A manually annotated corpus in French for the study of urbanization and the natural risk prevention

Maksim Koptelov (1, 2, 3) , Margaux Holveck (4) , Bruno Cremilleux (1) , Justine Reynaud (1) , Mathieu Roche (3, 5) , Maguelonne Teisseire (3)

1 Equipe CODAG - Laboratoire GREYC - UMR6072
2 INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
3 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
4 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
5 Cirad-ES - Département Environnements et Sociétés

Land artificialization is a serious problem of civilization. Urban planning and natural risk management are aimed to improve it. In France, these practices operate the Local Land Plans (PLU – Plan Local d’Urbanisme) and the Natural risk prevention plans (PPRn – Plan de Prévention des Risques naturels) containing land use rules. To facilitate automatic extraction of the rules, we manually annotated a number of those documents concerning Montpellier, a rapidly evolving agglomeration exposed to natural risks. We defined a format for labeled examples in which each entry includes title and subtitle. In addition, we proposed a hierarchical representation of class labels to generalize the use of our corpus. Our corpus, consisting of 1934 textual segments, each of which labeled by one of the 4 classes (Verifiable, Non-verifiable, Informative and Not pertinent) is the first corpus in the French language in the fields of urban planning and natural risk management. Along with presenting the corpus, we tested a state-of-the-art approach for text classification to demonstrate its usability for automatic rule extraction.

Domaines: Informatique [cs]

Maksim Koptelov, Margaux Holveck, Bruno Cremilleux, Justine Reynaud, Mathieu Roche, et al.. A manually annotated corpus in French for the study of urbanization and the natural risk prevention. Scientific Data , 2023, 10 (1), pp.818. ⟨10.1038/s41597-023-02705-y⟩. ⟨hal-04520001⟩