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Remote Sens. 2015, 7(6), 7597-7614; doi:10.3390/rs70607597

Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China
2
German Remote Sensing Data Centre (DFD), German Aerospace Centre (DLR), D-82234 Wessling, Germany
3
Department of Geography, University of South Carolina, Columbia, SC 29208, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Arnon Karnieli and Prasad S. Thenkabail
Received: 11 February 2015 / Revised: 1 June 2015 / Accepted: 2 June 2015 / Published: 9 June 2015
(This article belongs to the Special Issue Remote Sensing of Land Degradation in Drylands)
View Full-Text   |   Download PDF [6800 KB, uploaded 9 June 2015]   |  

Abstract

Understanding the spatial and temporal dynamics of vegetation is essential in drylands. In this paper, we evaluated three vegetation indices, namely the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Enhanced Vegetation Index (EVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Surface-Reflectance Product in the Xinjiang Uygur Autonomous Region, China (XUAR), to assess index time series’ suitability for monitoring vegetation dynamics in a dryland environment. The mean annual VI and its variability were generated and analyzed from the three VI time series for the period 2001–2012 across XUAR. Two phenological metrics, start of the season (SOS) and end of the season (EOS), were detected and compared for each vegetation type. The mean annual VI images showed similar spatial patterns of vegetation conditions with varying magnitudes. The EVI exhibited high uncertainties in sparsely vegetated lands and forests. The phenological metrics derived from the three VIs are consistent for most vegetation types, with SOS and EOS generated from NDVI showing the largest deviation. View Full-Text
Keywords: MODIS; vegetation index; dryland; vegetation dynamics; time series; phenology MODIS; vegetation index; dryland; vegetation dynamics; time series; phenology
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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

Lu, L.; Kuenzer, C.; Wang, C.; Guo, H.; Li, Q. Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring. Remote Sens. 2015, 7, 7597-7614.

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