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The Center for Spatial Studies, Department of Geography at the University of California, Santa Barbara is hosting the Spatial Data Science Symposium 2019 this coming week with the title

Setting the Spatial Data Science Agenda”

Over 40 selected participants will gather to discuss the future of Spatial Data Science at this expert meeting. Instead of being restricted by a historically grown partition into small and overlapping communities that deal with spatial data in one way or the other, the overarching goal of this symposium is to put spatial data science at the forefront of a unified field that explores the current research and application landscape to define an agenda for spatial data science for the next 10 years.

Prof. Alexander Zipf has been invited to stimulate the discussion with an talk about

User generated Geoinformation and Spatial Data Science - Dream Team or Nightmare?”

We thank the organisers for initiating this important meeting and are looking towards the outcome of the discussion about a potential research agenda for the emerging field of Spatial Data Science.


Last June, colleagues from the GIScience group - Dr. Tessio Novack, Dr. Michael Schultz and Prof. Dr. Alexander Zipf - together with Dr. Peter Mooney (Maynooth University, Ireland) and Dr. Yair Grinberger (The Hebrew University in Jerusalem, Israel) have organized a workshop on “The Geographical and Cultural Aspects of Geo-Information: Issues and Solutions (GeoCultGIS)” as part of the AGILE 2019 conference in Limassol. The proceedings of this workshop are now freely available online, including an introduction from the organizers and interesting contributions on topics such as the institutional contexts of volunteered geographic information, the representation of urban green spaces in OpenStreetMap, and the spatial signatures of street types in relation to place types.

We remind you that a special issue of Transactions in GIS, based on the workshop’s theme, is currently being organized by Dr. Novack, Dr. Schultz, Prof. Dr. Zipf, and Dr. Grinberger. We are welcoming high-quality contributions related, but not limited, to the following topics:

  • The formalization of geo-cultural contexts within GIScience methods
  • Representation of geo-cultural contexts with GISystems
  • Identifying geo-cultural effects on geo-information and vice versa
  • Methodological developments in analyzing global heterogeneous datasets
  • Geo-ontologies and their relations to culture and geography
  • The application of machine-learning methods across diverse geo-cultural contexts
  • Integration of data production procedures in methodological developments and applications
  • The transferability of GIScience methods over different contexts
  • Volunteered geographical information (e.g. OpenStreetMap) systems and methods for representing and capturing local knowledge
  • Critical GIS, critiques of GIS, and their contributions to methodological development in GIScience
  • Review of the state-of-the-art in addressing cultural and geographical peculiarities in GIScience.

The submission deadline is 15 January 2020.

Manuscripts should be prepared in accordance with ​the authors’ guidelines​ and submitted via the journal’s submission system. Please mark your manuscript as part of the special issue while submitting. All submissions will go through a ​peer-review​ process, in accordance with the regular requirements of Transactions in GIS. Questions and inquiries should be addressed to Dr. Tessio Novack: ​novack@uni-heidelberg.de

Happy Birthday Missing Maps! On the occasion of the recently launched Missing Maps 5 Years Birthday Blog, that also highlighted our latest Missing Maps related HeiGIT and ohsome projects, we put together an overview of our years with and within the Missing Maps.

November 2014 the Missing Maps project was launched by the British and American Red Cross, MSF UK and the Humanitarian OpenStreetMap Team with the humble objective to put the world`s vulnerable people on the map. Since then, 14 organizations joined the founding members to support in achieving this goal- and more than 95, 000 mappers.

Already in 2015, GIScience Research Group and disastermappers heidelberg were invited to join the Missing Maps members. While the former were previously providing mapathon support and raising awareness of Missing Maps in academia in general and the own university networks, Heidelberg then already became the gathering place of Missing Maps members in May 2015- and was now the official location for our Missing Maps Gathering 2019.

Missing Maps Meeting 2015

Missing Maps Meeting 2019

The 2015 meeting already lead to a first collaborative project- MapSwipe- building on related research and expertise of the GIScience group and showing the great potential of humanitarians and researchers working together.

