A GIS methodology for mapping regional and community vitality for Canada using the CanEcumene 3.0 Geodatabase with census data

• Published in: One ecosystem : ecology and sustainability data journal Vol. 9; pp. 32 - 22
• Main Author: Eddy, Brian
• Format: Journal Article
• Language: English
• Published: Sofia Pensoft Publishers 26.06.2024
• Subjects: Age composition; Census; Economic conditions; Ecosystem management; Ecosystem-based Management (EBM); Geographic information systems; Geographical distribution; Mapping; Population distribution; Population growth; socio-economic; Socioeconomic factors; Canada
• ISSN: 2367-8194; 2367-8194
• DOI: 10.3897/oneeco.9.e122079

Many ecosystem-based management (EBM) and related applications require integrating geospatial information about socio-economic conditions of human populated areas within a study area. However, integrating socio-economic data in such a way that it can be related to ecological data is challenging due to issues associated with spatial representation between socio-economic and ecological data frameworks. In Canada, this problem is particularly acute given its large geographic size, diversity of environments and highly irregular population distribution. Although several indices have been developed for Canada related to well-being and vulnerability, their suitability for EBM-related applications is limited. This article presents a GIS-based methodology for mapping regional and community vitality index (RVI/CVI) for Canada using standard Census data integrated with the CanEcumene 3.0 Geospatial Database (GDB). The method uses percentile ranks of five sub-indicators of vitality covering population growth, age structure, education, employment and economic wealth. Results reveal a number of notable patterns and trends in socio-economic conditions across the country and across different types of communities and regions. Most notable are decreasing CVI values from economic core regions to rural and remote communities; decreasing scores from high population centres to lower populated areas and lower scores for Indigenous communities when compared with non-Indigenous communities. A series of maps show variation in RVI/CVI values for specific locations with changes over time.