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Quantifying Vegetation Change in Semiarid Environments: Precision and Accuracy of Spectral Mixture Analysis and the Normalized Difference Vegetation IndexBecause in situ techniques for determining vegetation abundance in semiarid regions are labor intensive, they usually are not feasible for regional analyses. Remotely sensed data provide the large spatial scale necessary, but their precision and accuracy in determining vegetation abundance and its change through time have not been quantitatively determined. In this paper, the precision and accuracy of two techniques, Spectral Mixture Analysis (SMA) and Normalized Difference Vegetation Index (NDVI) applied to Landsat TM data, are assessed quantitatively using high-precision in situ data. In Owens Valley, California we have 6 years of continuous field data (1991-1996) for 33 sites acquired concurrently with six cloudless Landsat TM images. The multitemporal remotely sensed data were coregistered to within 1 pixel, radiometrically intercalibrated using temporally invariante surface features and geolocated to within 30 m. These procedures facilitated the accurate location of field-monitoring sites within the remotely sensed data. Formal uncertainties in the registration, radiometric alignment, and modeling were determined. Results show that SMA absolute percent live cover (%LC) estimates are accurate to within ?4.0%LC and estimates of change in live cover have a precision of +/-3.8%LC. Furthermore, even when applied to areas of low vegetation cover, the SMA approach correctly determined the sense of clump, (i.e., positive or negative) in 87% of the samples. SMA results are superior to NDVI, which, although correlated with live cover, is not a quantitative measure and showed the correct sense of change in only 67%, of the samples.
Document ID
20010030713
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Elmore, Andrew J.
(Brown Univ. Providence, RI United States)
Mustard, John F.
(Brown Univ. Providence, RI United States)
Manning, Sara J.
(Inyo County Water Dept. Bishop, CA United States)
Elome, Andrew J.
(Brown Univ. Providence, RI United States)
Date Acquired
August 20, 2013
Publication Date
January 1, 2000
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier Science, Inc.
Volume: 73
ISSN: 0034-4257
Subject Category
Life Sciences (General)
Funding Number(s)
CONTRACT_GRANT: NAG5-6003
Distribution Limits
Public
Copyright
Other

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