Since then, several joint publications (see below), presentations, projects and partnerships followed. Presentations were, among others, given to audiences of medical sectors at MSF Scientific Days, of international humanitarian organizations at Global Platform for Disaster Risk Reduction and International Dialogue Platforms on Anticipatory Action and the GIScience and research community at the Geospatial World Forum and ISCRAM. Previous projects to date include MapSwipe and MapSwipe Analytics, Micro-mapping in the scope of MS Wissenschaft, as well as developments around the openrouteservice for disaster management and the use of machine and deep learning to support humanitarian mapping.

Regarding Missing Maps related partnerships, apart from our close link to other Missing Maps members, the formalized partnership with German Red Cross can further be highlighted. Starting with mapathons and meetings at GRC and beyond in 2017, the groups signed a Memorandum of Understanding in 2018, and now have a joint HeiGIT/GRC position to further strengthen the collaboration. GRC is furthermore currently in the process of joining Missing Maps as a formal member.

But what about our current and future Missing Maps involvement? Apart from already listed and still ongoing projects, the HeiGIT team supports Missing Maps in monitoring and visualizing its achievements and impact using the HOT Tasking Manager API and their own ohsome framework. This work is also highlighted in the recently launched Missing Maps birthday blog and will be further extended with the Missing Maps members. Among other project ideas for sure…

We are looking forward to learning what we will collaboratively achieve in the next 5+ years. So make sure to stay tuned!

Happy Birthday Missing Maps!

Herfort, B., Li, H., Fendrich, S., Lautenbach, S., Zipf, A. (2019): Mapping Human Settlements with Higher Accuracy and Less Volunteer Efforts by Combining Crowdsourcing and Deep Learning. Remote Sensing 11(15), 1799. https://doi.org/10.3390/rs11151799

Li, H., Herfort, B., Zipf, A. (2019): Estimating OpenStreetMap Missing Built-up Areas using Pre-trained Deep Neural Networks. Proceedings of the 22nd AGILE Conference on Geographic Information Science, Limassol, Cyprus.

Scholz, S., Knight, P., Eckle, M., Marx, S., Zipf, A. (2018): Volunteered Geographic Information for Disaster Risk Reduction: The Missing Maps Approach and Its Potential within the Red Cross and Red Crescent Movement. Remote Sens., 10(8), 1239, doi: 10.3390/rs10081239.

de Albuquerque, J. P., Eckle, M., Herfort, B., Zipf, A. (2016): Crowdsourcing geographic information for disaster management and improving urban resilience: an overview of recent developments and lessons learned. In: Capineri, C, Haklay, M, Huang, H, Antoniou, V, Kettunen, J, Ostermann, F and Purves, R. (eds.) European Handbook of Crowdsourced Geographic Information, Pp. 309–321. London: Ubiquity Press. DOI: http://dx.doi.org/10.5334/bax.w. License: CC-BY 4.0.

Herfort, B., Eckle, M., de Albuquerque, J. P. (2016): Being specific about geographic information crowdsourcing: a typology and analysis of the Missing Maps project in South Kivu. 13th International Conference on Information Systems for Crisis Response and Management. ISCRAM 2016. Rio de Janeiro, Brazil.

Porto de Albuquerque, J., Herfort, B.,Eckle, M. (2016): The Tasks of the Crowd: A Typology of Tasks in Geographic Information Crowdsourcing and a Case Study in Humanitarian Mapping. Remote Sensing. 2016, 8(10), 859; doi:10.3390/rs8100859.

On 29 November 2019, we celebrated together with the graduates of 2018/2019 of Bachelor and Master of Science in Geography, and also School Education (Lehramt) at the ceremony in the venue of the Neue Aula of Heidelberg University. Moreover, Prof. Carl Zillich gave an interesting talk about perspectives, controversies and visions of the International Building Exhibition (IBA) Heidelberg and the role of science in urban developement.

Furthermore, the Dietrich Barsch Prize for the best Bachelor thesis in Physical Geography was awarded to Veit Ulrich. He investigated an acive rock glacier in the Austrian Alps by means of 3D surface change at different timescales using terrestrial LiDAR observation. Veit was jointly supervised by Prof. Bernhard Höfle and Dr Stefan Hecht.

We congratulate all graduates and wish them all the best for their future!

