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Remote Sens. 2016, 8(7), 600; doi:10.3390/rs8070600

Quantifying the Impacts of Environmental Factors on Vegetation Dynamics over Climatic and Management Gradients of Central Asia

1
Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Bonn 53113, Germany
2
Earth Observation Unit, International Center of Insect Physiology and Ecology (ICIPE), Duduville, Kasarani Road, P.O. Box 30772, Nairobi 00100, Kenya
3
German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Wessling 82234, Germany
4
Remote Sensing Research Group, Department of Geography, University of Bonn, Meckenheimer Allee 166, Bonn 53115, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Petri Pellikka, Lars Eklundh, Parth Sarathi Roy and Prasad S. Thenkabail
Received: 17 May 2016 / Revised: 2 July 2016 / Accepted: 13 July 2016 / Published: 15 July 2016
(This article belongs to the Special Issue Monitoring of Land Changes)
View Full-Text   |   Download PDF [3297 KB, uploaded 15 July 2016]   |  

Abstract

Currently there is a lack of quantitative information regarding the driving factors of vegetation dynamics in post-Soviet Central Asia. Insufficient knowledge also exists concerning vegetation variability across sub-humid to arid climatic gradients as well as vegetation response to different land uses, from natural rangelands to intensively irrigated croplands. In this study, we analyzed the environmental drivers of vegetation dynamics in five Central Asian countries by coupling key vegetation parameter “overall greenness” derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI time series data, with its possible factors across various management and climatic gradients. We developed nine generalized least-squares random effect (GLS-RE) models to analyze the relative impact of environmental factors on vegetation dynamics. The obtained results quantitatively indicated the extensive control of climatic factors on managed and unmanaged vegetation cover across Central Asia. The most diverse vegetation dynamics response to climatic variables was observed for “intensively managed irrigated croplands”. Almost no differences in response to these variables were detected for managed non-irrigated vegetation and unmanaged (natural) vegetation across all countries. Natural vegetation and rainfed non-irrigated crop dynamics were principally associated with temperature and precipitation parameters. Variables related to temperature had the greatest relative effect on irrigated croplands and on vegetation cover within the mountainous zone. Further research should focus on incorporating the socio-economic factors discussed here in a similar analysis. View Full-Text
Keywords: land surface dynamics; time-series data; vegetation patterns; Moderate Resolution Imaging Spectroradiometer (MODIS); linear regression modeling land surface dynamics; time-series data; vegetation patterns; Moderate Resolution Imaging Spectroradiometer (MODIS); linear regression modeling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Dubovyk, O.; Landmann, T.; Dietz, A.; Menz, G. Quantifying the Impacts of Environmental Factors on Vegetation Dynamics over Climatic and Management Gradients of Central Asia. Remote Sens. 2016, 8, 600.

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