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Communication Dans Un Congrès Année : 2023

Annotating Satellite Images of Forests with Keywords from a Specialized Corpus in the Context of Change Detection

Ismat Ara Reshma
Camille Franchet
  • Fonction : Auteur
Margot Gaspard
  • Fonction : Auteur
Radu Tudor Ionescu
  • Fonction : Auteur
Josiane Mothe
Sylvain Cussat-Blanc
Hervé Luga
  • Fonction : Auteur
Pierre Brousset
  • Fonction : Auteur

Résumé

The Amazon rain forest is a vital ecosystem that plays a crucial role in regulating the Earth’s climate and providing habitat for countless species. Deforestation in the Amazon is a major concern as it has a significant impact on global carbon emissions and biodiversity. In this paper, we present a method for detecting deforestation in the Amazon using image pairs from Earth observation satellites. Our method leverages deep learning techniques to compare the images of the same area at different dates and identify changes in the forest cover. We also propose a visual semantic model that automatically annotates the detected changes with relevant keywords. The candidate annotation for images are extracted from scientific documents related to the Amazon region. We evaluate our approach on a dataset of Amazon image pairs and demonstrate its effectiveness in detecting deforestation and generating relevant annotations. Our method provides a useful tool for monitoring and studying the impact of deforestation in the Amazon. While we focus on environment applications of our work by using images of deforestation in the Amazon rain forest to demonstrate the effectiveness of our proposed approach, it is generic enough to be applied to other domains.
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Dates et versions

hal-04404237 , version 1 (18-01-2024)

Identifiants

Citer

Ismat Ara Reshma, Camille Franchet, Margot Gaspard, Radu Tudor Ionescu, Josiane Mothe, et al.. Annotating Satellite Images of Forests with Keywords from a Specialized Corpus in the Context of Change Detection. 20th International Conference on Content-based Multimedia Indexing (CBMI 2023), Sep 2023, Orléans, France. pp.14-20, ⟨10.1145/3617233.3617242⟩. ⟨hal-04404237⟩
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