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
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