The objective of the Elevation, Topographic Science, and Lidar Branch, within the EROS Science Division is to establish partnerships and conduct research and applications that facilitate the development and use of integrated national and global topographic datasets. The Program includes research and applications that result in improved seamless topographic datasets, advanced elevation technology research, terrain visualization research, raster and vector technique development research, development of internet presence. Integrated-science applications for mapping, national natural resource initiatives, hazards, and global change science are conducted with partners.

National Elevation Dataset (NED)

The USGS National Elevation Dataset (NED) has been developed by merging the highest-resolution, best quality elevation data available across the United States into a seamless raster format. NED is the result of the maturation of the USGS effort to provide 1:24,000-scale Digital Elevation Model (DEM) data for the conterminous US and 1:63,360-scale DEM data for Alaska. The dataset provides seamless coverage of the United States, HI, AK, and the island territories. NED has a consistent projection (Geographic), resolution (1 arc second), and elevation units (meters). The horizontal datum is NAD83, except for AK, which is NAD27. The vertical datum is NAVD88, except for AK, which is NAVD29. NED is a living dataset that is updated bimonthly to incorporate the "best available" DEM data. As more 1/3 arc second (10m) data covers the US, then this will also be a seamless dataset.

Elevation Derivatives for National Applications (EDNA)

EDNA is a multi-layered database derived from a version of the National Elevation Dataset (NED), which has been hydrologically conditioned for improved hydrologic flow representation. The seamless EDNA database provides 30 meters resolution raster and vector data layers.

Center for LIDAR Information Coordination and Knowledge

There has been increasing demand for research utilizing all information generated from lidar remote sensing data and not just bare earth digital elevation models (DEMs). While this technology has been a proven mapping tool, effective for generating bare earth DEMs,research on using the entire point cloud of this remote sensing data for scientific applications have been slowed by:

• The high cost of collecting lidar
• A steep learning curve on research and understanding involving utilizing the entire point cloud.

The goal of CLICK is to facilitate data access, user coordination and education of lidar remote sensing for scientific needs.

Topographic Change

The USGS has developed a national inventory of significant topographic changes based on seamless multitemporal elevation data and land cover data. The National Elevation Dataset (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.

The need for more comprehensive information on the nature and extent of recent human geomorphic activity led to a spatial emphasis for the first ever accounting of topographic change across the United States. Historical NED data values were subtracted from the recently collected SRTM data to determine significant topographic changes. The National Land Cover Dataset (NLCD) provided land cover information at a 30-meter resolution that matched the NED and SRTM data.

The primary types of topographic changes resulting from human geomorphic activity include surface mining, road construction, urban development, dam construction, and landfills.

Topo - Bathy

Topobathy provides a dynamic online map interface that can be used to view USGS datasets.

GTOPO30

GTOPO30 is a global digital elevation model (DEM) with a horizontal grid spacing of 30 arc seconds (approximately 1 kilometer). GTOPO30 was derived from several raster and vector sources of topographic information. For easier distribution, GTOPO30 has been divided into tiles which can be selected from the map shown above. Detailed information on the characteristics of GTOPO30 including the data distribution format, the data sources, production methods, accuracy, and hints for users, is found in the GTOPO30 README file.