@article{fdi:010081709,
  title = {{M}apping and describing geospatial data to generalize complex models : the case of {L}itto{SIM}-{GEN}},
  author = {{L}aatabi, {A}. and {B}ecu, {N}. and {M}arilleau, {N}icolas and {P}ignon-{M}ussaud, {C}. and {A}malric, {M}. and {B}ertin, {X}. and {A}nselme, {B}. and {B}eck, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}or some scientific questions, empirical data are essential to develop reliable simulation models. {T}hese data usually come from different sources with diverse and heterogeneous formats. {T}he design of complex data-driven models is often shaped by the structure of the data available in research projects. {H}ence, applying such models to other case studies requires either to get similar data or to transform new data to fit the model inputs. {I}t is the case of agent-based models ({ABM}s) that use advanced data structures such as {G}eographic {I}nformation {S}ystems data. {W}e faced this problem in the {L}itto{SIM}-{GEN} project when generalizing our participatory flooding model ({L}itto{SIM}) to new territories. {F}rom this experience, we provide a mapping approach to structure, describe, and automatize the integration of geospatial data into {ABM}s},
  keywords = {{FRANCE} ; {OLERON} {ILE} ; {NORMANDIE}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {G}eospatial and {E}nvironmental {R}esearch},
  volume = {7},
  numero = {1},
  pages = {6 [19  + 2 p. h.t.]},
  ISSN = {2332-2047},
  year = {2020},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081709},
}