GWmodelS: a standalone software to train geographically weighted models

被引:1
作者
Lu, Binbin [1 ]
Hu, Yigong [2 ]
Yang, Dongyang [3 ]
Liu, Yong [3 ]
Ou, Guangyu [1 ]
Harris, Paul [4 ]
Brunsdon, Chris [5 ]
Comber, Alexis [6 ]
Dong, Guanpeng [3 ,7 ,8 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan, Peoples R China
[2] Univ Bristol, Sch Geog Sci, Bristol, England
[3] Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng, Peoples R China
[4] Rothamsted Res, Net Zero & Resilient Farming, North Wyke, England
[5] Maynooth Univ, Natl Ctr Geocomputat, Maynooth, Ireland
[6] Univ Leeds, Sch Geog, Leeds, England
[7] Henan Univ, Collaborat Innovat Ctr Yellow River Civilizat Join, Minist Educ, Kaifeng, Peoples R China
[8] Minist Educ, Key Lab Geospatial Technol Middle & Lower Yellow R, Kaifeng, Peoples R China
关键词
Spatial heterogeneity; spatial non-stationarity; visualization; high-performance; local techniques; SPATIAL HETEROGENEITY; MULTILEVEL MODELS; EXPANSION METHOD; REGRESSION; GROWTH;
D O I
10.1080/10095020.2024.2343011
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
With the recent increase in studies on spatial heterogeneity, geographically weighted (GW) models have become an essential set of local techniques, attracting a wide range of users from different domains. In this study, we demonstrate a newly developed standalone GW software, GWmodelS using a community-level house price data set for Wuhan, China. In detail, a number of fundamental GW models are illustrated, including GW descriptive statistics, basic and multiscale GW regression, and GW principle component analysis. Additionally, functionality in spatial data management and batch mapping are presented as essential supplementary activities for GW modeling. The software provides significant advantages in terms of a user-friendly graphical user interface, operational efficiency, and accessibility, which facilitate its usage for users from a wide range of domains.
引用
收藏
页码:648 / 670
页数:23
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