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GIScience Blog

Tag: Spatial Autocorrelation

  • Seminar on “Spatial urban analytics” at Harvard

    Our team member René Westerholt recently held a joint session with Dr Guibo Sun from Hong Kong University. The session on “spatial urban analytics” was part of the Geography colloquium at Harvard University. Both talks were dealing with methodological issues. Thereby, René emphasised on technical issues in the spatial analysis of social media data. Dr…

  • Two new DFG projects on VGI, OSM Quality and Social Media Analysis

    recently we were happy to receive the notification that two new research projects will be funded by the Deutsche Forschungsgemeinschaft (DFG) the German main funding agency for fundamental research. Both projects belong to the DFG Priority Programme “Volunteered Geographic Information: Interpretation, Visualisation and Social Computing“ (SPP 1894). The two projects are: A:) IntrisicOSMquality: A framework…

  • PhD Defence Lucy Mburu on Geographic Criminal Profiling

    This Friday – the hottest day of the year so far – Lucy Waruguru Mburu from the GIScience Research Group Heidelberg University successfully defended her PhD thesis on Criminal Geographic Profiling methods. Her thesis is entitled: “ A Framework for Prediciting Criminal Behavior and Area-Specific Crime Risk through Retrospective Analysis of Geographic Data“. Complemented by…

  • Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data

    Detailed knowledge regarding the whereabouts of people and their social activities in urban areas with high spatial and temporal resolution is still widely unexplored. Thus, the spatiotemporal analysis of Location Based Social Networks (LBSN) has great potential regarding the ability to sense spatial processes and to gain knowledge about urban dynamics, especially with respect to…

  • New ways in analysing multi-scale datasets

    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…

  • A Local Multi-Scale Spatial Autocorrelation Measure for Social Media Datasets

    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,…