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Tag Archive 'Spatial Statistics'

Recently our former team member Rene Westerholt (now at Warwick UK) received this years prize for the best PhD at “Förderpreis Runder Tisch GIS München 2019“. The PhD was done in Heidelberg within the graduate school “CrowdAnalyser – Spatio-temporal Analysis of User-generated Content”.  We concratulate cordially!
The following papers are part of the cummulative PhD thesis [...]

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The concept of place recently gains momentum in GIScience. In some fields like human geography, spatial cognition or information theory, this topic already has a longer scholarly tradition. This is however not yet completely the case with statistical spatial analysis and cartography. Despite that, taking full advantage of the plethora of user-generated information that we [...]

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This week our GIScience Heidelberg team member Rene Westerholt most successfully defended his PhD! Congratulations! Very well deserved!

The thesis is located at the interface between spatial analysis methodology and the characteristics of spatially superimposed random variables. Three types of contributions are presented:
(i) the interactions of spatial analysis techniques with spatially superimposed random variables
are investigated;
(ii) novel [...]

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Inspection and analysis of geo-tagged shipping information could provide insights to the transformation of a variety of “global spaces” during times of rapid globalization. One of the famous resources of shipping data is a shipping newspaper called LLOYDS lists. The list contains weekly and later daily information on global shipping since the late seventeenth century [...]

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A Study on the Twitter usage in the River Elbe Flood of June 2013
In recent years, social media emerged as a potential resource to improve the management of crisis situations such as disasters triggered by natural hazards. Although there is a growing research body concerned with the analysis of the usage of social media [...]

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Many user-generated datasets (e.g., social media) reflect a number of different phenomena. Consequently, these datasets also comprise very different spatial scales. It goes without saying that this evokes tremendous challenges when conducting spatial statistical analyses of such datasets. When assessing spatial autocorrelation among the observations, for example, classical approaches are usually not appropriate. These were [...]

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Some time ago we reported about a new method for assessing spatial autocorrelation among points in social media datasets. A major contribution thereby is the ability of restricting the analysis to specific scales limited by both, an upper and a lower bound. The corresponding paper is now officially available online at IJGIS:
Westerholt, R., Resch, B., [...]

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