Coupling spectral unmixing and trend analysis for monitoring of long-term vegetation dynamics in Mediterranean rangelands

The development of vegetation cover is one of the primary indicators for land degradation, stability, or regeneration in regions threatened by overgrazing. This paper addresses the problem how spatially explicit information about degradation processes in European Mediterranean rangelands can be deri...

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Bibliographic Details
Published in:Remote sensing of environment 2003-10, Vol.87 (2), p.183-197
Main Authors: Hostert, Patrick, Röder, Achim, Hill, Joachim
Format: Article
Language:English
Subjects:
Animal, plant and microbial ecology
Applied geophysics
Biological and medical sciences
Earth sciences
Earth, ocean, space
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Internal geophysics
Landsat
Long-term monitoring
Rangelands
Spectral mixture analysis
Teledetection and vegetation maps
Vegetation dynamics
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Summary:The development of vegetation cover is one of the primary indicators for land degradation, stability, or regeneration in regions threatened by overgrazing. This paper addresses the problem how spatially explicit information about degradation processes in European Mediterranean rangelands can be derived from long time series of satellite data. The selected test site in central Crete, Greece, is considered to be representative for the highly heterogeneous character of such landscapes. The monitoring approach comprises the time period between 1977 and 1996, covered by nine Landsat TM and four Landsat MSS images. Special emphasis has hence been put on the evaluation of potentials and drawbacks when coupling Landsat TM and MSS based results. The data sets were geometrically and radiometrically pre-processed in a rigorous fashion, followed by a linear spectral unmixing approach and a time series analysis of vegetation fraction images. Based on the resulting map, the spatio-temporal patterns of vegetation cover changes are explained. Even a test site such as central Crete, with its limited spatial extend, exhibits heterogeneous patterns of change, supporting the hypothesis that long time series of EOS data from Landsat-like sensors are mandatory to identify the relevant changes at landscape level.
ISSN:0034-4257
1879-0704
DOI:10.1016/S0034-4257(03)00145-7