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Social and Behavioral Sciences Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
Volunteered And Crowdsourced Geographic Information: The Openstreetmap Project, Michela Bertolotto, Gavin Mcardle, Bianca Schoen-Phelan
Volunteered And Crowdsourced Geographic Information: The Openstreetmap Project, Michela Bertolotto, Gavin Mcardle, Bianca Schoen-Phelan
Journal of Spatial Information Science
Advancements in technology over the last two decades have changed how spatial data are created and used. In particular, in the last decade, volunteered geographic information (VGI), i.e., the crowdsourcing of geographic information, has revolutionized the spatial domain by shifting the map-making process from the hands of experts to those of any willing contributor. Started in 2004, OpenStreetMap (OSM) is the pinnacle of VGI due to the large number of volunteers involved and the volume of spatial data generated. While the original objective of OSM was to create a free map of the world, its uses have shown how the …
Methosm: A Methodology For Computing Composite Indicators Derived From Openstreetmap Data, Dumitru Roman, Tatiana Tarasova, Javier Paniagua
Methosm: A Methodology For Computing Composite Indicators Derived From Openstreetmap Data, Dumitru Roman, Tatiana Tarasova, Javier Paniagua
Journal of Spatial Information Science
The task of computing composite indicators to define and analyze complex social, economic, political, or environmental phenomena has traditionally been the exclusive competence of statistical offices. Nowadays, the availability of increasing volumes of data and the emergence of the open data movement have enabled individuals and businesses affordable access to all kinds of datasets that can be used as valuable input to compute indicators. OpenStreetMap (OSM) is a good example of this. It has been used as a baseline to compute indicators in areas where official data is scarce or difficult to access. Although the extraction and application of OSM …
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Journal of Spatial Information Science
In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. This problem becomes even more pronounced if the cultural and linguistic differences are considered. As a solution, this paper investigates the role of topology as the defining characteristic of a class of spatial objects. We propose a data mining approach based on frequent itemset mining to learn patterns in …
Enhancing Building Footprints With Squaring Operations, Imran Lokhat, Guillaume Touya
Enhancing Building Footprints With Squaring Operations, Imran Lokhat, Guillaume Touya
Journal of Spatial Information Science
Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat …
Twitter Location (Sometimes) Matters: Exploring The Relationship Between Georeferenced Tweet Content And Nearby Feature Classes, Stefan Hahmann, Ross S. Purves, Dirk Burghardt
Twitter Location (Sometimes) Matters: Exploring The Relationship Between Georeferenced Tweet Content And Nearby Feature Classes, Stefan Hahmann, Ross S. Purves, Dirk Burghardt
Journal of Spatial Information Science
In this paper, we investigate whether microblogging texts (tweets) produced on mobile devices are related to the geographical locations where they were posted. For this purpose, we correlate tweet topics to areas. In doing so, classified points of interest from OpenStreetMap serve as validation points. We adopted the classification and geolocation of these points to correlate with tweet content by means of manual, supervised, and unsupervised machine learning approaches. Evaluation showed the manual classification approach to be highest quality, followed by the supervised method, and that the unsupervised classification was of low quality. We found that the degree to which …