Tag: cluster. spatial analysis

Mining and correlating traffic events from human sensor observations with official transport data using self-organizing-maps

Cities are complex systems, where related Human activities are increasingly difficult to explore within. In order to understand urban processes and to gain deeper knowledge about cities, the potential of location-based social networks like Twitter could be used a promising example to explore latent relationships of underlying mobility patterns. In a recently published paper (Steiger…

2016-11-16
Enrico Steiger defends PhD on Explorative Spatial & Temporal Human Mobility Analysis from User-Generated Data

today Enrico Steiger successfully defended his PhD thesis about “Explorative Spatial and Temporal Human Mobility Analysis from User-Generated Data” at GIScience Heidelberg University. The massive amount of pervasive, user-generated data creates new possibilities to discover and utilize geographic information. Tied in with this novel role of actively participating users, is a growing research challenge where…

2016-02-05
CrowdAnalyser Talk and Workshop on Big Data and Socioeconomic Analysis by Professor Paul Longley

By the end of November, Professor Paul Longley and his colleague Guy Lansley (both from Department of Geography, University College London) visited our group as part of the last CrowdAnalyser workshop. Both of them gave really inspiring talks. Paul talked about the provenance and use of big data (largely focussing on social media). Guy, in…

2015-12-07
gis.SCIENCE special issue GEOINFORMATIK 2013

The issue 3/2013 (Vol. 26) of the journal gis.SCIENCE by Wichmann has been published. It contains selected full review paper (e.g. on context-aware 3D geovisualization or on the analysis of tourist activity from Flickr fotos) from the conference GEOINFORMATIK 2013, that was held at Heidelberg University this year. The cover features a screenshot from OSM-3D.org…

2013-09-26
New tool for clustering and analyzing spatial data with Neural Networks and Neural Gas

A new tool for clustering and analyzing geographic data with artifical self-organizing neural networks (SOM) and the innovative Neural Gas (NG) algorithms has been made availabe. The free SPAWNN suite supports different spatial context models and it also establishes interactive linkage between the neural network and geographic maps. Notably it enables further the follow-up clustering…

2013-09-12