Identifying Patterns in Geospatial Data

Abstract

This thesis discusses the integration between GIS and Data Science. It tries to implement GWR (geographically weighted regression), a geospatial type of regression, through creating a Python plugin that works with QGIS application. The purpose of this work is to use the possible integration between GIS software and data analysis programming languages to implement spatial analysis methods such as GWR. In the beginning of the thesis, some information and background is presented. Afterwards, the GWR method is explained in details. Thereafter, some case studies are discussed, which include two geographical datasets on which GWR could be applied. In the implementation section, the process of creating the plugin is summarized, and the execution results on the datasets are illustrated. Finally, some notes and observations were discussed about the results, along with some future work that can be done for possible improvement.