Vegetation changes and influencing factors in different watersheds of Henan Province based on GEE and geographic detectors.

Q3 Environmental Science 应用生态学报 Pub Date : 2024-07-18 DOI:10.13287/j.1001-9332.202407.021
Xia Li, Le-Yi Zhang, Chen Wu
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Abstract

Clarifying vegetation changes and the driving factors can provide references for ecological restoration and sustainable social development. We analyzed vegetation distribution and trend changes in Henan Province and its basin zoning (Haihe River basin zoning, Yellow River basin zoning, Huaihe River basin zoning, Yangtze River basin zoning), with fractional vegetation cover data from 2000 to 2020 based on the Google Earth Engine platform, and by combining Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index. We also utilized factor detection and factor interaction to explore the individual and mutual influences of natural and anthropogenic factors on vegetation at different scales. The results showed that the fractional vegetation cover (FVC) in Henan Province exhibited a distribution pattern of higher coverage in the south and lower in the north during the study period, predominantly characterized by moderate to high vegetation coverage. The Yangtze River basin zoning had the highest coverage. FVC in Henan Province and its zoning exhibited a consistent pattern of fluctuating upward trends, with all areas showing significant improvement. Particularly, the Yangtze River basin zoning had the largest area of improvement. According to the Hurst index, apart from the possibility of continued improvement in the Huaihe River basin zoning, other zoning would be likely to shift from improvement to degradation in the future. Vegetation changes in Henan Province and its zoning were the result of combined effects of anthropogenic and natural factors, with the influence of these factors changing over time and the dominant factors varying by region. Anthropogenic factors such as land use/cover type and nighttime lighting had a stronger impact on vegetation than natural factors like elevation, slope, and annual mean low temperature. The interaction between factors, particularly between anthropogenic and natural factors, exhibited a nonlinear enhancing pattern.

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基于 GEE 和地理探测器的河南省不同流域植被变化及其影响因素。
明确植被变化及其驱动因素可为生态恢复和社会可持续发展提供参考。我们基于谷歌地球引擎平台,利用2000-2020年的植被分指数数据,结合Theil-Sen中值趋势分析、Mann-Kendall检验和Hurst指数,分析了河南省及其流域分区(海河流域分区、黄河流域分区、淮河流域分区、长江流域分区)的植被分布及其变化趋势。我们还利用因子检测和因子交互作用,探讨了自然和人为因子在不同尺度上对植被的单独和相互影响。结果表明,在研究期间,河南省的植被分覆盖度(FVC)呈现出南高北低的分布格局,以中高植被覆盖度为主。长江流域分区的植被覆盖率最高。河南省的森林覆盖率及其分区呈现出波动上升的一致格局,所有地区都有显著改善。其中,长江流域分区的改善面积最大。根据赫斯特指数,除了淮河流域分区有可能继续改善外,其他分区未来都有可能由改善转为退化。河南省的植被变化及其分区是人为因素和自然因素共同作用的结果,这些因素的影响随时间的推移而变化,主导因素也因地区而异。与海拔、坡度和年平均低温等自然因素相比,土地利用/覆盖类型和夜间光照等人为因素对植被的影响更大。各种因素之间的相互作用,特别是人为因素与自然因素之间的相互作用,呈现出非线性增强模式。
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来源期刊
应用生态学报
应用生态学报 Environmental Science-Ecology
CiteScore
2.50
自引率
0.00%
发文量
11393
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