Abstract

Urbanization in Indonesia's cities is increasing, leading to various impacts, including negative consequences due to insufficient investment in local public infrastructure. Urbanization assessment primarily relies on examining changes in built-up areas over the past decade. These changes serve as an indicator that can be effectively derived from remote sensing data. In our study, we applied remote sensing data from the Google Earth Engine (GEE) catalog to delve into the urbanization dynamics within Greater Surabaya area, Indonesia. We employed satellite imagery from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI TIRS) for 2012 and 2022. We used Support Vector Machine (SVM) classification techniques to construct precise urban expansion models. Our analysis revealed distinct urban expansion trends in Mojokerto and Sidoarjo, which contrast with the relatively stable urban development trends in northern Surabaya due to the construction of toll roads. The findings provide valuable inputs for urban management, necessitating targeted interventions and strategies to address the urbanization disparities between these two areas. It underscores the critical importance of resource allocation, infrastructure development, and urban planning initiatives, with a specific focus on Gresik, to ensure sustainable urban growth and mitigate potential challenges associated with rapid expansion.

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