New MDA Transformation Process from Urban Satellite Image Classification to Specific Urban Landsat Satellite Image Classification

Abstract

In a context where urban satellite image processing technologies are undergoing rapid evolution, this article presents an innovative and rigorous approach to satellite image classification applied to urban planning. This research proposes an integrated methodological framework, based on the principles of model-driven engineering (MDE), to transform a generic meta-model into a meta-model specifically dedicated to urban satellite image classification. We implemented this transformation using the Atlas Transformation Language (ATL), guaranteeing a smooth and consistent transition from platform-independent model (PIM) to platform-specific model (PSM), according to the principles of model-driven architecture (MDA). The application of this IDM methodology enables advanced structuring of satellite data for targeted urban planning analyses, making it possible to classify various urban zones such as built-up, cultivated, arid and water areas. The novelty of this approach lies in the automation and standardization of the classification process, which significantly reduces the need for manual intervention, and thus improves the reliability, reproducibility and efficiency of urban data analysis. By adopting this method, decision-makers and urban planners are provided with a powerful tool for systematically and consistently analyzing and interpreting satellite images, facilitating decision-making in critical areas such as urban space management, infrastructure planning and environmental preservation.