The dominant influencing factors of desertification changes in the source region of Yellow River: Climate change or human activity?

被引:105
作者
Guo, Bing [1 ,2 ,3 ,4 ,5 ,6 ,7 ]
Wei, Cuixia [1 ]
Yu, Yang [1 ]
Liu, Yifeng [1 ]
Li, Jialin [1 ]
Meng, Chao [3 ]
Cai, Yumei [3 ]
机构
[1] Shandong Univ Technol, Sch Civil Architectural Engn, Zibo 255000, Shandong, Peoples R China
[2] Key Lab Meteorol & Ecol Environm Hebei Prov, Shijiazhuang 050021, Hebei, Peoples R China
[3] China Land Survey & Planning Inst, Key Lab Land Use, MNR, Beijing 100035, Peoples R China
[4] Chinese Acad Sci, Key Lab Digital Earth Sci, Beijing 100101, Peoples R China
[5] Inst Geog Sci & Nat Resources Res, Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
[6] Minist Nat Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen 518000, Peoples R China
[7] Minist Nat Resources, Key Lab Natl Geog Census & Monitoring, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金;
关键词
Desertification; Feature space; Spatial and temporal pattern; Geodetector; Source region of Yellow River; 3-RIVER HEADWATERS REGION; QINGHAI-TIBET PLATEAU; DETECTION MODEL; VEGETATION; QUALITY; CHINA;
D O I
10.1016/j.scitotenv.2021.152512
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to the combined effects of global warming and human activities, the ecological environment of the Yellow River source area has undergone profound changes and desertification has become increasingly prominent. In this study, an optimal desertification monitoring index based on feature space was proposed for the Yellow River source area, and constructed using Landsat images. Then, the spatial and temporal variation of desertification in the Yellow River source area and its driving mechanism were studied using Geodetector. The main conclusions are as follows: (1) The newly proposed feature space-based desertification monitoring index has good applicability in the study area. The best inversion accuracy of the point-to-point Albedo-NDVI feature space model was 88.4%. (2) Desertification in the eastern and southern regions of the Yellow River source area has a tendency to increase, while the desertification situation in the central region is relatively stable. (3) From 1995 to 2015, there was a significant improvement in desertification in the study area, as evidenced by a decrease in desertification intensity. (4) As the intensity of human disturbance increases, the influence of natural factors on desertification gradually diminishes. The interaction of natural and anthropogenic factors has greater explanatory power for desertification than that of individual natural or anthropogenic factors. The research results can be used as a reference for decision-making on desertification control in the Three-River Source Region.
引用
收藏
页数:18
相关论文
共 48 条
[1]   Assessment of desertification using modified MEDALUS model in the north Nile Delta, Egypt [J].
Abuzaid, Ahmed S. ;
Abdelatif, Abdelatif D. .
GEODERMA, 2022, 405
[2]   Synthesized remote sensing-based desertification index reveals ecological restoration and its driving forces in the northern sand-prevention belt of China [J].
Chen, Ang ;
Yang, Xiuchun ;
Guo, Jian ;
Xing, Xiaoyu ;
Yang, Dong ;
Xu, Bin .
ECOLOGICAL INDICATORS, 2021, 131
[3]   Quantitatively determine the dominant driving factors of the spatial-temporal changes of vegetation NPP in the Hengduan Mountain area during 2000-2015 [J].
Chen, Shu-ting ;
Guo, Bing ;
Zhang, Rui ;
Zang, Wen-qian ;
Wei, Cui-xia ;
Wu, Hong-wei ;
Yang, Xiao ;
Zhen, Xiao-yan ;
Li, Xing ;
Zhang, Da-fu ;
Han, Bao-min ;
Zhang, Hai-ling .
JOURNAL OF MOUNTAIN SCIENCE, 2021, 18 (02) :427-445
[4]  
Feng J., 2018, CHINA RURAL WATER HY, V2, P147, DOI 10.11821/yj2013020003
[5]   Path analysis model to identify and analyse the causes of aeolian desertification in Mu Us Sandy Land, China [J].
Feng, Kun ;
Wang, Tao ;
Liu, Shulin ;
Yan, Changzhen ;
Kang, Wenping ;
Chen, Xiang ;
Guo, Zichen .
ECOLOGICAL INDICATORS, 2021, 124
[6]   Spatial-temporal shifts of ecological vulnerability of Karst Mountain ecosystem-impacts of global change and anthropogenic interference [J].
Guo, Bing ;
Zang, Wenqian ;
Luo, Wei .
SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 741
[7]   Improved evaluation method of the soil wind erosion intensity based on the cloud-AHP model under the stress of global climate change [J].
Guo, Bing ;
Zang, Wenqian ;
Yang, Xiao ;
Huang, Xiangzhi ;
Zhang, Rui ;
Wu, Hongwei ;
Yang, Luoan ;
Wang, Zhen ;
Sun, Guangqiang ;
Zhang, Yi .
SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 746
[8]   Spatial and temporal change patterns of net primary productivity and its response to climate change in the Qinghai-Tibet Plateau of China from 2000 to 2015 [J].
Guo, Bing ;
Zang, Wenqian ;
Yang, Fei ;
Han, Baomin ;
Chen, Shuting ;
Liu, Yue ;
Yang, Xiao ;
He, Tianli ;
Chen, Xi ;
Liu, Chunting ;
Gong, Rui .
JOURNAL OF ARID LAND, 2020, 12 (01) :1-17
[9]   Dynamic monitoring of desertification in Naiman Banner based on feature space models with typical surface parameters derived from LANDSAT images [J].
Guo, Bing ;
Zang, Wenqian ;
Han, Baomin ;
Yang, Fei ;
Luo, Wei ;
He, Tianli ;
Fan, Yewen ;
Yang, Xiao ;
Chen, Shuting .
LAND DEGRADATION & DEVELOPMENT, 2020, 31 (12) :1573-1592
[10]   Detection model of soil salinization information in the Yellow River Delta based on feature space models with typical surface parameters derived from Landsat8 OLI image [J].
Guo, Bing ;
Zang, Wenqian ;
Luo, Wei ;
Wen, Ye ;
Yang, Fei ;
Han, Baomin ;
Fan, Yewen ;
Chen, Xi ;
Qi, Zhen ;
Wang, Zhen ;
Chen, Shuting ;
Yang, Xiao .
GEOMATICS NATURAL HAZARDS & RISK, 2020, 11 (01) :288-300