[1]聂普璇,方圣辉,龚龑,等.基于GWR模型的河北省土壤水分空间分异研究[J].水土保持研究,2019,26(01):98-105.
　NIE Puxuan,FANG Shenghui,GONG Yan,et al.Research on Spatial Variation of Soil Moisture in Hebei Province Based on GWR Model[J].Research of Soil and Water Conservation,2019,26(01):98-105.
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基于GWR模型的河北省土壤水分空间分异研究

《水土保持研究》[ISSN:1005-3409/CN:61-1272/P] 卷: 26 期数: 2019年01期 页码: 98-105 栏目: 出版日期: 2019-02-28
Title:
Research on Spatial Variation of Soil Moisture in Hebei Province Based on GWR Model
作者:
聂普璇1, 方圣辉1, 龚龑1, 刘进2
1. 武汉大学 遥感信息工程学院, 武汉 430079;
2. 北京师范大学 地理科学学部, 北京 100875
Author(s):
NIE Puxuan1, FANG Shenghui1, GONG Yan1, LIU Jin2
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
关键词:
土壤水分; 影响因子; GWR模型; 空间异质; 河北省
Keywords:
soil moisture; influencing factors; geographically weighted regression model (GWR); spatial variation; Hebei Province
分类号:
S152.7
摘要:
为研究环境因素对土壤水分空间分异的影响，利用2013-2017年SMOS Level-3土壤水分数据，选取降水、DEM、坡度、植被、地表温度为影响土壤水分的环境因子，对河北省土壤水分进行了空间自相关分析，建立了河北省土壤含水量与影响因子之间的地理加权模型，将GWR模型与一般线性回归模型对比，分析了影响因子在空间上对土壤水分作用的异质特征。结果表明：河北省土壤含水量具有空间异质性，集聚特征明显。GWR模型的拟合效果在拟合优度和空间分布上都远远优于OLS模型。GWR模型的拟合优度R2比OLS模型提高了43%，GWR模型对土壤水分影响因子的解释能力比OLS模型提高了34.6%，GWR模型的残差平方和、AIC值均远远小于OLS模型。研究区影响因子对土壤水分的作用参数具有空间分异特征，影响因子的作用程度也不同，DEM影响最大，其次是坡度、地表温度、降水、NDVI。各因子在空间上对土壤水分既有负向又有局部正向的作用，但在大部分范围里都呈负向影响。研究成果对研究区的精准农业发展、水土保持利用和生态建设具有重要意义。
Abstract:
In order to study the influence of environmental factors on the spatial differentiation of soil moisture in Hebei Province, SMOS Level-3 soil moisture data from 2013 to 2017 were used to select precipitation, DEM, slope, vegetation, and land surface temperature as environmental factors affecting soil moisture. Spatial autocorrelation analysis of soil moisture in Hebei Province was conducted to establish the geographically weighted regression model between soil moisture contents and impact factors. The GWR model was compared with the general linear regression model to analyze the heterogeneity of the effect of the influencing factors on soil moisture in space. The results showed that the soil moisture in Hebei Province had spatial heterogeneity and obvious agglomeration characteristics. The fitting effect of GWR model was far better than the OLS model in terms of fitting goodness and spatial distribution. The fitting goodness (R2) of the GWR model was 43% higher than that of the OLS model. The ability of the GWR model to explain the soil moisture impact factor was 34.6% higher than that of the OLS model. The residual square sum and AIC value of the GWR model were much smaller than those of OLS model. The effect parameters of the impact factors on soil moisture in the study area had spatial differentiation characteristics, and the degrees of influence of the influence factors were also different with DEM having the greatest impact followed by slope gradient, land surface temperature, precipitation, and NDVI. Each factor had both negative and positive effects on soil moisture in space, but it had the negative effect in most areas. The research results are of great significance to the development of precision agriculture, soil and water conservation, resource utilization, and ecological construction in the study area.

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备注/Memo

收稿日期:2018-6-22;改回日期:2018-7-3。
基金项目:民用航天技术预先研究项目（Y7K00100KJ）
作者简介:聂普璇(1995-),女,河北邢台人,在读硕士研究生,主要从事土壤水分研究。E-mail:puxuannie@whu.edu.cn
通讯作者:方圣辉(1964-),男,安徽巢湖人,博导,教授,主要从事定量遥感等研究。E-mail:shfang@whu.edu.cn

更新日期/Last Update: 1900-01-01