An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications

被引：67

作者：

Jokar Arsanjani, Jamal ^{[1
]}

Zipf, Alexander ^{[1
]}

Mooney, Peter ^{[2
]}

Helbich, Marco ^{[3
]}

机构：

[1] GIScience Research Group, Institute of Geography, Heidelberg University, Heidelberg

[2] Department of Computer Science, Maynooth University, Maynooth, Co. Kildare

[3] Department of Human Geography and Spatial Planning, Utrecht University, Heidelberglaan 2, Utrecht

来源：

Lecture Notes in Geoinformation and Cartography | 2015年 / 0卷 / 9783319142791期

关键词：

D O I：

10.1007/978-3-319-14280-7_1

中图分类号：

G252.7 [文献检索]; G354 [情报检索];

学科分类号：

摘要：

Recent years have seen new ways of collecting geographic information via the crowd rather than organizations. OpenStreetMap (OSM) is a prime example of this approach and has brought free access to a wealth of geographic information—for many parts of the world, for the first time. The strong growth in the last few years made more and more people consider it as a potential alternative to commercial or authoritative data. The increasing availability of ever-richer data sets of freely available geographic information led to strong interest of researchers and practitioners in the usability of this data—both its limitations and potential. Both the unconventional way the data is being produced as well as its richness and heterogeneity have led to a range of different research questions on how we can assess, mine, enrich, or just use this data in different domains and for a wide range of applications. While this book cannot present all types of research around OpenStreetMap or even the broader category of User Generated Content (UGC) or Volunteered Geographic Information (VGI), it attempts to provide an overview of the current state of the art by presenting some typical and recent examples of work in GIScience on OSM. This chapter provides an introduction to the scholarly work on OpenStreetMap and its current state and summarizes the contributions to this book. © 2015, Springer International Publishing Switzerland.

引用

页码：1 / 15

页数：14

共 34 条

[1]

Amelunxen C., On the suitability of volunteered geographic information for the purpose of geocoding, Proceedings of the Geoinformatics Forum Salzburg, Na, (2010)

[2]

Bakillah M., Res Dominguez J., Zipf A., Liang S., Mostafavi M.A., Multi-agent evacuation simulation data model with social considerations for disaster management context, Intelligent Systems for Crisis Management, SE-1, pp. 3-16, (2013)

[3]

Bakillah M., Liang S., Mobasheri A., Jokar Arsanjani J., Zipf A., Fine-resolution population mapping using OpenStreetMap points-of-interest, Int J Geogr Inf Sci, 28, pp. 1940-1963, (2014)

[4]

Bakillah M., Lauer J., Liang S., Zipf A., Jokar Arsanjani J., Loos L., Mobasheri A., Exploiting Big VGI to Improve Routing and Navigation Services, pp. 177-192, (2014)

[5]

Fan H., Zipf A., Fu Q., Neis P., Quality assessment for building footprints data on OpenStreetMap, Int J Geogr Inf Sci, 28, pp. 700-719, (2014)

[6]

Goetz M., Towards generating highly detailed 3D CityGML models from OpenStreet- Map, Int J Geogr Inf Sci, 27, pp. 845-865, (2013)

[7]

Goetz M., Zipf A., Using crowdsourced indoor geodata for agent-based indoor evacuation simulations, ISPRS Int J Geo-Inf, 1, 2, pp. 186-208, (2012)

[8]

Goodchild M.F., The quality of big (Geo) data, Dialogues Hum Geogr, 3, pp. 280-284, (2013)

[9]

Graham M., Hale S., Stephens M., Digital divide: The geography of internet access, Environ Plan A, 44, pp. 1009-1010, (2012)

[10]

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, pp. 963-982, (2012)

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