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首页> 外文期刊>International journal of applied mechanics >Driving Factors of Land Change in China's Loess Plateau: Quantification Using Geographically Weighted Regression and Management Implications
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Driving Factors of Land Change in China's Loess Plateau: Quantification Using Geographically Weighted Regression and Management Implications

机译:中国黄土高原土地变化的推动因素:使用地理加权回归和管理影响量化

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摘要

Land change is a key topic in research on global environmental change, and the restoration of degraded land is the core component of the global Land Degradation Neutrality target under the UN 2030 Agenda for Sustainable Development. In this study, remote-sensing-derived land-use data were used to characterize the land-change processes in China's Loess Plateau, which is experiencing large-scale ecological restoration. Geographically Weighted Regression was applied to capture the spatiotemporal variations in land change and driving-force relationships. First, we explored land-use change in the Loess Plateau for the period 1990-2015. Grassland, cropland and forestland were dominant land cover in the region, with a total percentage area of 88%. The region experienced dramatic land-use transitions during the study period: degraded grassland and wetland, expansion of cropland and built-up land and weak restoration of forestland during 1990-2000; and increases in grassland, built-up land, forestland and wetland, concurrent with shrinking cropland during 2000-2015. A Geographically Weighted Regression (GWR) analysis revealed altitude to be the common dominant factor associated with the four major land-use types (forestland, grassland, cropland and built-up land). Altitude and slope were found to be positively associated with forestland, while being negatively associated with cropland in the high, steep central region. For both forestland and grassland, temperature and precipitation behaved in a similar manner, with a positive hotspot in the northwest. Altitude, slope and distance to road were all negatively associated with built-up land across the region. The GWR captured the spatial non-stationarity on different socioeconomic driving forces. Spatial heterogeneity and temporal variation of the impact of socioeconomic drivers indicate that the ecological restoration projects positively affected the region's greening trend with hotspots in the center and west, and also improved farmer well-being. Notably, urban population showed undesired effects, expressed in accelerating grassland degradation in central and western regions for 1990-2000, hindering forestland and grassland restoration in the south during 2000-2015, and highlighting the long-term sustainability of the vegetation restoration progress. Such local results have the potential to provide a methodological contribution (e.g., nesting local-level approaches, i.e., GWR, within land system research) and spatially explicit evidence for context-related and proactive land management (e.g., balancing urbanization and ecological restoration processes and advancing agricultural development and rural welfare improvement).
机译:土地变革是全球环境变革研究的关键话题,恢复退化的土地是根据“可持续发展的”联合国公约“议程下全球土地退化中立目标的核心组成部分。在这项研究中,遥感衍生的土地利用数据用于表征中国黄土高原的土地变化过程,这正在经历大规模的生态恢复。适用地理加权回归来捕获土地变化和驱动力关系的时空变化。首先,我们探讨了1990 - 2015年黄土高原的土地使用变化。草原,农田和林地是该地区的主要陆地覆盖,总百分比面积为88%。该地区在研究期间经历了戏剧性的土地使用过渡:退化草地和湿地,在1990 - 2000年期间扩大农田和建筑造成土地和较弱的造林;并增加了草原,建筑的土地,林地和湿地,2000 - 2015年期间与萎缩的农田同时发生。地理加权回归(GWR)分析显示了高度,是与四种主要土地使用类型(林地,草原,农田和建筑陆地)相关的共同主导因素。发现高度和坡度与林地正相关,同时与高陡峭的中央区域的农作物负相关。对于林地和草地,温度和降水量以类似的方式表现出色,西北部有一个正热点。海拔高度,坡度和距离的距离都与整个地区的建筑焊盘负相关。 GWR在不同的社会经济驱动力上捕获了空间非公平性。社会经济司机影响的空间异质性和时间变化表明,生态修复项目积极影响该地区的绿化趋势与中心和西部的热点,也有改善农民福祉。值得注意的是,城市人口表现出不希望的影响,在2000 - 2015年期间妨碍南部的森林和西部地区的草地和西部地区的草地退化表达,并突出了植被恢复进展的长期可持续性。这种局部结果具有提供方法论贡献(例如,嵌套本地级别方法,即GWR,土地系统研究中的GWR,在土地系统研究中)以及与上下文相关和主动土地管理的空间明确证据(例如,平衡城市化和生态恢复过程并推进农业发展和农村福利改善)。

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