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Articles | Volume 1
https://doi.org/10.5194/ica-abs-1-152-2019
https://doi.org/10.5194/ica-abs-1-152-2019
15 Jul 2019
 | 15 Jul 2019

Feedbacks on VGI in-situ campaign for updating LULC data

Laurence Jolivet, Ana-Maria Olteanu-Raimond, Marie-Dominique Van Damme, Marie Gombert, Simon Fauret, and Thierry Saffroy

Keywords: Volunteered Geographic Information, Land Use Land Cover data, in-situ campaign, data update

Abstract. This work is part of LandSense European H2020 project aiming to build a citizen platform for monitoring Land Use and Land Cover (LULC) data by integrating different types of information such as citizens-contributed data and proposing a set of services (Matheus et al., 2018). One of the pilot studies proposed in LandSense is to monitor urban dynamics to complement authoritative data sources. In this context, one of the goals of the French Mapping Agency (IGN France) is to study the potential of volunteered geographic information (VGI) (Goodchild, 2007) to enrich and update LULC authoritative database by engaging with citizens and several public authorities. The targeted database is OCS-GE containing LULC data (vector polygons) which is produced by IGN France for a 1 : 5.000 scale use. A specificity of OCS-GE database is that both classes LU and LC are assigned to each polygon. Two distinct nomenclatures are in fact defined, each one containing three hierarchical levels. Though in the database, some of the classes are merged due to lack of in-situ information. It is especially the case for some LU classes. Another characteristic is that the database is dated (i.e. represents LULC at a given year) without intermediate versions between two releases (generally every 3 years). Thus, in this context three needs are identified:

  • Detect LULC changes in order to facilitate updates in the next dated version of OCS-GE.
  • Improve LULC data by dividing the merged classes in the database to better match the nomenclature.
  • Update LULC data corresponding to the year of the OCS-GE (for the moment 2013 and 2016).
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