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Remote Sens. 2019, 11(2), 103; https://doi.org/10.3390/rs11020103

Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017

1
Heihe Remote Sensing Experimental Research Station, Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Received: 11 December 2018 / Revised: 27 December 2018 / Accepted: 1 January 2019 / Published: 9 January 2019
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Abstract

The Qilian Mountain ecosystems play an irreplaceable role in maintaining ecological security in western China. Vegetation, as an important part of the ecosystem, has undergone considerable changes in recent decades in this area, but few studies have focused on the process of vegetation change. A long normalized difference vegetation index (NDVI) time series dataset based on remote sensing is an effective tool to investigate large-scale vegetation change dynamics. The MODerate resolution Imaging Spectroradiometer (MODIS) NDVI dataset has provided very detailed regional to global information on the state of vegetation since 2000. The aim of this study was to explore the spatial-temporal characteristics of abrupt vegetation changes and detect their potential drivers in the Qilian Mountain area using MODIS NDVI data with 1 km resolution from 2000 to 2017. The Breaks for Additive Season and Trend (BFAST) algorithm was adopted to detect vegetation breakpoint change times and magnitudes from satellite observations. Our results indicated that approximately 80.1% of vegetation areas experienced at least one abrupt change from 2000 to 2017, and most of these areas were distributed in the southern and northern parts of the study area, especially the area surrounding Qinghai Lake. The abrupt browning changes were much more widespread than the abrupt greening changes for most years of the study period. Environmental factors and anthropogenic activities mainly drove the abrupt vegetation changes. Long-term overgrazing is likely the main cause of the abrupt browning changes. In addition, our results indicate that national ecological protection policies have achieved positive effects in the study area. View Full-Text
Keywords: MODIS NDVI; Qilian Mountains; vegetation dynamics; breakpoint; time series analysis MODIS NDVI; Qilian Mountains; vegetation dynamics; breakpoint; time series analysis
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Geng, L.; Che, T.; Wang, X.; Wang, H. Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017. Remote Sens. 2019, 11, 103.

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