Detection and Semantic Description of Changes in Earth Observation Time Series Data

Milon-Flores, Daniela F.; Bernard, Camille; Gensel, Jérôme; Giuliani, Gregory

doi:10.1007/978-3-031-74633-8_29

Proceedings chapter

English

Detection and Semantic Description of Changes in Earth Observation Time Series Data

ContributorsMilon-Flores, Daniela F.

; Bernard, Camille

; Gensel, Jérôme

; Giuliani, Gregory

Presented atInternational Workshops of ECML PKDD 2023, Turin, Italy, 18-22 Septembre 2023

Published inMachine Learning and Principles and Practice of Knowledge Discovery in Databases, p. 405-411

PublisherCham : Springer Nature Switzerland

Collection

Communications in Computer and Information Science; 2135

Publication date2025

First online date2025-01-01

Abstract

The overexploitation of natural resources and pollution are urgent concerns aﬀecting the Earth’s global system.Earth Observation (EO) data can be used to analyze the environmental impact of human activities. However, extracting meaningful insights from EO time series data requires domain expertise. In this position paper, we propose a methodology to improve the accessibility and understanding of environ- mental trends for a wide audience. Using Machine Learning (ML) tech- nologies, we detect and describe in the Semantic Web (SW) changes in EO time series.

Keywords

Earth Observations
Semantic Web
Machine Learning

Affiliation entities

Centres et instituts / Institut des sciences de l'environnement

Research groups

Citation (ISO format)

MILON-FLORES, Daniela F. et al. Detection and Semantic Description of Changes in Earth Observation Time Series Data. In: Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy. Cham : Springer Nature Switzerland, 2025. p. 405–411. (Communications in Computer and Information Science) doi: 10.1007/978-3-031-74633-8_29

Proceedings chapter (Published version)

Identifiers

PID : unige:182368
DOI : 10.1007/978-3-031-74633-8_29

Additional URL for this publicationhttps://link.springer.com/10.1007/978-3-031-74633-8_29

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Detection and Semantic Description of Changes in Earth Observation Time Series Data

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