• Home
  • About

GIScience News Blog

News of Heidelberg University’s GIScience Research Group.

Feed on
Posts
Comments
« GIScience Heidelberg presentation at Münchner GI-Runde
Towards a Landmark based pedestrian Navigation Service using OpenStreetMap data »

Prize of “Runder Tisch GIS” for GIScience Master Thesis on Geospatial Analysis of the German Software Industry (Jan Kinne, Heidelberg)

Feb 23rd, 2017 by GIScienceHD

The Master Thesis of Jan Kinne on the subject: “The Geographic Dispersal of the German Software Industry - Geospatial Analysis and Location Pattern Modeling” won the price “Nachwuchsförderpreis Geoinformatik 2017” of the “Runde Tisch GIS e.V.” in the category ‘Master Thesis’ with a value of 1.500 Euro.
In addition Jan did also win the audience price for the best presentation of the thesis.
The price was handed to Jan Kinne in a ceremony at the GI-Runde 2017 (Mon 20.Feb 2017) in Munich. We congratulate Jan cordially for this achievement!

Jan Kinne studied Geography with a focus on GIScience at Heidelberg University and wrote the thesis in cooperation with ZEW Mannheim (Centre for European Economic Research) using data of the “Mannheim Enterprise Panel“.

The research within the scope of this thesis aims to contribute to Location Theory. The applied interdisciplinary approach incorporates Regional Science, Economic Geography and Geographic Information Science. The research objective is to analyse the geographic dispersal of German software firm locations. These firm locations are derived from geocoded postal addresses of a multi-year firm census. The resulting point data set allows for the analysis of non-aggregated firm locations in Germany for the first time. It is shown that such detailed geographic data can be used to detect information on location determinants,
which are superimposed when aggregated spatial units are analysed. In an exploratory geospatial data analysis, it is found that the regional settlement structure and the interaction of rural and urban areas have an impact on the local dispersal of software firm locations. In a subsequent regression analysis, the thus identified location determinants are used to model a function that predicts the local occurrence of software firms within each square kilometre of Germany. It is shown that the relationship between the number of software firms and the predicting location factors can be adequately estimated. However, it becomes apparent that a spatial regression model may yield better results than a single global model.

Foto: (c) Runder Tisch GIS

The thesis was written in English, yet here you can find an abstract in German.

Tags: Geographie, GIScience, spatial analysis

Posted in Events, Press release, Research

Comments are closed.

  • About

    GIScience News Blog
    News of Heidelberg University’s GIScience Research Group.
    There are 1,459 Posts and 0 Comments so far.

  • Meta

    • Log in
    • Entries RSS
    • Comments RSS
    • WordPress.org
  • Recent Posts

    • Keynote at McGILL GIS DAY: Analysing and Improving OpenStreetMap for Humanitarian Aid with Data Mining and GeoAI
    • Update on “Accessibility of COVID-19 vaccination centers in Germany”
    • Globales Gletschermonitoring - Chance und Herausforderung — HGG Vortrag am 19.Januar 2021 Dr. Isabelle Gärtner-Roer, World Glacier Monitoring Service, Universität Zürich
    • Accessibility to pharmacies in Germany with 15km Covid-19 restriction
    • 4D change analysis for improving our understanding of dynamic landscapes
  • Tags

    3D 3DGEO Big Spatial Data CAP4Access Citizen Science Colloquium crisis mapping Crowdsourcing data quality disaster DisasterMapping GeoNet.MRN GIScience heigit HOT humanitarian Humanitarian OpenStreetMap team intrinsic quality analysis landuse laser scanning Lidar Mapathon MapSwipe MissingMaps Missing Maps ohsome ohsome example Open data openrouteservice OpenStreetMap OSM OSM History Analytics OSMlanduse Quality quality analysis remote sensing routing social media spatial analysis Teaching terrestrial laser scanning Twitter VGI Wheelchair Navigation Workshop
  • Archives

    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
    • October 2014
    • September 2014
    • August 2014
    • July 2014
    • June 2014
    • May 2014
    • April 2014
    • March 2014
    • February 2014
    • January 2014
    • December 2013
    • November 2013
    • October 2013
    • September 2013
    • August 2013
    • July 2013
    • June 2013
    • May 2013
    • April 2013
  •  

    February 2017
    M T W T F S S
    « Jan   Mar »
     12345
    6789101112
    13141516171819
    20212223242526
    2728  
  • Recent Comments

    GIScience News Blog CC by-nc-sa Some Rights Reserved.

    Free WordPress Themes | Fresh WordPress Themes