Contribution of Machine learning and GIS to the analysis of urban planning in flood-prone areas of Tebessa city. algeria.

Abstract

Today, more than ever before, our cities are exposed to many issues and phenomena that are inevitable natural or human disasters that threaten their stability. According to rapid urbanization, many of these cities extend at the expense of flood-prone areas that cause human and economic losses and make them beyond any control. According to the National Social and Economic Council, the city of Tebessa is one of the most flood-prone cities in Algeria, which made this city suffer every time from flooding issues caused by flood-prone areas. On the one hand, the interaction between humans and the built and natural environment at the visual and sensory level is known as urban planning, which describes physical features as a framework for how to optimize the urban fabric in order to ensure the sustainability of the built environment, and on the other hand, urban planning is one of the most important components of the urban fabric and one of the factors that exacerbate the issue of flooding, especially in flood-prone areas. One of the tools used in this regard is the Geographic Information System (GIS), a system that analyzes, generates, manages and maps all types of data, and provides a basis for drawing, analyzing and using machine learning, helping users and decision makers to understand relationships, geographic context and patterns. In this regard, our goal in this research project mainly talks about using machine learning and GIS to analyze the urban planning of flood-prone areas to understand their characteristics in the city of Tebessa.