摘要
本文基于Google Earth Engine(GEE)这一全球地理信息云平台,利用其高效的数据获取和处理能力,对1990—2024年六盘山区的植被覆盖度时空演变特征进行了探究。以Landsat系列卫星影像为基础,采用像元二分模型、趋势分析、Hurst指数等方法,探讨了植被覆盖时空变化特征以及未来变化预测。此外,结合地理因子探测器对影响植被覆盖度的主要地理因子进行了深入解析。结果表明:①植被覆盖度空间分布呈现东南向西北高-中-低-高的格局,不同土地利用类型的植被覆盖度差异显著;②植被覆盖度在35 a间总体呈波动上升趋势,平均值为0.3577,增速为0.0012/a,低覆盖度区域减少15270.54 km^(2),高覆盖度区域增加3969.71 km^(2);③植被覆盖度趋势分析显示不显著增加区域占比40.71%,不显著减少区域占比27.93%;结合Hurst指数分析显示未来3~5 a内植被覆盖度呈减少趋势区域占比60.99%,呈增加趋势区域占比38.86%;④降水是影响植被覆盖度的主要地理因子,解释力为0.634;各因子交互作用对植被覆盖度的解释力均高于单因子,其中降水与气温的交互作用解释力最强为0.752。
This study investigates the spatiotemporal evolution of vegetation coverage in the Liupan Mountain area from 1990 to 2024,based on the Google Earth Engine(GEE)global geospatial cloud platform.Utilizing GEE’s efficient data acquisition and processing capabilities,the research employs methods such as the Pixel Binary Model,trend analysis,and the Hurst index to explore the spatiotemporal changes in vegetation coverage and predict future trends.Furthermore,the study conducts an in-depth analysis of the primary geographic factors influencing vegetation coverage,using the Geographic Detector.The results show that:1)The spatial distribution of vegetation coverage follows a high-medium-low-high pattern from southeast to northwest,with significant differences in vegetation coverage across different land use types;2)Over the 35-year period,vegetation coverage generally showed a fluctuating upward trend,with an average value of 0.3577 and a growth rate of 0.0012/a.Low-coverage areas decreased by 15270.54 km^(2),while high-coverage areas increased by 3969.71 km^(2);3)Trend analysis of vegetation coverage reveals 40.71% of the area without significant increase,and 27.93% without significant decrease.Combining the Hurst index analysis,it is predicted that in the next 3-5 years,60.99% of the area will experience a decreasing trend in vegetation coverage,while 38.86% will show an increasing trend;4)Precipitation is the primary geographic factor influencing vegetation coverage,with an explanatory power of 0.634.The interaction between factors has a higher explanatory power than individual factors,with the interaction between precipitation and temperature having the strongest explanatory power of 0.752.These findings provide insights into the spatio-temporal changes of vegetation coverage in the Liupan Mountain area and its driving factors,offering valuable reference for ecological protection in the region.
作者
王拓
杨贵军
徐新刚
冯海宽
董立国
张静
刘淼
唐澳华
吴强
Wang Tuo;Yang Guijun;Xu Xingang;Feng Haikuan;Dong Liguo;Zhang Jing;Liu Miao;Tang Aohua;Wu Qiang(School of Geology Engineering and Surveying,Chang’an University,Xi’an 710054,Shaanxi,China;Key Laboratory of Agricultural Remote Sensing Mechanisms and Quantitative Remote Sensing,Ministry of Agriculture and Rural Affairs,Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;Forestry and Grassland Ecology Research Institute,Ningxia Academy of Agriculture and Forestry Sciences,Forestry Ecology Research Room,Yinchuan 750013,Ningxia,China)
出处
《地理科学》
北大核心
2025年第8期1684-1697,共14页
Geographical Science
基金
宁夏回族自治区重点研发计划项目(2023BEG02050)资助。
