Driving Mechanism of the Spatiotemporal Evolution of Vegetation in the Yellow River Basin from 2000 to 2020

被引:0
|
作者
Tian Z.-H. [1 ,2 ]
Ren Z.-G. [3 ]
Wei H.-T. [1 ,2 ]
机构
[1] School of Earth Sciences and Technology, Zhengzhou University, Zhengzhou
[2] Joint Laboratory of Eco-Meteorology, Zhengzhou University-Chinese Academy of Meteorological Sciences, Zhengzhou
[3] College of Chemistry, Zhengzhou University, Zhengzhou
来源
Huanjing Kexue/Environmental Science | 2022年 / 43卷 / 02期
基金
美国国家科学基金会;
关键词
Climate change; Human activities; Normalized difference vegetation index (NDVI); Residuals analysis; Yellow River basin;
D O I
10.13227/j.hjkx.202105213
中图分类号
学科分类号
摘要
The NDVI (normalized difference vegetation index) was used as the vegetation coverage index. Based on the NDVI and weather data from 2000 to 2020, the characteristics of the spatiotemporal evolution and the driving mechanism of vegetation were investigated by using correlation analysis, the Theil-Sen estimator, the Mann-Kendall method, and multivariate residual trend analysis. The results showed that the growing season average NDVI in the Yellow River basin was a fluctuating upward trend of 0.005 a-1 from 2000 to 2020. Areas with significantly improved vegetation in the basin were mainly distributed in the Qinling Mountains, the Northern Shaanxi Plateau, and the Lvliang Mountains in the midstream. The average value of the partial correlation coefficient between the growing season average NDVI and rainfall in the Yellow River basin was 0.57, and the average value of the partial correlation coefficient between the growing season average NDVI and temperature was 0.49. The impact of rainfall on vegetation was higher than that of temperature. The areas where human activities significantly improved vegetation growth were mainly distributed in the northern Shaanxi Plateau, the Lvliang Mountains, and southern Ningxia. The areas where human activities inhibited vegetation growth were mainly distributed in cities with strong human activities such as Yinchuan, Baotou, Xi'an, Luoyang, Zhengzhou, and Taiyuan. Human activities and climate change contributed to 72% and 28% of the vegetation change in the Yellow River basin. Driven by human activities and climate change, the area where vegetation growth has improved in the Yellow River basin accounted for 96.4% of the basin area, of which the contribution rate of human activities greater than 80% of the area accounted for 34.3%, which was mainly distributed in the middle and southeast of the basin. The area with a contribution rate of climate change greater than 80% accounted for 4.2%, which was mainly distributed in the Sichuan-Tibet Plateau and Longzhong Loess Plateau in the basin. The results of this research can provide scientific support for the ecological protection and high-quality development of the Yellow River basin. © 2022, Science Press. All right reserved.
引用
收藏
页码:743 / 751
页数:8
相关论文
共 37 条
  • [1] Pearson R G, Phillips S J, Loranty M M, Et al., Shifts in arctic vegetation and associated feedbacks under climate change, Nature Climate Change, 3, 7, pp. 673-677, (2013)
  • [2] Kong D D, Zhang Q, Singh V P, Et al., Seasonal vegetation response to climate change in the Northern Hemisphere (1982- 2013), Global and Planetary Change, 148, pp. 1-8, (2017)
  • [3] Gillespie T W, Madson A, Cusack C F, Et al., Changes in NDVI and human population in protected areas on the Tibetan Plateau, Arctic, Antarctic, and Alpine Research, 51, 1, pp. 428-439, (2019)
  • [4] Hao F H, Zhang X, Ouyang W, Et al., Vegetation NDVI linked to temperature and precipitation in the upper catchments of Yellow River, Environmental Modeling & Assessment, 17, 4, pp. 389-398, (2012)
  • [5] Xu Y F, Yang J, Chen Y N., NDVI-based vegetation responses to climate change in an arid area of China, Theoretical and Applied Climatology, 126, 1- 2, pp. 213-222, (2016)
  • [6] Tarnavsky E, Garrigues S, Brown M E., Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products, Remote Sensing of Environment, 112, 2, pp. 535-549, (2008)
  • [7] Bai Y Q, Yang Y P, Jiang H., Intercomparison of AVHRR GIMMS3g, Terra MODIS, and SPOT-VGT NDVI products over the Mongolian Plateau, Remote Sensing, 11, 17, (2019)
  • [8] Fensholt R, Proud S R., Evaluation of earth observation based global long term vegetation trends - Comparing GIMMS and MODIS global NDVI time series, Remote Sensing of Environment, 119, pp. 131-147, (2012)
  • [9] Zewdie W, Csaplovics E, Inostroza L., Monitoring ecosystem dynamics in northwestern Ethiopia using NDVI and climate variables to assess long term trends in dryland vegetation variability, Applied Geography, 79, pp. 167-178, (2017)
  • [10] Emamian A, Rashki A, Kaskaoutis D G, Et al., Assessing vegetation restoration potential under different land uses and climatic classes in northeast Iran, Ecological Indicators, 122, (2021)