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基于网格尺度的湟水河流域土地利用与生态系统服务价值空间自相关分析

Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale.

作者信息

Shi Feifei, Zhou Bingrong, Zhou Huakun, Zhang Hao, Li Hongda, Li Runxiang, Guo Zhuanzhuan, Gao Xiaohong

机构信息

School of Geographical Science, Qinghai Normal University, Xining 810008, China.

Institute of Qinghai Meteorological Science Research, Xining 810008, China.

出版信息

Plants (Basel). 2022 Sep 2;11(17):2294. doi: 10.3390/plants11172294.

Abstract

The Huangshui River Basin is one of the most densely populated areas on the Qinghai-Tibet Plateau and is characterized by a high level of human activity. The contradiction between ecological protection and socioeconomic development has become increasingly prominent; determining how to achieve the balanced and coordinated development of the Huangshui River Basin is an important task. Thus, this study used the Google Earth Engine (GEE) cloud-computing platform and Sentinel-1/2 data, supplemented with an ALOS digital elevation model (ALOS DEM) and field survey data, and combined a remote sensing classification method, grid method, and ecosystem service value (ESV) evaluation method to study the spatial correlation and interaction between land use (LU) and ESV in the Huangshui River Basin. The following results were obtained: (1) on the GEE platform, Sentinel-1/2 active and passive remote sensing data, combined with the gradient tree-boosting algorithm, can efficiently produce highly accurate LU data with a spatial resolution of 10 m in the Huangshui River Basin; the overall accuracy (OA) reached 88%. (2) The total ESV in the Huangshui River Basin in 2020 was CNY 33.18 billion (USD 4867.2 million), of which woodland and grassland were the main contributors to ESV. In the Huangshui River Basin, the LU type, LU degree, and ESV have significant positive spatial correlations, with urban and agricultural areas showing an H-H agglomeration in terms of LU degree, with woodlands, grasslands, reservoirs, and wetlands showing an H-H agglomeration in terms of ESV. (3) There is a significant negative spatial correlation between the LU degree and ESV in the Huangshui River Basin, indicating that the enhancement of the LU degree in the basin could have a negative spatial spillover effect on the ESV of surrounding areas. Thus, green development should be the future direction of progress in the Huangshui River Basin, i.e., while maintaining and expanding the land for ecological protection and restoration, and the LU structure should be actively adjusted to ensure ecological security and coordinated and sustainable socioeconomic development in the Basin.

摘要

湟水河流域是青藏高原人口最为密集的地区之一,人类活动程度高。生态保护与社会经济发展之间的矛盾日益突出,确定如何实现湟水河流域的平衡协调发展是一项重要任务。因此,本研究利用谷歌地球引擎(GEE)云计算平台和哨兵-1/2数据,辅以先进陆地观测卫星数字高程模型(ALOS DEM)和实地调查数据,并结合遥感分类方法、网格方法和生态系统服务价值(ESV)评估方法,研究湟水河流域土地利用(LU)与ESV之间的空间相关性和相互作用。得到以下结果:(1)在GEE平台上,哨兵-1/2主动和被动遥感数据结合梯度提升树算法,能够高效生成湟水河流域空间分辨率为10米的高精度LU数据;总体精度(OA)达到88%。(2)2020年湟水河流域ESV总量为331.8亿元人民币(48.672亿美元),其中林地和草地是ESV的主要贡献者。在湟水河流域,LU类型、LU程度和ESV具有显著的正空间相关性,城市和农业区域在LU程度方面呈现高-高集聚,林地、草地、水库和湿地在ESV方面呈现高-高集聚。(3)湟水河流域LU程度与ESV之间存在显著的负空间相关性,表明流域内LU程度的增强可能对周边地区的ESV产生负空间溢出效应。因此,绿色发展应是湟水河流域未来的发展方向,即在维持和扩大生态保护与修复用地的同时,应积极调整LU结构,以确保流域生态安全和社会经济协调可持续发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4491/9460333/8bb16b785754/plants-11-02294-g001.jpg

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