OCT Madrid Land Use

During my internship, I contributed to the development and update of the Madrid Land Use (MLU) geospatial database, a high-resolution polygon dataset documenting urban land use evolution across the Madrid metropolitan area.

The primary goal of this project was to update detailed parcel-level land use classifications for the years 2014 and 2020, extending an existing time series dataset previously developed for 2000, 2006, and 2009. The database supports research and planning initiatives focused on urban growth patterns, infrastructure expansion, and land management decision-making.

Results

The mapping work resulted in a finalized parcel-level land use classification dataset and accompanying visualization map documenting urban land use conditions for the municipalities assigned during my internship period. The completed mapping identifies spatial patterns of residential development, infrastructure expansion, and changes in public, commercial, and service land uses, providing a detailed snapshot of urban growth between 2009, 2014, and 2020.

The final outputs provide planners and researchers with a standardized, multi-temporal dataset that supports direct comparison of land use change across years. By maintaining complete polygon coverage, including areas categorized as unclassified land, the dataset enables future integration with environmental or rural land use data through overlay and statistical analysis workflows. These results contribute to a regional geospatial resource used to support urban planning, land management strategies, and long-term monitoring of metropolitan development trends.

Article Link: Large detail scale mapping from aerial orthophotos for understanding local-scale urban land use dynamics. The case of Madrid, Spain