GWmodelS: A software for geographically weighted models
Binbin Lu,
Yigong Hu,
Dongyang Yang,
Yong Liu,
Liuqi Liao,
Zuoyao Yin,
Tianyang Xia,
Zheyi Dong,
Paul Harris,
Chris Brunsdon,
Lex Comber,
Guanpeng Dong
Affiliations
Binbin Lu
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Yigong Hu
School of Geographical Sciences, University of Bristol, Bristol, UK
Dongyang Yang
Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng, 475001, China
Yong Liu
Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng, 475001, China
Liuqi Liao
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Zuoyao Yin
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Tianyang Xia
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Zheyi Dong
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Paul Harris
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, UK
Chris Brunsdon
National Centre for Geocomputation, Maynooth University, Maynooth, Ireland
Lex Comber
School of Geography, University of Leeds, Leeds, UK
Guanpeng Dong
Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng, 475001, China; Collaborative Innovation Center on Yellow River Civilization Jointly Built By Henan Province and Ministry of Education, Henan University, Kaifeng, 475001, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, China; Corresponding author at: Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng, 475001, China.
Spatial heterogeneity or non-stationarity has become a popular and necessary concern in exploring relationships between variables. In this regard, geographically weighted (GW) models provide a powerful collection of techniques in its quantitative description. We developed a user-friendly, high-performance and systematic software, named GWmodelS, to promote better and broader usages of such models. Apart from a variety of GW models, including GW descriptive statistics, GW regression models, and GW principal components analysis, data management and mapping tools have also been incorporated with well-designed interfaces.
