Assessing long-term trends in vegetation cover change in the Xilin River Basin: Potential for monitoring grassland degradation and restoration

Yajun Zhou; Okke Batelaan; Huade Guan; Tingxi Liu; Limin Duan; Yixuan Wang; Xia Li

doi:10.1016/j.jenvman.2023.119579

Assessing long-term trends in vegetation cover change in the Xilin River Basin: Potential for monitoring grassland degradation and restoration

J Environ Manage. 2024 Jan 1:349:119579. doi: 10.1016/j.jenvman.2023.119579. Epub 2023 Nov 15.

Authors

Yajun Zhou¹, Okke Batelaan², Huade Guan², Tingxi Liu³, Limin Duan⁴, Yixuan Wang⁴, Xia Li¹

Affiliations

¹ Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot, 010018, China; Inner Mongolia Key Laboratory of Protection and Utilization of Water Resources, Hohhot, 010018, China; Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River, Hohhot, 010018, China; College of Science & Engineering, National Centre for Groundwater Research and Training, Flinders University, Adelaide, South Australia, Australia.
² College of Science & Engineering, National Centre for Groundwater Research and Training, Flinders University, Adelaide, South Australia, Australia.
³ Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot, 010018, China; Inner Mongolia Key Laboratory of Protection and Utilization of Water Resources, Hohhot, 010018, China; Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River, Hohhot, 010018, China. Electronic address: txliu@imau.edu.cn.
⁴ Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot, 010018, China; Inner Mongolia Key Laboratory of Protection and Utilization of Water Resources, Hohhot, 010018, China; Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River, Hohhot, 010018, China.

PMID: 37976643
DOI: 10.1016/j.jenvman.2023.119579

Abstract

Under the influence of climate change and human activities, the problem of grassland degradation is becoming increasingly severe. Detection of changes in vegetation cover is crucial for a better understanding of the interaction between humans and ecosystems. This study maps changes in vegetation cover using the Google Earth Engine (GEE). We used 36 years of Landsat satellite imagery (1985-2020) in the Xilin River Basin, China, to classify grassland conditions and validated the results with field observation data. The overall classification of the model accuracy assessment was 83.3%. The Dynamic Reference Vegetation Cover Method (DRCM) was adopted to remove the effect of interannual variation of rainfall, allowing to focus on the impact of human activities on vegetation cover changes. The results identify five categories of vegetation cover changes: significantly increased, potentially increased, stable, potentially decreased, and significantly decreased. The reference level is derived from the most persistent land surface coverage across different grassland types and all years. Overall, 9.3% of the study area had a significant increase in vegetation cover, 14.2% a potential increase, 48.6% of the area showed a stable vegetation condition, 9.8% showed a potential decrease, and 18.1% a significant decrease in vegetation cover. The largest proportion of combined potential and significant reduction was 35.2% for desert grassland, where the vegetation faced the most severe reduction. This study will provide a basis for identifying grassland degradation and developing scientific management policies.

Keywords: Drought index; Google earth engine; Landsat; Vegetation coverage; Xilin river basin.

MeSH terms

China
Climate Change
Ecosystem*
Environmental Monitoring / methods
Grassland*
Humans
Rivers
Satellite Imagery