• DocumentCode
    786564
  • Title

    Unmixing AVHRR imagery to assess clearcuts and forest regrowth in Oregon

  • Author

    Hlavka, Christine A. ; Spanner, Michael A.

  • Author_Institution
    NASA Ames Res. Center, Moffett Field, CA, USA
  • Volume
    33
  • Issue
    3
  • fYear
    1995
  • fDate
    5/1/1995 12:00:00 AM
  • Firstpage
    788
  • Lastpage
    795
  • Abstract
    Advanced Very High Resolution Radiometer imagery provides frequent and low-cost coverage of the Earth, but its coarse spatial resolution (1.1 km by 1.1 km) does not lend itself to standard techniques of automated categorization of land cover classes because the pixels are generally mixed; that is, the extent of the pixel includes several land use/cover classes. Unmixing procedures were developed to extract land use/cover class signatures from mixed pixels, using Landsat Thematic Mapper data as a source for the training set, and to estimate fractions of class coverage within pixels. Application of these unmixing procedures to mapping forest clearcuts and regrowth in Oregon indicated that unmixing is a promising approach for mapping major trends in land cover with AVHRR bands 1 and 2. Including thermal bands by unmixing AVHRR bands 1-4 did not lead to significant improvements in accuracy, but experiments with unmixing these four bands did indicate that use of weighted least squares techniques might lead to improvements in other applications of unmixing
  • Keywords
    forestry; geophysical techniques; image classification; infrared imaging; remote sensing; AVHRR imagery unmixing; Advanced Very High Resolution Radiometer imagery; IR infrared visible; Landsat Thematic Mapper; Oregon; United States USA; automated categorization; clearcut; cover class; forest; forestry; geophysical measurement technique; image classification; image processing; land surface imaging; optical method; regrowth; remote sensing; training set; vegetation mapping; Clouds; Monitoring; NASA; Ocean temperature; Radiometry; Remote sensing; Satellites; Spatial resolution; Temperature sensors; Vegetation mapping;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.387594
  • Filename
    387594