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As urbanization continues to shape the world's landscape, concerns have intensified over environmental degradation and depletion of natural resources. Accordingly, international agendas emphasize managing urban sprawl for inclusive, resilient, and sustainable cities. On this basis, this study consists of exploring the nexus of urbanization and advanced technologies following a methodological approach based on a bibliometric analysis using the Dimensions Database to analyse research related to urban sprawl and LULC Changes from 1994 to the recent years; and a systematic review to synthesize existing literature on different methodologies integrating GeoAI technologies and LULC Analytics in the process of monitoring landscape, which optimizes Urban Planning and empowers predictive modelling to monitor environmental changes, therefore, promoting intelligent decision-making and inclusive growth via enabling the creation of targeted policies that address socio-economic disparities, environmental sustainability and infrastructure enhancement. By improving comprehension of scientific concepts, this article aims to fill the knowledge gap between urban studies and remote sensing using machine learning.
Aidaoui et al. (Sun,) studied this question.
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