The semi-urban, semi-rural nature of many cities around the world often leads to conflicts due to their unclear boundaries. This study aims to classify geospatial data into peri-urban, urban, and rural areas using a spatial analysis and geoprocessing process based on socio-economic indicators such as population, distance to urban areas, urban isolation, and road network density and availability. The process utilized satellite images and OpenStreetMap data to distinguish three types of settlements: urban, rural, and peri-urban, and subcategories within each type such as urban, semi-urban, suburban, metropolis, douar, rural settlement, sparse rural, and isolated habitat. Results showed a correlation of over 98% between the estimated population of the generated settlement classes and census data, indicating the effectiveness of this approach, which can be replicated in other settlements, particularly in North Africa.
Automated Process for Classifying Built-up Areas Using Geospatial and Census Data, Applied to an Agglomeration of the Algerian Coast
Mohamed el-Amine Gacemi, Sid Ahmed Souiah, Walid Rabehi, Djamel Mansour; Automated Process for Classifying Built-up Areas Using Geospatial and Census Data, Applied to an Agglomeration of the Algerian Coast. The Arab World Geographer 1 September 2023; 26 (1): 38–56. doi: https://doi.org/10.5555/1480-6800-26.1.38
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