草原
植被(病理学)
环境科学
草地退化
自然地理学
土地覆盖
水文学(农业)
遥感
土地利用
生态学
地理
地质学
医学
岩土工程
病理
生物
作者
Yajun Zhou,Okke Batelaan,Huade Guan,Tingxi Liu,Limin Duan,Yixuan Wang,Xia Li
标识
DOI:10.1016/j.jenvman.2023.119579
摘要
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.
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