Publications des scientifiques de l'IRD

Laatabi A., Becu N., Marilleau Nicolas, Pignon-Mussaud C., Amalric M., Bertin X., Anselme B., Beck E. (2020). Mapping and describing geospatial data to generalize complex models : the case of LittoSIM-GEN. International Journal of Geospatial and Environmental Research, 7 (1), 6 [19 p. + 2 p. h.t.]. ISSN 2332-2047.

Titre du document
Mapping and describing geospatial data to generalize complex models : the case of LittoSIM-GEN
Année de publication
2020
Type de document
Article
Auteurs
Laatabi A., Becu N., Marilleau Nicolas, Pignon-Mussaud C., Amalric M., Bertin X., Anselme B., Beck E.
Source
International Journal of Geospatial and Environmental Research, 2020, 7 (1), 6 [19 p. + 2 p. h.t.] ISSN 2332-2047
For some scientific questions, empirical data are essential to develop reliable simulation models. These data usually come from different sources with diverse and heterogeneous formats. The design of complex data-driven models is often shaped by the structure of the data available in research projects. Hence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. It is the case of agent-based models (ABMs) that use advanced data structures such as Geographic Information Systems data. We faced this problem in the LittoSIM-GEN project when generalizing our participatory flooding model (LittoSIM) to new territories. From this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into ABMs
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du milieu [021] ; Télédétection [126] ; Cartographie / Méthodes graphiques [128]
Localisation
Fonds IRD [F B010081709]
Identifiant IRD
fdi:010081709
Contact