Advancements in High-Resolution Land Use Mapping: Methodologies and Insights from the Rethinkaction H2020 Project

Christoph Correia; Jesús Ortuño Castillo; Marta Toro Bermejo; Patricia Perez Ramirez

doi:10.18172/cig.6415

Autores/as

Christoph Correia GMV Innovating Solutions (Spain) https://orcid.org/0009-0002-2559-539X
Jesús Ortuño Castillo GMV Innovating Solutions (Spain) https://orcid.org/0000-0003-1737-8934
Marta Toro Bermejo GMV Innovating Solutions (Spain) https://orcid.org/0009-0002-2366-4101
Patricia Perez Ramirez GMV Innovating Solutions (Spain) https://orcid.org/0009-0009-8364-4218

DOI:

https://doi.org/10.18172/cig.6415

Palabras clave:

usos del suelo, GEOBIA, análisis espacial, teledetección, cartografía de alta resolución

Resumen

La cartografía de uso y cobertura del suelo (LULC, por sus siglas en inglés) es fundamental para las estrategias de adaptación y mitigación del cambio climático basadas en el territorio. Este estudio presenta el desarrollo de mapas de uso del suelo de alta resolución (HR) a 10 metros en el marco del proyecto RethinkAction H2020, con el objetivo de mejorar la planificación espacial orientada a la mitigación y adaptación climática. La metodología integra datos de teledetección, técnicas de clasificación mediante aprendizaje automático y conjuntos de datos auxiliares para generar clasificaciones precisas y transferibles del uso del suelo en seis regiones bioclimáticas europeas. El estudio emplea imágenes de Sentinel-2 y Landsat-8, utilizando clasificación supervisada con Random Forest (RF) y análisis geográfico basado en objetos (GEOBIA) para mejorar la precisión y reducir la confusión espectral. Este enfoque dio lugar a la creación de doce mapas HR de uso del suelo en dos niveles de clasificación, abarcando seis áreas de estudio de caso (CS). Una contribución clave de esta investigación es la generación de mapas de idoneidad, que evalúan el potencial para implementar soluciones de mitigación y adaptación basadas en el suelo (LAMS), como la reforestación, la captación de agua y el desarrollo de energía fotovoltaica. Este estudio subraya la importancia de integrar teledetección, aprendizaje automático y análisis espacial para respaldar la toma de decisiones fundamentadas en la planificación del uso del suelo, ofreciendo una metodología escalable y replicable para la clasificación detallada de LULC.

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