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DOI | 10.3390/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 |
EISSN | 2072-4292 |
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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