Automatización de flujos de procesamiento de imágenes satelitales para monitoreo de desplazamiento de tierra

Abstract

The project arises from the need to optimize the processing of satellite imagery within the SNAP platform, as this procedure is currently performed manually and requires multiple user-dependent steps. The main objective is to design and implement a web application that automates workflow processes in order to reduce execution times and improve efficiency in landslide analysis. Sentinel-1 satellite images obtained from the ASF platform were used. Additionally, tools such as React for the graphical interface, Flask for the backend, and SNAP/GPT for workflow execution were employed, along with containerization using Docker to ensure reproducibility. Among the results, a reduction in processing times was observed, as well as improved usability for system users. Furthermore, a visualization module was integrated to enable clear and accessible interpretation of the results. It is concluded that automation constitutes an effective tool to optimize landslide monitoring and strengthen geological risk management in Ecuador. Keywords: Automation, SNAP, Sentinel-1, landslides, satellite processing.