Integration of Datasets Toward Slum Identification: Local Implementation of the IDEAMAPS Framework
摘要
We present a pilot implementation to identify and define slums spatially, using the integrated deprived area mapping system (IDEAMAPS)’ deprivation framework. This pilot allows the integration of diverse datasets toward using a data lake architecture developed by INEGI and a grid-based approach to build an ecosystem of interoperable information with an interactive user interface. The pipeline also offers spatial scalability, transferability, and flexibility to work with different data sources, while the grid-based design can facilitate the exploration of interactions among variables. The proposed methodology was tested on a hypothetical case of use in Mexico City, integrating more than 150 variables related to slum conditions in the IDEAMAPS’ framework. Additionally, we created a visualization tool to explore the integrated data.