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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.

This week Prof. Alexander Zipf presented some recent work of the GIScience Research Group Heidelberg and HeiGIT at the “Münchner GI-Runde” of the “Runde Tisch GIS e.V. Munich”. The overall topic of the presentation was spatio-temporal analysis from user generated geodata such as VGI or AGI (Social Media).
Examples included work on OSM quality analytics such as follow up activities based on the ideas from OSMatrix.uni-hd.de and iOSManalyzer (intrinsic OSM analysis) to recent DFG projects dealing with Social Media Data integration or case studies on measuring Recovery from Disasters or Landmark-Based navigation. The outlook covered recent results from Deep Learning combining OSM and MapSwipe data, as well as deriving landuse information from VGI such as OSM (OSMlanduse.org).

the GIScience Heidelberg colloquium series winter semester 2016/17 finished last week with even two presentations about Modeling Tsunami based risks and exposure. We were happy to hear first an overview from Andreas Schäfer vom KIT’s CEDIM about his PhD on Developing a Global Tsunami Risk Model. Thanks for our partners in the HeiKA CrowdFDA project (Crowdsourcing for Forensic Disaster Analysis), (funded through DFG Initiative of Excellence) for jumping in dynamically due to some logistics issues.
Afterwards Prof. Shunichi Koshimura (International Research Institute of Disaster Science, Tohoku University, Japan) talked about the Enhancement of Earth Observation and Modeling for Tsunami Disaster Response and Management.
This was an inspiring end of the colloquium series this semester. Thanks for the discussions!
We are looking forward to welcome anyone interested to the forthcoming GIScience colloquium talks in summer semester 2017. This will start already on Mon, April 3, with a talk from Asher Yair Grinberger (Jerusalem) about “The Identification of Geographic Activity Contexts: Considering Behavioral Effects“. Feel welcome and stay tuned for the next presentations.

(Andreas Schäfer, KIT)

(Prof. Koshimura, Tohoku)

Recently we introduced the website OSMlanduse.org . This week it is featured as “Image of the Week” in the OSM Wiki. Thanks a lot for the recognition! It is already the second OSM Wiki image of the week from GIScience Heidelberg in this short year,as in week 4 OSMvis from our group member Franz-Benjamin was featured.

OSM Landuse/Landcover is a WebGIS application to explore the OpenStreetMap database specifically in terms of landuse and landcover information. It was developed by Michael Auer and Janek Voss with support of the GIScience and HeiGIT team.
There exist well known Landcover/Landuse (LULC) data sets generated from remote sensing imagery such as CORINE, Urban Atlas or GlobeLand30. These are available for different areas, time stamps, and offer different LULC classifications. So it is an interesting question if and to what degree OpenStreetMap can complement, add to, or refine these sources. We want to evaluate the overall possibility and suitability of OpenStreetMap (OSM) for these purposes, identify ways for improvement and provide this information globally to the interested communities. As a first step we categorized the OSM data similar to the classification level 2 of the CORINE Landcover classes. The map is still under development, so stay tuned for further updates!

Last month GIScience Heidelberg (Prof. Zipf) participated in the First United Nations World Data Forum. This was a high level event including many organisations that generate and analyse data related to achieving the UN Sustainable Development Goals of the UN 2030 Agenda for Sustainable Development.
For this we need a huge amount of data about society, development and environment at different scales. This includes e.g. health, education, demography, infrastructure, economy to many environmental aspects from local to global. In total 240 indicators have officially been agreed on as a global indicator framework. Therefore in particular many National Statistical Offices and National Mapping Agencies participated, as well as stakeholders from NGOs, academia and industry.
Geographic information is hereby very important for achieving the UN Sustainable Development Goals and needs to be integrated with the other kind of data and statistical information.
This data is not only needed for measuring the performance of how good the different goals in the different areas have been achieved, but more important already also for setting the priorities and planning activities. Without data it is hard to implement efficient actions!
Further it was stressed that because of the high number of objectives and measures both administration as well as science needs to work on better integrating further kind of data sources such as crowdsourcing into the data generation and analysis chain. This was acknowledged also by officials from UN Statistics office.
The key example for crowdsourced geographic information is OpenStreetMap (OSM). This was also presented by Rebecka Firth from the Humanitarian OpenStreetMap Team (HOT). She gives a good overview of OSM related aspects of the conference in this blog post. This mentions also the goals and work of the Missing Maps project, where GIScience HD is an active early member contributing through tools, research and development helping to improve the availability of geodata in countries in need.

The Special Issue on “Crowdsourced Mapping” of the international journal “Cartography and Geographic Information Science” is online. Here you can read the editorial.

Further this issue includes our paper on Deriving incline values for street networks from voluntarily collected GPS traces. 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. Therfore we have investigated an 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.

