• Title of article

    Monitoring forest changes in the southwestern United States using multitemporal Landsat data

  • Author/Authors

    Vogelmann، نويسنده , , James E. and Tolk، نويسنده , , Brian and Zhu، نويسنده , , Zhiliang، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    10
  • From page
    1739
  • To page
    1748
  • Abstract
    Landsat time series data sets were acquired for the Santa Fe National Forest in New Mexico. This area includes the San Pedro Parks Wilderness area, which was designated as an official wilderness in 1964. Eight autumnal Landsat Thematic Mapper (TM) scenes acquired from 1988 to 2006 were analyzed to determine whether significant changes have occurred throughout the region during the past 18 years and, if so, to assess whether the changes are long-term and gradual or short-term and abrupt. It was found that, starting in about 1995, many of the conifer stands within the Wilderness area showed consistently gradual and marked increases in the Shortwave Infrared/Near Infrared Index. These trends generally imply decreases in canopy greenness or increases in mortality. Other high-elevation conifer forests located outside of the Wilderness area showed similar spectral trends, indicating that changes are potentially widespread. The spatial patterns of forest damage as inferred from the image analyses were very similar to the general patterns of insect defoliation damage mapped via aerial sketch mapping by the United States Department of Agriculture Forest Service Forest Health Monitoring Program. A field visit indicated that zones of spectral change are associated with high levels of forest damage and mortality, likely caused by a combination of insects and drought. The study demonstrates the effectiveness of using historical Landsat data for providing objective and consistent long-term assessments of the gradual ecosystem changes that are occurring within the western United States.
  • Keywords
    Forest change , Landsat , Time series
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2009
  • Journal title
    Remote Sensing of Environment
  • Record number

    1629237