Modelo metodológico geoespacial para la detección sistemática de inconsistencias prediales y optimización de la estratificación socioeconómica: caso de estudio Bosa, Bogotá

Abstract

Research demonstrates that the application of data analytics and geospatial technologies enhances the efficiency of cadastral management by optimizing the processes of identifying and prioritizing properties that require field verification. The developed model enables the resolution of a significant proportion of cases from the office, thereby reducing unnecessary travel, lowering operational costs, and focusing institutional resources on properties presenting greater technical complexity. This strategy boosts the productivity of cadastral managers and supports the achievement of institutional goals through a more efficient allocation of available resources. Furthermore, the proposal incorporates a data architecture based on PostgreSQL/PostGIS and utilizes the CHIP as a unique integration identifier, ensuring interoperability among the entities responsible for land management. This integration strengthens data consistency and quality, embodies the principle of "collect once, use many times," and facilitates the utilization of data by various institutions for decision-making. From a social perspective, the model serves as a preventive mechanism that fosters territorial and fiscal equity by promptly identifying inconsistencies in property data; this supports the accurate allocation of subsidies to vulnerable populations and provides reliable information for fairer, more transparent taxation that aligns with the actual conditions of the properties