John, S.; Hahmann, S.; Rousell, A.; Löwner, M.-O. and Zipf, A. (2016): Deriving incline values for street networks from voluntarily collected GPS traces. Cartography and Geographic Information Systems. Vol 40. Issue 2. Pages 152-169. dx.doi.org/10.1080/15230406.2016.1190300

Stellenausschreibung

Zur Förderung von Technologietransfer und angewandter Forschung im Bereich Geoinformatik wird derzeit mit Grundförderung der Klaus-Tschira Stiftung Heidelberg das Heidelberg Institute for Geoinformation Technology (HeiGIT) aufgebaut. Dies soll zukünftig als An-Institut weitergeführt werden. http://www.geog.uni-heidelberg.de/gis/heigit.html Hierfür wird ein Research & Innovation Manager Geoinformation Technology gesucht (100%). Die Aufgaben beinhalten insbesondere:

  • Strategische Konzeption neuer R&D-Aktivitäten, Dienste, Anwendungen und Produkte auf Basis OpenStreetMap, Open Geodata und nutzergenerierten Daten aus dem Social Web, v.a. in Bereichen wie Datenqualität, Mobilität & Navigation, Smart Cities oder Katastrophenmanagement.
  • Koordinierende Schnittstelle zwischen Forschungs- und Entwicklungsaktivitäten der Abteilung Geoinformatik der Uni HD und dem Heidelberg Institute for Geoinformation Technology sowie Partnern aus Wirtschaft, Verwaltung und Wissenschaft
  • Wissensmanagement und Technology Development
  • Auftrags- und Projektakquise, sowie –management, Drittmittelakquise im nationalen und internationalen Umfeld, Zusammenarbeit mit den Wissenschaftlern GIScience Heidelberg
  • Koordination von Forschungs- und Entwicklungsarbeiten der drei HeiGIT Kernteams (Navigation Intelligence, Big Spatial Data Analytics, Disaster Management)
  • Kommunikation und Präsentation intern und mit externen Partnern und Nutzern, etc.

Wir bieten eine attraktive Stelle in einem interdisziplinär ausgerichteten dynamischen Team in einem hochaktuellen Wachstumsmarkt. Die Abteilung ist u.a. Mitglied im Interdisziplinären Zentrum für Wissenschaftliches Rechnen (IWR) & Gründungsmitglied des Heidelberg Center for the Environment (HCE). Die Exzellenz-Universität Heidelberg bietet in besonderem Maße ein anregendes interdisziplinäres Forschungsumfeld mit vielen persönlichen Entwicklungsmöglichkeiten.

Wir erwarten ein überdurchschnittlich abgeschlossenes Universitätsstudium in einem der Fächer Geoinformatik, Informatik, Geographie o.ä., idealerweise mit Promotion. Erforderlich sind neben ausgeprägtem Teamgeist, Selbständigkeit und hoher Motivation, v.a. ausgezeichnete Methoden- und Technikkompetenz und Erfahrung im Bereich Geoinformatik, insbesondere entweder im Bereich Navigation Intelligence oder Big Spatial Data Analytics. Erfahrung bei Projektakquise und –management, Marketing und Vertrieb, Koordination und Administration, sowie ausgezeichnete Fähigkeiten zu interner und externer Kommunikation und Präsentation auf Deutsch und Englisch.

Die Stelle ist baldmöglichst zu besetzen und zunächst auf 3 Jahre befristet mit der Option auf nachhaltige Verlängerung. Bewerbungsunterlagen (CV, Zeugnisse, Referenzen, etc.) senden Sie baldmöglichstbis spätestens 10.03.2017 - bzw. solange bis die Position besetzt ist an zipf@uni-heidelberg.de. Schwerbehinderte werden bei gleicher Eignung vorrangig eingestellt.

Ausschreibung als PDF

During last weeks LandSense stakeholder at IIASA workshops various tools relevant for VGI data capture, Quality assessment and beyond were discussed. Potential hotshots for validation and improvement of OSMLanduse were FotoQuest and LacoWiki. Also discussed were platforms for hobby bird fans or for spatial data geeks.

http://www.geog.uni-heidelberg.de/gis/land_sense.html
http://osmlanduse.org

Last week we had a special guest for our New Years Mapathon: Nadja Schlüter, a journalist of the popular youth magazine “Jetzt” of the Süddeutsche Zeitung. Nadja had heard about the Missing Maps related activities at our institute during an interview with MSF UK and visited us to learn more about our work and disaster mapping in general. And what better way to learn about disaster mapping than taking part in a mapathon? Read about her experiences in her article: “Heidelberger Studenten kartieren die Krisengebiete der Welt“.

A big thank you to all of our great supporters, we hope to see you again soon at our next mapathon!

Today colleagues from Heidelberg Mobil International GmbH (HDMI) and Heidelberg Institute for Geoinformation Technology (HeiGIT) met in Mathematikon to discuss current trends and activities in developing and advancing Geoinformation Technologies.
Several presentations were given and fruitful discussions covered a broad range of topics that the two institutions are actively working on.
Topics ranged from automated geodata processing and integration, databases and big spatial data frameworks, location based services for indoor and outdoor, routing and navigation, disaster management and humanitarian VGI, as well as several OpenStreetMap APIs and services. Further current technology for mapping and visualisation in 2D and 3D were explained, as well as examples on Spatial Analytics of crowd generated geodata and even recent deep learning approaches. We are looking forward to more closer cooperation and similar follow up events in the new ‘GeoTech Hub’ at Mathematikon Heidelberg, were both institutions are located.

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