2026-05-30T01:08:07Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/306382026-02-03T10:53:19Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Burgueño Romero, Antonio Manuel author Aldana Martín, José Francisco author Vázquez-Pendón, María author Barba-González, Cristóbal author Jiménez-Gómez, Yaiza author García Millán, Virginia author Navas-Delgado, Ismael author 2023-06-02 The production of land cover maps is an everyday use of image classification applications on remote sensing. However, managing Earth observation satellite data for a large region of interest is challenging in the task of creating land cover maps. Since satellite imagery is getting more precise and extensive, Big Data techniques are becoming essential to handle the rising quantity of data. Furthermore, given the complexity of managing and analysing the data, defining a methodology that reduces the complexity of the process into different smaller steps is vital to data processing. This paper presents a Big Data methodology for creating land cover maps employing artificial intelligence algorithms. Machine Learning algorithms are contemplated for remote sensing and geodata classification, supported by explainable artificial intelligence. Furthermore, the process considers aspects related to downloading data from different satellites, Copernicus and ASTER, executing the pre-processing and processing of the data in a distributed environment, and depicting the visualisation of the result. The methodology is validated in a test case for er map of the Mediterranean Basin. Burgueño, A. M., Aldana-Martín, J. F., Vázquez-Pendón, M., Barba-González, C., Jiménez Gómez, Y., García Millán, V., & Navas-Delgado, I. (2023). Scalable approach for high-resolution land cover: a case study in the Mediterranean Basin. Journal of Big Data, 10(1), 1-22.https://doi.org/10.1186/s40537-023-00770-z https://hdl.handle.net/10630/30638 10.1186/s40537-023-00770-z Aprendizaje automático (Inteligencia artificial) Árboles de decisión Suelo - Uso - Proceso de datos Scalable approach for high-resolution land cover: a case study in the Mediterranean Basin.