Spatio-Temporal Variation and Climatic Driving Factors of Vegetation Coverage in the Yellow River Basin from 2001 to 2020 Based on kNDVI

被引:42
作者
Feng, Xuejuan [1 ]
Tian, Jia [1 ]
Wang, Yingxuan [1 ]
Wu, Jingjing [1 ]
Liu, Jie [1 ]
Ya, Qian [1 ]
Li, Zishuo [1 ]
机构
[1] Ningxia Univ, Sch Agr, Yinchuan 750021, Peoples R China
基金
中国国家自然科学基金;
关键词
kNDVI (kernel normalized difference vegetation index); vegetation coverage; spatial-temporal change; driving factors; Yellow River basin; LOESS PLATEAU; VARIABILITY; TRENDS;
D O I
10.3390/f14030620
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The Yellow River Basin (YRB) is a fundamental ecological barrier in China and is one of the regions where the ecological environment is relatively fragile. Studying the spatio-temporal variations in vegetation coverage in the YRB and their driving factors through a long-time-series vegetation dataset is of great significance to eco-environmental construction and sustainable development in the YRB. In this study, we sought to characterize the spatio-temporal variation in vegetation coverage and its climatic driving factors in the YRB from 2001 to 2020 by constructing a new kernel normalized difference vegetation index (kNDVI) dataset based on MOD13 A1 V6 data from the Google Earth Engine (GEE) platform. Using Theil-Sen median trend analysis, the Mann-Kendall test, and the Hurst exponent, we investigated the spatio-temporal variation characteristics and future development trends of the vegetation coverage. The climatic driving factors of vegetation coverage in the YRB were obtained via partial correlation analysis and complex correlation analysis of the associations between kNDVI and both temperature and precipitation. The results reveal the following: The spatial distribution pattern of kNDVI in the YRB showed that vegetation coverage was high in the southeast and low in the northwest. Vegetation coverage fluctuated from 2001 to 2020, with a main significant trend of increasing growth at a rate of 0.0995/5a. The response of vegetation to climatic factors was strong in the YRB, with a stronger response to precipitation than to temperature. Additionally, the main driving factors of vegetation coverage in the YRB were found to be non-climatic factors, which were mainly distributed in Henan, southern Shaanxi, Shanxi, western Inner Mongolia, Ningxia, and eastern Gansu. The areas driven by climatic factors were mainly distributed in northern Shaanxi, Shandong, Qinghai, western Gansu, northeastern Inner Mongolia, and Sichuan. Our findings have implications for ecosystem restoration and sustainable development in the YRB.
引用
收藏
页数:17
相关论文
共 66 条
[1]  
Alam S.S., 2020, ECOL INDIC, V121, P107124
[2]   Mapping Three Decades of Changes in the Brazilian Savanna Native Vegetation Using Landsat Data Processed in the Google Earth Engine Platform [J].
Alencar, Ane ;
Shimbo, Julia Z. ;
Lenti, Felipe ;
Marques, Camila Balzani ;
Zimbres, Barbara ;
Rosa, Marcos ;
Arruda, Vera ;
Castro, Isabel ;
Fernandes Marcico Ribeiro, Joao Paulo ;
Varela, Victoria ;
Alencar, Isa ;
Piontekowski, Valderli ;
Ribeiro, Vivian ;
Bustamante, Mercedes M. C. ;
Sano, Edson Eyji ;
Barroso, Mario .
REMOTE SENSING, 2020, 12 (06)
[3]   A unified vegetation index for quantifying the terrestrial biosphere [J].
Camps-Valls, Gustau ;
Campos-Taberner, Manuel ;
Moreno-Martinez, Alvaro ;
Walther, Sophia ;
Duveiller, Gregory ;
Cescatti, Alessandro ;
Mahecha, Miguel D. ;
Munoz-Mari, Jordi ;
Javier Garcia-Haro, Francisco ;
Guanter, Luis ;
Jung, Martin ;
Gamon, John A. ;
Reichstein, Markus ;
Running, Steven W. .
SCIENCE ADVANCES, 2021, 7 (09)
[4]   Spatiotemporal Variation of Vegetation Net Primary Productivity and Its Responses to Climate Change in the Huainan Coal Mining Area [J].
Chen, Guangzhou ;
Huang, Yong ;
Chen, Jun ;
Wang, Yongfeng .
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2019, 47 (11) :1905-1916
[5]   The Study of Vegetation Carbon Storage in Qinghai Lake Valley Based on Remote Sensing and CASA Model [J].
Chen Kelong ;
Han Yanli ;
Cao Shengkui ;
Ma Jin ;
Cao Guangchao ;
Lu Hui .
2011 3RD INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY ESIAT 2011, VOL 10, PT B, 2011, 10 :1568-1574
[6]   Spatiotemporal Variation and Influence Factors of Vegetation Cover in the Yellow River Basin (1982-2021) Based on GIMMS NDVI and MOD13A1 [J].
Cheng, Yi ;
Zhang, Lijuan ;
Zhang, Zhiqiang ;
Li, Xueyin ;
Wang, Haiying ;
Xi, Xu .
WATER, 2022, 14 (20)
[7]   Study on Spatiotemporal Variation Pattern of Vegetation Coverage on Qinghai-Tibet Plateau and the Analysis of Its Climate Driving Factors [J].
Deng, Xiaoyu ;
Wu, Liangxu ;
He, Chengjin ;
Shao, Huaiyong .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (14)
[8]   Global trends analysis of the main vegetation types throughout the past four decades [J].
Faour, Ghaleb ;
Mhawej, Mario ;
Nasrallah, Ali .
APPLIED GEOGRAPHY, 2018, 97 :184-195
[9]   Greenness in semi-arid areas across the globe 1981-2007 - an Earth Observing Satellite based analysis of trends and drivers [J].
Fensholt, Rasmus ;
Langanke, Tobias ;
Rasmussen, Kjeld ;
Reenberg, Anette ;
Prince, Stephen D. ;
Tucker, Compton ;
Scholes, Robert J. ;
Le, Quang Bao ;
Bondeau, Alberte ;
Eastman, Ron ;
Epstein, Howard ;
Gaughan, Andrea E. ;
Hellden, Ulf ;
Mbow, Cheikh ;
Olsson, Lennart ;
Paruelo, Jose ;
Schweitzer, Christian ;
Seaquist, Jonathan ;
Wessels, Konrad .
REMOTE SENSING OF ENVIRONMENT, 2012, 121 :144-158
[10]   Influence of topography on some vegetation cover properties [J].
Florinsky, IV ;
Kuryakova, GA .
CATENA, 1996, 27 (02) :123-141