Vol. 7, No. 1, 30-45, 2008
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Spatio-temporal drifts in AVHRR/NDVI-precipitation relationships and their linkage to land use change in central Kazakhstan
Pavel Propastin and Martin Kappas
Abstract
Spatial relationship
between vegetation patterns and precipitation in drylands
of Kazakhstan was investigated with Normalised Difference
Vegetation Index (NDVI) derived from
the Advanced Very High Resolution Radiometer (AVHRR) and climate records from
weather stations. A local regression technique known as geographically weighted
regression (GWR) was used to model the growing season relationship between
these variables at the local scale. GWR models were established for each pixel
and every analysis year during the period of 1985-2000. The models exposed
spatial and temporal non-stationarity of the NDVI-precipitation relationships. This
non-stationarity was estimated for each pixel and
each year and mapped. We traced at the per-pixel basis the vegetation response
to precipitation over the period of 1985-2000 and compared it with land
use/land cover change that happened in the study region. For the four cases
investigated the study proved that any temporal drift of this response is a
result of any land use/land cover change. The areas with clear signs of land
degradation displayed either extraordinary low response of NDVI to rainfall
or a permanent decrease of this response
throughout the observation time. On the contrary, the areas associated with
improvement of vegetation cover are characterised by an increase of the
vegetation response to precipitation. The results of this study improve our
understanding of the interaction between the vegetation cover, the climatic
components and human activities of dryland's ecosystem in Central Asia.
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History
Submitted: 11 June 2007
Revised: 20 Feb 2008
Accepted: 18 Mar 2008
Published: 16 Apr 2008
Responsible editor: Bogdan Zagajewski
Citation
Propastin P & M Kappas, 2008.
Spatio-temporal drifts in AVHRR/NDVI-precipitation relationships and their linkage to land use change in central Kazakhstan.
EARSeL eProceedings, 7(1): 30-45
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ISSN 1729-3782
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