Forest Cover Index for Tree Cover Detection Using Landsat-7 Multispectral Imagery

Abstract

Forest cover monitoring using satellite imagery is important to U.S. military terrain analysis. Mobility models, cover and concealment, and precise surface feature delineation all rely on an accurate forest/nonforest cover layer. However, the challenge remains in distinguishing trees from other vegetative land covers when relying on single date imagery. A Forest Cover Index (FCI) algorithm was previously developed on Worldview-2 imagery and was designed to separate forest cover from nonforest covered areas. In this research, the FCI algorithm was applied to Landsat-7 imagery using the analogous red (636673 nanometers (nm)) and near-infrared bands (851878 nm) from a peak summer image on 16 August 2012. The results obtained with Landsat-7 imagery proved satisfactory with an overall accuracy (tree cover versus non-tree cover) of > 83 percent, according to testing with two different accuracy assessment tests. The application of the FCI to Landsat-7 imagery broadens the applicability of the FCI to freely available imagery.

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Document Details

Document Type
Technical Report
Publication Date
Sep 12, 2019
Accession Number
AD1080372

Entities

People

  • Andrew L. Russ
  • Craig S. Daughtry
  • Kristofer D. Lasko
  • Luisa I. Felicianio-cruz
  • Sarah J. Becker

Organizations

  • Geospatial Research Laboratory

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Agriculture
  • Algorithms
  • Artificial Satellites
  • Department Of Defense
  • Detection
  • Ecology
  • Environment
  • Environmental Protection
  • Geography
  • High Resolution
  • Information Science
  • Monitoring
  • Multispectral
  • Remote Sensing
  • Satellite Imaging
  • Statistical Sampling

Readers

  • Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • Space