These users may contact EROS Customer Services...

Date published: December 6, 2018

Vegetation Dynamics Drought Web Services

The Drought Monitoring datasets are available as OGC Web Map Services (WMS). 

Date published: December 4, 2018

Vegetation Dynamics Drought Viewer

The Vegetation Dynamics/Drought viewer provides a dynamic online map interface that can be used to view USGS and other data. 

Date published: August 21, 2018

Topographic Change Viewer

The USGS has developed a national inventory of significant topographic changes based on seamless multi-temporal elevation data and land cover data. The NED and the Shuttle Radar Topography Mission (SRTM) data form a unique pair of seamless elevation datasets that can be used to detect and analyze 20th century topographic surface changes in the United States.  

Date published: June 22, 2018

AVHRR Orbital Drift Data

A USGS EROS-led study concluded that NOAA satellite orbital drift increased the solar zenith angle (SZA), and in turn, influenced the phenological metrics. Eliminating the years with high SZA greatly reduced the influence of orbital drift on the Remote Sensing Phenology time-series. Read the full publication

Users of these...

Date published: June 22, 2018

Temporally Smoothed Weekly AQUA C6 Moderate MODIS NDVI data - 250m

The Temporally Smoothed Weekly AQUA C6 Moderate MODIS NDVI data were developed to provide researchers an analysis ready NDVI dataset, at a spatial resolution of 250 meters, suitable for time series analysis applications and research. Click here to learn more.

Users of these NDVI data sets should cite this DOI:...

Date published: June 22, 2018

C5 Terra Eastern U.S. 250 m eMODIS Remote Sensing Phenology Data

Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.

Date published: June 22, 2018

C5 Terra Western U.S. 250 m eMODIS Remote Sensing Phenology Data

Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.

Date published: June 22, 2018

Conterminous U.S. 1 km AVHRR Remote Sensing Phenology Data

Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.

Date published: June 6, 2018

Remote Sensing Memory Game

In this interactive matching game developed by USGS and AmericaView, you’ll compare satellite images that show land cover change at various locations around the world. The goal is to find all the matching pairs of images in the shortest amount of time.