藏北高原砾石粒径空间异质性研究
收稿日期: 2022-07-09
修回日期: 2022-11-27
网络出版日期: 2023-03-08
基金资助
国家自然科学基金项目(41971226);国家自然科学基金项目(41871357);中国科学院战略性先导科技专项(XDA19030303);中国科学院战略性先导科技专项(XDA28110503);国家重点基础研究发展规划项目:矿山环境地质灾害协同监测预警技术与装备(2017YFC1503103)
Spatial heterogeneity of gravel size in Northern Tibetan Plateau
Received date: 2022-07-09
Revised date: 2022-11-27
Online published: 2023-03-08
砾石是各种水文和侵蚀等过程综合作用的产物,是草地和土壤退化、生态系统恶化的一个标志,反过来这些砾石也影响到侵蚀的各个过程。研究藏北高原地表砾石的空间分异对区域生态环境恢复具有重要意义。本文以地表砾石粒径大小和空间位置为研究对象,通过Moran’s I指数、空间变异函数、地理探测器、回归分析等方法对其空间异质性进行系统性分析。结果表明:(1) 全局Moran’s I指数值为0.481,呈显著的正相关,局部Moran’s I指数显示,研究区东部砾石聚集模式为高-高聚集,中部为低-低聚集,其余区域多呈随机分布。(2) 砾石空间异质性由结构因素主导,但是变异函数最佳拟合模型与特征参数值均存在一定差异性,即存在一定的各向异性特征。(3) 地理探测器结果显示,NDVI、土地利用类型为影响研究区砾石粒径空间异质性的主要因素,人口密度、植被类型、年均降水为次要因素。(4) 回归分析结果显示,最优尺度回归为最佳回归模型,NDVI对砾石粒径影响最大,其后依次为土地利用类型、年均降水、植被类型。
徐涛 , 于欢 , 孔博 , 邱霞 , 胡孟珂 , 凌鹏飞 . 藏北高原砾石粒径空间异质性研究[J]. 干旱区研究, 2023 , 40(2) : 292 -302 . DOI: 10.13866/j.azr.2023.02.13
Gravel is the product of various hydrological and erosion processes and is a symbol of grassland and soil degradation and ecosystem deterioration. Consequently, gravel also affects various erosion processes. Studying the spatial differentiation of gravel in the Northern Tibetan Plateau is of considerable importance for the restoration of regional ecological environments. In this paper, the size and spatial location of surface gravel were studied, and the spatial heterogeneity was systematically analyzed by Moran’s I index, spatial variogram, geographic detector, and regression analysis. The following results are presented. (1) The global Moran’s I index is 0.481, which shows a significant positive correlation. Meanwhile, the local Moran’s I index shows a high-high gravel accumulation pattern in the eastern part of the study area, low-low in the middle part, and mostly random distribution in the rest of the study area. (2) Gravel spatial heterogeneity is dominated by structural factors. However, some differences are found between the best fitting model of the variogram and the values of characteristic parameters; that is, certain anisotropy characteristics exist. (3) The geographic detector results showed that NDVI and land-use type were the main factors affecting the spatial heterogeneity of gravel size in the study area, while population density, vegetation type, and annual average precipitation were the secondary factors. (4) The results of regression analysis revealed that the optimal scale regression was the best regression model, and NDVI had the largest influence on gravel size, followed by land-use type, annual mean precipitation, and vegetation type.
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