RT Journal Article
T1 Semantic modelling of Earth Observation remote sensing
A1 Aldana Martín, José Francisco
A1 García-Nieto, José Manuel
A1 Roldán-García, María del Mar
A1 Aldana-Montes, José Francisco
K1 Teledetección
AB Earth Observation (EO) based on Remote Sensing (RS) is gaining importance nowadays, since it offers a well-grounded technological framework for the development of advanced applications in multiple domains, such as climate change, precision agriculture, smart urbanism, safety, and many others. This promotes the continuous generation of data-driven software facilities oriented to advanced processing, analysis and visualization, which often offer enhanced computing capabilities. Nevertheless, the development of knowledge-driven approaches is still an open challenge in remote sensing, besides they provide human experts with domain knowledge representation, support for data standardization and semantic integration of sources, which indeed enhance the construction of advanced on-top applications. To this end, the use of ontologies and web semantic technologies have shown high success in knowledge representation in many fields, in which the Earth Observation is not an exception. However, as argued by the research community, there is large room for improvement in the specific case of remote sensing, where ontologies that consider the special nature and structure of different satellital and airborne data products are demanded. This article addresses, in first instance, part of this need by proposing a semantic model for the consolidation, integration, reasoning and linking of data (and meta-data), in the context of satellital remote sensing products for EO. With this objective, an OWL ontology has been developed and an RDF repository has been generated to allow advanced SPARQL querying. Although the proposal has been designed to consider remote sensing data products in general, the current study is mainly focused on the Sentinel 2 satellite mission from the Copernicus Programme of the European Space Agency (ESA).  (...)
PB Elsevier
YR 2022
FD 2022-01
LK https://hdl.handle.net/10630/23948
UL https://hdl.handle.net/10630/23948
LA eng
NO Aldana Martín, José Francisco ; Garcia Nieto, Jose Manuel ; Roldan-Garcia, Maria del Mar ; Aldana-Montes, Jose Francisco. Semantic modelling of Earth Observation remote sensing. Expert Systems with Applications Volume 187, January 2022, 115838. https://doi.org/10.1016/j.eswa.2021.115838
NO Funding for open access charge: Universidad de Málaga / CBUA. This work has been partially funded by FEDER Grants TIN2017-86049-R and PID2020-112540RB-C41 (AEI/FEDER, UE) (Spanish Ministry of Education and Science), Andalusian PAIDI program with grant P18-RT-2799, and Green-Senti 2019 & 2021 PP Smart Campus UMA. It is also granted by the LifeWatch-ERIC initiative Smartfood Lifewatch (FEDER & Junta de Andalucia).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 22 ene 2026