Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018

Xiaojing Zhang; Guoqiang Wang; Baolin Xue; Yinglan A

doi:10.1016/j.envres.2022.114253

Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018

Environ Res. 2022 Dec;215(Pt 1):114253. doi: 10.1016/j.envres.2022.114253. Epub 2022 Sep 5.

Authors

Xiaojing Zhang¹, Guoqiang Wang¹, Baolin Xue², Yinglan A³

Affiliations

¹ Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences, Beijing Normal University, Beijing, 100875, China.
² Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences, Beijing Normal University, Beijing, 100875, China. Electronic address: xuebl@bnu.edu.cn.
³ China Institute of Water Resources and Hydropower Research, Beijing, China.

PMID: 36067843
DOI: 10.1016/j.envres.2022.114253

Abstract

Vegetation cover is one of the primary indicators of changes in ecosystems. China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the Inner Mongolia Reach of the Yellow River Basin to prevent and control soil erosion. Although these programs have alleviated the environment problems in the region to a certain extent, the effects of the increasing vegetation greenness on the environments under climate change remain controversial for the argued large water consumption. In this study, the spatio-temporal characteristics of Normalized Difference Vegetation Index (NDVI) in the vegetation coverage area of the study area based on remote sensing data from 2001 to 2018. Meanwhile, using the Extreme Gradient Boosting (XGBoost) method - an excellent algorithm for ensemble learning methods - to forecast vegetation growth in the following ten years. The results indicated that, despite of the spatial heterogeneity, the vegetation NDVI exhibited a significant increase across the study area. Based on the NDVI trend, the area of improved vegetation in this region was much larger than the degraded area from 2001 to 2018, accounting for 85.9% and 8.6% of the total vegetation coverage area, respectively. However, the forecasting result by the Hurst index shows the future growth and carbon sequestration capacity in most areas showed a declining trend. Further, based on the Coupled Model Inter comparison Project - Phase 6 (CMIP6) data, the XGBoost method is used to predict the growth status and carbon sequestration capacity of vegetation in this area under different climate scenarios. The results showed that different climate scenarios had little effect on vegetation growth from 2019 to 2030. Results from this study may provide basis for the protection of ecological environment in the Inner Mongolia Reach of the Yellow River Basin.

Keywords: CMIP6; Inner Mongolia Reach of the yellow river basin; Spatio-temporal characteristics; Vegetation greenness; XGBoost method.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

China
Climate Change
Ecosystem*
Environmental Monitoring / methods
Rivers*