Stefan Hahmann

How much information is geospatially referenced? Networks and cognition

The aim of this article is to provide a basis in evidence for (or against) the much-quoted assertion that 80% of all information is geospatially referenced. For this purpose, two approaches are presented that are intended to capture the portion of geospatially referenced information in user-generated content: a network approach and a cognitive approach. In the network approach, the German Wikipedia is used as a research corpus. It is considered a network with the articles being nodes and the links being edges. The Network Degree of Geospatial Reference (NDGR) is introduced as an indicator to measure the network approach. We define NDGR as the shortest path between any Wikipedia article and the closest article within the network that is labeled with coordinates in its headline. An analysis of the German Wikipedia employing this approach shows that 78% of all articles have a coordinate themselves or are directly linked to at least one article that has geospatial coordinates. The cognitive approach is manifested by the categories of geospatial reference (CGR): direct, indirect, and non-geospatial reference. These are categories that may be distinguished and applied by humans. An empirical study including 380 participants was conducted. The results of both approaches are synthesized with the aim to (1) examine correlations between NDGR and the human conceptualization of geospatial reference and (2) to separate geospatial from non-geospatial information. From the results of this synthesis, it can be concluded that 56–59% of the articles within Wikipedia can be considered to be directly or indirectly geospatially referenced. The article thus describes a method to check the validity of the ‘80%-assertion’ for information corpora that can be modeled using graphs (e.g., the World Wide Web, the Semantic Web, and Wikipedia). For the corpus investigated here (Wikipedia), the ‘80%-assertion’ cannot be confirmed, but would need to be reformulated as a ‘60%-assertion’.

Twitter location (sometimes) matters: Exploring the relationship between georeferenced tweet content and nearby feature classes

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 OpenStreetMapserve asvalidationpoints. We adopted the classification andgeolocation of these points to correlate with tweet content by means of manual, supervised, and unsuper- vised machine learning approaches. Evaluation showed the manual classification approach to be highest quality, followed by the supervised method, and that the unsupervised clas- sification was of low quality. We found that the degree to which tweet content is related to nearby points of interest depends upon topic (that is, upon the OpenStreetMap category). A more general synthesis with prior research leads to the conclusion that the strength of the relationship of tweets and their geographic origin also depends upon geographic scale (where smaller scale correlations are more significant than those of larger scale).

Deriving incline values for street networks from voluntarily collected GPS traces

ABSTRACT When producing optimal routes through an environment, considering the incline of surfaces can be of great benefit in a number of use cases. For instance, steep segments need to be avoided for energy-efficient routes and for routes that are suitable for mobility-restricted people. Such incline information may be derived from digital elevation models (DEMs). However, the corresponding data capturing methods (e.g. airborne LiDAR, photogrammetry, and terrestrial surveying) are expensive. Current low-cost and open-licensed DEM (e.g. Shuttle Radar Topography Mission [SRTM] and Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) generally do not have sufficient horizontal resolution or vertical accuracy, and lack a global coverage. Therefore, we have investigated an alternative low-cost approach which derives street incline values from GPS traces that have been voluntarily collected by the OpenStreetMap contributors. Despite the poor absolute accuracy of this data, the relative accuracy of traces seems to be sufficient enough to compute incline values with reasonable accuracy. A validation shows that the accuracy of incline values calculated from GPS traces slightly outperforms incline values derived from SRTM-1 DEM, though results depend on how many traces per street segment are used for computation.

Community Engagement Strategies for Crowdsourcing Accessibility Information

Social innovations are increasingly being seen as a way of compensating for insufficiencies of both, state and market to create inclusive and accessible environments. In this paper we explore crowdsourcing accessibility information as a form of social innovation, requiring adequate engagement strategies that fit the skills of the intended group of volunteers and ensure the needed levels of data accuracy and reliability. The tools that were used for crowdsourcing included printed maps, mobile apps for collective tagging, blogs for reflection and visualizations of changing mapping statuses.

Routing through open spaces – a performance comparison of algorithms

Abstract Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines. A common solution is routing on the open space boundary, which causes in most cases an unnecessarily long route. A possible alternative is to create a subgraph within the open space. This paper assesses this approach and investigates its implications for routing engines. A number of algorithms (Grid, Spider-Grid, Visibility, Delaunay, Voronoi, Skeleton) have been evaluated by four different criteria: (i) Number of additional created graph edges, (ii) additional graph creation time, (iii) route computation time, (iv) routing quality. We show that each algorithm has advantages and disadvantages depending on the use case. We identify the algorithms Visibility with a reduced number of edges in the subgraph and Spider-Grid with a large grid size to be a good compromise in many scenarios.

How to cross a square

The poster compares algorithms how squares can be integrated into a routing engine. A case study showed that most algorithms increase the processing time and the created count of edges significantly. FOSS4G 2016 Academic Track Cocobot: An Efficient Road Change Detection System

Maple – a Web Map Service for Verbal Visualisation using Tag Clouds Generated from Map Feature Frequencies

Tag cloud visualisation has been introduced in the seventies. In current Web 2.0 applications this method is a very popular visualisation technique. This paper presents an approach that uses this technique in combination with maps. Our method augments cartographic representations with additional verbal content, which is one of the strongest instruments available to cartographers to communicate spatial information. The idea is that only few words extracted from the semantics contained in the features of the underlying map are suitable to characterise the map section as a whole. To demonstrate the approach we used the OpenStreetMap dataset. In order to allow a variety of web map clients to use the results of the method, we realised the prototype by implementing it as a Web Map Service (WMS) based on the according Open Geospatial Consortium (OGC) specification.