Abstract
Today, accelerated growth has led to unprecedented growth in urban areas. Indeed, the demographic explosion has become a problem for urban planners because it makes it necessary to frequently update land use and occupancy maps. To overcome the difficulties of urban planning, it is necessary to implement a geographic information system (GIS) as the main tool in planning operations and satellite data. GIS and satellite imagery can support the urban planning process by enabling the storage, manipulation, and analysis of data valid for planning, and decision making. The objective of our paper is to present an overview of the different approaches and advanced methods of spatial analysis and machine learning applied in the field of urban planning. Then, we cited the different sources of satellite data, and we have demonstrated the usefulness of integrating remote sensing with GIS and the different multispectral indices that allow the extraction of urban characteristics and are designed to improve satellite imagery to introduce new urban classification schemes. The researchers’ results showed that the implementation of GIS in urban planning can improve the result based on the quality of the urban planning process, save time, and the data can be obtained faster.
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