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Geospatial Information ScienceISSN: 10095020 (Print) 19935153 (Online) Journal homepage: https://www.tandfonline.com/loi/tgsi20A Principal Component Analysis (PCA)based framework for automated variable selection in geodemographic classification Yunzhe Liu, Alex Singleton & Daniel ArribasBel To cite this article: Yunzhe Liu, Alex Singleton & Daniel ArribasBel (2019) A Principal Component Analysis (PCA)based framework for automated variable selection in geodemographic classification, Geospatial
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Geo-spatial information science is the field that focuses on the collection, analysis, interpretation, and visualization of geographic and spatial data. It utilizes various technologies like Geographic Information Systems (GIS), remote sensing, and global positioning systems (GPS) to understand spatial phenomena.
Individuals or organizations that engage in activities that require the reporting or management of geographic and spatial data are often required to file geo-spatial information science. This can include government agencies, urban planners, environmental researchers, and businesses involved in real estate and transportation.
Filling out geo-spatial information science typically involves gathering relevant spatial data, entering it into a GIS platform or designated reporting tool, ensuring proper format and accuracy, and submitting the data according to the guidelines provided by the governing authority or organization.
The purpose of geo-spatial information science is to provide tools and methodologies for understanding spatial relationships and patterns, aiding in decision-making processes, facilitating planning and development, and enhancing the management of resources and environments.
Information that must be reported may include geographic coordinates, spatial data layers, descriptions of the data sources, methods of data collection, temporal aspects of the data, and any relevant metadata that provides context and usability for the spatial data.
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