Investigating the potential of OpenStreetMap for land use/land cover production: A case study for continental Portugal

被引：43
作者：
Estima, Jacinto [1 ]
Painho, Marco [1 ]
机构：
[1] ISEGI, Universidade Nova de Lisboa, Lisbon
来源：
Lecture Notes in Geoinformation and Cartography | 2015年 / 0卷 / 9783319142791期
关键词：
Land cover; Land use; OpenStreetMap (OSM); Volunteered geographic information (VGI);
D O I：
10.1007/978-3-319-14280-7_14
中图分类号：
学科分类号：
摘要：
In the last decade, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information (VGI). Through the research that has been conducted recently, it has become clear that this huge amount of information might hide interesting and rich geographical information. The OpenStreetMap (OSM) project is one of the most well-known and studied VGI initiatives. It has been studied to identify its potential for different applications. In the field of Land Use/Cover, an earlier study by the authors explored the use of OSM for Land Use/Cover (LULC) validation. Using the COoRdination of INformation on the Environment (CORINE) Land Cover (CLC) database as the Land Use reference data, they analyzed the OSM coverage and classification accuracy, finding an interesting global accuracy value of 76.7 % for level 1 land classes, for the study area of continental Portugal, despite a very small coverage value of approximately 3.27 %. In this chapter we review the existing literature on using OSM data for LULC database production and move this research forwards by exploring the suitability of the OSM Points of Interest dataset. We conclude that OSM can give very interesting contributions and that the OSM Points of Interest dataset is suitable for those classified as CLC class 1 which represents artificial surfaces. © 2015, Springer International Publishing Switzerland.
引用
收藏
页码：273 / 293
页数：20
相关论文
共 41 条
  • [21] Goodchild M., Assertion and authority: The science of user-generated geographic content. In: Proceedings of the Colloquium for Andrew U. Frank’s 60th birthday, Department of Geoinformation and Cartography, (2008)
  • [22] Goodchild M., Commentary: Whither VGI, Geojournal, 72, 3-4, pp. 239-244, (2008)
  • [23] Goodchild M., Glennon J.A., Crowdsourcing geographic information for disaster response: A research frontier, Int J Digit Earth, 3, 3, pp. 231-241, (2010)
  • [24] (2014)
  • [25] Hagenauer J., Helbich M., Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks, Int J Geogr Inf Sci, 26, 6, pp. 963-982, (2012)
  • [26] Hecht R., Kunze C., Hahmann S., Measuring completeness of building footprints in OpenStreetMap over space and time, ISPRS Int J Geo-Inf, 2, 4, pp. 1066-1091, (2013)
  • [27] Hollenstein L., Purves R., Exploring place through user-generated content: Using Flickr to describe city cores, J Spat Inf Sci, 1, 1, pp. 21-48, (2010)
  • [28] Holone H., Misund G., Holmstedt H., Users are doing it for themselves: Pedestrian navigation with user generated content, International Conference on Next Generation Mobile Applications, Services and Technologies, pp. 91-99, (2007)
  • [29] Hudson-Smith A., Batty M., Crooks A., Milton R., Mapping for the masses: Accessing web 2.0 through crowdsourcing, Soc Sci Comput Rev, 27, 4, pp. 524-538, (2009)
  • [30] Jokar Arsanjani J., Helbich M., Bakillah M., Exploiting volunteered geographic information to ease land use mapping of an urban landscape, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (2013)
12345