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DOI10.3390/rs11161860
Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method
Xue, Yayong1; Zhang, Baoqing1; He, Chansheng1,2; Shao, Rui1
发表日期2019
EISSN2072-4292
卷号11期号:16
英文摘要

Vegetation is the major component of the terrestrial ecosystem. Understanding both climate change and anthropogenically induced vegetation variation is essential for ecosystem management. In this study, we used an ensemble empirical mode decomposition (EEMD) method and a linear regression model to investigate spatiotemporal variations in the normalized difference vegetation index (NDVI) over the agropastoral ecotone of northern China (APENC) during the 1982-2015 period. A quantitative approach was proposed based on the residual trend (RESTREND) method to distinguish the effects of climatic (i.e., temperature (TEM), precipitation (PRE), total downward solar radiation (RAD), and near surface wind speed (SWS)) and anthropogenic effects on vegetation variations. The results showed that the NDVI exhibited a significant greening trend of 0.002 year(-1) over the entire study period of 1982-2015 and that areas with monotonous greening dominated the entire APENC, occupying 40.97% of the region. A browning trend was also found in the central and northern parts of the APENC. PRE presented the highest spatial correlation with the NDVI and climate factors, suggesting that PRE was the most important factor affecting NDVI changes in the study area. In addition, the RESTREND results indicated that anthropogenic contributions dominated the vegetation variations in the APENC. Therefore, reusing farmland for grass and tree planting made a positive contribution to vegetation restoration, while deforestation, overgrazing, and the reclamation of grasslands were the opposite. In addition, with the continuous implementation of national ecological engineering programs such as the Grain to Green Program, positive human activity contributions to vegetation greening significantly increased. These results will support decision- and policy-making in the assessment and rehabilitation of ecosystems in the study region.


WOS研究方向Remote Sensing
来源期刊REMOTE SENSING
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/101204
作者单位1.Lanzhou Univ, Coll Earth & Environm Sci, Minist Educ, Key Lab Western Chinas Environm Syst, Lanzhou 730000, Gansu, Peoples R China;
2.Western Michigan Univ, Dept Geog, Kalamazoo, MI 49008 USA
推荐引用方式
GB/T 7714
Xue, Yayong,Zhang, Baoqing,He, Chansheng,et al. Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method[J],2019,11(16).
APA Xue, Yayong,Zhang, Baoqing,He, Chansheng,&Shao, Rui.(2019).Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method.REMOTE SENSING,11(16).
MLA Xue, Yayong,et al."Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method".REMOTE SENSING 11.16(2019).
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