IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Using OpenStreetMap to Create Land Use and Land Cover Maps: Development of an Application

Using OpenStreetMap to Create Land Use and Land Cover Maps: Development of an Application
View Sample PDF
Author(s): Cidália Costa Fonte (University of Coimbra, Portugal & INESC Coimbra, Portugal), Joaquim António Patriarca (INESC Coimbra, Portugal), Marco Minghini (Politecnico di Milano, Italy), Vyron Antoniou (Hellenic Military Geographical Service, Greece), Linda See (International Institute for Applied Systems Analysis, Austria)and Maria Antonia Brovelli (Politecnico di Milano, Italy)
Copyright: 2017
Pages: 25
Source title: Volunteered Geographic Information and the Future of Geospatial Data
Source Author(s)/Editor(s): Cláudio Elízio Calazans Campelo (Federal University of Campina Grande, Brazil), Michela Bertolotto (University College Dublin, Ireland)and Padraig Corcoran (Cardiff University, UK)
DOI: 10.4018/978-1-5225-2446-5.ch007

Purchase

View Using OpenStreetMap to Create Land Use and Land Cover Maps: Development of an Application on the publisher's website for pricing and purchasing information.

Abstract

OpenStreetMap (OSM) is a bottom up community-driven initiative to create a global map of the world. Yet the application of OSM to land use and land cover (LULC) mapping is still largely unexploited due to problems with inconsistencies in the data and harmonization of LULC nomenclatures with OSM. This chapter outlines an automated methodology for creating LULC maps using the nomenclature of two European LULC products: the Urban Atlas (UA) and CORINE Land Cover (CLC). The method is applied to two regions in London and Paris. The results show that LULC maps with a level of detail similar to UA can be obtained for the urban regions, but that OSM has limitations for conversion into the more detailed non-urban classes of the CLC nomenclature. Future work will concentrate on developing additional rules to improve the accuracy of the transformation and building an online system for processing the data.

Related Content

Salwa Saidi, Anis Ghattassi, Samar Zaggouri, Ahmed Ezzine. © 2021. 19 pages.
Mehmet Sevkli, Abdullah S. Karaman, Yusuf Ziya Unal, Muheeb Babajide Kotun. © 2021. 29 pages.
Soumaya Elhosni, Sami Faiz. © 2021. 13 pages.
Symphorien Monsia, Sami Faiz. © 2021. 20 pages.
Sana Rekik. © 2021. 9 pages.
Oumayma Bounouh, Houcine Essid, Imed Riadh Farah. © 2021. 14 pages.
Mustapha Mimouni, Nabil Ben Khatra, Amjed Hadj Tayeb, Sami Faiz. © 2021. 18 pages.
Body Bottom