Country

France

 

General description

Institut National de l’Information Géographique et Forestière (IGN http://www.ign.fr) is the French National Mapping Agency. It is the public-owned national operator in charge of the collection and dissemination of GeoInformation and forestry information on the whole French territory. It is also in charge of carrying out in-depth research in the fields of geo-sensors, geodesy, photogrammetry, remote sensing, spatial information sciences, and geo-statistics to maintain a strong expertise for the French public policies and to strongly support the innovation of IGN and more globally the innovation of the whole geospatial community.

 

Role in the project

IGN will lead the WP3 “Harmonisation & Interoperability”.

IGN is further involved in the experiments related to CAP monitoring and will – together with ASP – actively contribute to Use Case 1a ‘Earth observation monitoring and traffic lights’ and Use Case 5a ‘LPIS update’ in WP2.

 

Key persons involved

Dominique Laurent is engineer in geographic sciences. She has been working in standardization unit since 2005, mainly in activities related to data interoperability. She has been widely involved in INSPIRE (member of Drafting Team Data Specifications, facilitator of Thematic Working Groups on Cadastral Parcels and on Buildings, chair of the EuroGeographics INSPIRE Knowledge Exchange Network, contributor to several INSPIRE related projects, such as ESDIN, Humboldt, ELF). She is technical coordinator of UN-GGIM: Europe WG on core data (priority data for the SDG).

Nicolas David is engineer in geographic sciences. He has been involved in remote sensing activities in IGN since 2006: he worked first as a research engineer in the MATIS research lab at IGN. He also has a strong expertise in software development. He was lately been closely involved in the setting up of a new “Land Use Land Cover “ product (OCS GE).

Grégoire Maillet is an IGN engineer, with more than 15 year experience in the field of software development, photogrammetry and image processing. Since 2012, he is the head of a team in charge of software developments in these domains. This team is also responsible for development and maintenance of the IGN made aerial images processing chain (more than 200 000 km2 are processed every year).

 

Relevant publications

www.ign.fr

Hjelmager, J., Moellering, H., Cooper, A., Delgado, T., Rajabifard, A., Rapant, P., Danko, D., Huet, M., Laurent, D., Aalders, H. and Iwaniak, A., 2008. An initial formal model for spatial data infrastructures. International Journal of Geographical Information Science, 22(11-12), pp.1295-1309.

Cooper, A.K., Coetzee, S., Rapant, P., Laurent, D., Danko, D.M., Iwaniak, A., Peled, A., Moellering, H. and Düren, U., 2014. Exploring the Impact of a spatial data infrastructure on value-added resellers and vice versa. In Cartography from pole to pole (pp. 395-404). Springer, Berlin, Heidelberg.

 


Relevant projects and activities

• IGN is a participant of the Landsense H2020 project, aiming to aggregate innovative EO technologies, mobile devices, community-based environmental monitoring, data collection, interpretation and information delivery systems to empower communities to monitor and report on their environment.

• IGN is a participant in the Diabolo H2020 project, aiming to improve knowledge on European forest resources, by improving the methods of data collection in order to produce more accurate, harmonised and timely information that can be fed into EU forest information systems, and by developing methodologies to make innovative use of data collected using terrestrial, aerial and space based platforms.

• IGN is a participant in the Urclim project (funded by the ERA-NET ERA4CS), aiming to provide climate services to scientists to estimate the impacts of climate phenomena at the city scale, taking into account uncertainties of all kinds. IGN provides its expertise on existing geographic data, and smart visualization of impacts and uncertainties. IGN also works on multispectral images and urban DSM as inputs for heat island modeling.