Determinación de asentamientos informales en zonas de alta vulnerabilidad por movimientos de remoción en masa en la localidad de Ciudad Bolivar mediante un modelo de inteligencia artificial
Fecha
Autores
Director
Autor corporativo
Título de la revista
ISSN de la revista
Título del volumen
Editor
Compartir
Altmetric
Resumen
The current research aims to locate buildings located in areas with a high probability of landslides in Ciudad Bolívar, Bogotá, using artificial intelligence and Geographic Information Systems methodologies. This study was initiated as a response to the growing proliferation of informal housing in at-risk areas, a phenomenon that has complicated rapid government intervention due to the lack of formal records. To address this problem, two automated building detection models were developed and compared: one trained with local orthoimages and another pre-trained model from ESRI, called Building Footprints USA. Both models were applied to a high-resolution orthomosaic obtained by drone and analyzed based on their detection effectiveness and geographic coverage. The findings showed that the pre-trained model performed remarkably well, identifying 2,396 buildings, compared to the 464 recognized by the local model, which led to its incorporation into an automated geoprocessing workflow in ModelBuilder. Through the spatial superposition of the structures found and the official landslide risk map (Decree 555 of 2021), homes located in high-risk areas are identified. These results provide essential information for decision-making in urban risk management and territorial planning, aligning with the Sustainable Development Goals, especially Goals 1, 3, 11, and 13. Furthermore, this research seeks to demonstrate the integration of artificial intelligence in today's world, which has enabled significant reductions in the time and resources required to identify informal settlements, highlighting the potential of these technologies in vulnerable urban environments. As a result of this research, a map of informal settlements in the study area was obtained, which seeks to guide decision-making through the created model, facilitating the capture of said settlements, which, being in a high-risk zone for mass displacement, represent a danger to the human lives that live there. It must be a priority for the entities in charge to protect those lives and guarantee the well-being of all families.
