2022
DOI: 10.3390/agronomy12071697
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Examining the Driving Factors of SOM Using a Multi-Scale GWR Model Augmented by Geo-Detector and GWPCA Analysis

Abstract: A model incorporating geo-detector analysis and geographically weighted principal component analysis into Multi-scale Geographically Weighted regression (GWPCA-MGWR) was developed to reveal the factors driving spatial variation in soil organic matter (SOM). The regression accuracy and residuals from GWPCA-MGWR were compared to those of the classical Geographically Weighted regression (GWR), Multi-scale Geographically Weighted regression (MGWR), and GWPCA-GWR. Our results revealed that local multi-collinearity … Show more

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Cited by 9 publications
(3 citation statements)
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“…Spatial heterogeneity has gained widespread application in the domain of spatial relationship analysis, including in areas such as urban public health [51], housing prices and the built environment [52], social equity [53], and soil environmental analysis [54]. In the context of urban vitality analysis, research typically centers on urban landscapes, streets, or morphologies [55,56].…”
Section: Spatial Heterogeneitymentioning
confidence: 99%
“…Spatial heterogeneity has gained widespread application in the domain of spatial relationship analysis, including in areas such as urban public health [51], housing prices and the built environment [52], social equity [53], and soil environmental analysis [54]. In the context of urban vitality analysis, research typically centers on urban landscapes, streets, or morphologies [55,56].…”
Section: Spatial Heterogeneitymentioning
confidence: 99%
“…(2) Evaluations of the driving factors Geo-detector serves to identify spatial variations in geographic phenomena and uncover the underlying drivers behind them [46]. The method consists of four parts: risk detection, factor detection, ecological detection, and interaction detection.…”
Section: Evaluations Of the Driving Factors Of Estss (1) Selection Of...mentioning
confidence: 99%
“…It facilitates the exploration of yellowfin tuna catch responses to environmental changes across multiple spatial scales, enabling more precise analyses and evaluations. Both models have garnered attention in fields such as soil science [27,28], economics [29,30], sociology [31,32], agriculture [33,34], and others. Their efficacy in examining heterogeneity across spatial scales and analyzing response patterns is well established.…”
Section: Introductionmentioning
confidence: 99%