NLCD 2011 Full Details

Full Details

Title:

NLCD 2011

Description:

The National Land Cover Database 2011 (NLCD2011) percent tree canopy cover (TCC 2011) layer was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium (www.mrlc.gov). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service, the U.S. Forest Service, the National Park Service, the U.S. Fish and Wildlife Service, the Bureau of Land Management, NASA, and the U.S. Army Corps of Engineers. One of the primary goals of the project was to generate a current, consistent, and seamless national land cover, percent tree canopy cover, and percent impervious cover at medium spatial resolution. TCC 2011 is the NLCD tree canopy cover dataset for CONUS at medium spatial resolution (30 m). It was produced by the USDA Forest Service Remote Sensing Applications Center (RSAC). The TCC 2011 dataset has two layers: percent tree canopy cover and standard error. For the tree canopy cover layer, the pixel values range from 0 to 100 percent. For the standard error layer, the pixel values range from 0 to 45 percent. The standard error represents the model uncertainty associated with the corresponding pixel in the tree canopy cover layer. The tree canopy cover layer was produced using a Random Forests™ regression algorithm and the standard error layer was calculated from the variance of the canopy cover estimates from the random forest regression trees. The goal of this project is to provide the Nation with complete, current and consistent public domain information on its tree canopy cover.

Provider:

Cornell

Resource Class:

Datasets

Resource Type:

Raster data

Theme:

Biology, Land cover, and Environment

Temporal Coverage:

2011

Place:

New York (State)

Access Rights:

Public

Format:

GeoTIFF

Date Added:

2023-03-14