It’s been a while, since  we have published the last blog post about the awesome ohsome platform, but don’t worry, there’s always something happening of course in the spatial analytics team of HeiGIT. So here we are, back on track with enlarging your imagination on what is possible when using our OpenStreetMap history analytics tool. This blog post presents a recently added feature, namely the integration of simple feature keywords in the filters of the ohsome API. It is now possible to filter directly on point1, line1, polygon1, or other1 features using these respective keywords in the types filter of the API. Let’s look at two examples to get ideas about what we can do with that new feature.

The first example uses types=polygon in combination with keys=building to retrieve all buildings from a specified region, in this case from the old town of Bergamo in Italy for the 1st of October 2019. With the help of this filter, we do not need to know which OSM types we have to use (node vs. way vs. relation), but just get all buildings that are properly mapped with a correct geometry. This means that the result consists of a combination of way and relation features. Using the simple feature filters also results in a decrease in processing time, as we can filter out more complex geometries earlier in our processing chain, which would otherwise be included longer, if you would just use types=way,relation. The following visualization shows the returned data together with an OSM base map and the used bounding box.

The second example gives us actually just the opposite. It returns the incorrectly mapped (or tagged) buildings, this time for a bounding box around Frankfurt, Germany and using the same timestamp. To receive that data we use the types=line,other filter together with keys=building. In this response you can find for example features with the tag building=no, which is explicitly defined as not being a valid tag to define a polygon (further info). Especially this approach, searching for falsely tagged or drawn features, in other words erroneous data, has not really been covered in our analyses thus far. Having this new filtering feature enables you to fire such requests on our API and search for that kind of data in any region in the world.

If you liked this post (and even more so if not), or have any other ideas/comments/etc. please drop us a message at our info(at)heigit.org email address. Don’t forget to stay ohsome!

1 for those of you that are interested on what’s happening under the hood, here’s on what this new filter is based on internally:

  • point is puntal and uses the OSM type node
  • line is lineal and uses way features that are not seen as polygons, e.g.: roundabouts having the tag highway=* are closed ways, but not interpreted as planar features, so they are included here
  • polygon is polygonal and uses way, as well as relation features that are planar (planar := features having an area) and have a corresponding tag, which tells us that this feature has an area, e.g.: building, landuse; for further info see TagInterpreter of the OSHDB or List of polygon features
  • other is a geometry-collection and uses relation, e.g.: turn restrictions

Hello dear friends of disaster mapping,

Another busy disastermappers heidelberg year is coming to an end. After events and meetings in  Heidelberg as well as Würzburg, Kiel, Salzburg and Berlin all around the topic of disaster mapping, we want to use the start in the Advent season to get feedback on the past events and discuss new ideas with you.

For this purpose, we invite you to join our open disastermappers meeting next Tuesday, December 3rd, 6.30 pm, in relaxed atmosphere in Café Botanik.

Everyone is welcome to join and the meeting is also a great opportunity to get a first impression of disaster mapping.

If you do not already know us, look for Missing Maps Shirts ;-)

We are looking forward to seeing you there,

your disastermappers

An der Schnittstelle von Wissenschaft und Gesellschaft positioniert sich das TdLab Geographie in dieser Woche mit zwei Aktivitäten.

Am 25.11.2019 präsentierte Dr. Nicole Aeschbach gemeinsam mit Prof. Dr. Werner Aeschbach (Institut für Umweltphysik, Universität Heidelberg) im Rahmen eines sehr gut besuchten Vortrags bei der von Students for Future und Fridays for Future Heidelberg organisierten „Public Climate School“ naturwissenschaftliches Basiswissen zum anthropogenen Klimawandel. Der Vortrag bot einen Überblick über die Klimaentwicklung der letzten 150 Jahre und über die Klimafolgen heute und in Zukunft. Es wurde erläutert, welche klaren Belege für den menschlichen Fußabdruck im Klimasystem sprechen und warum ohne eine zügige Dekarbonisierung die international vereinbarten Klimaziele nicht zu halten sind.

In einem am 27.11.2019 erschienenen Gastbeitrag in der Rhein-Neckar-Zeitung reflektiert Dr. Nicole Aeschbach zusammen mit Maximilian Jungmann (Heidelberg Center for the Environment) und Prof. Dr. Sebastian Harnisch (Institut für Politische Wissenschaft, Universität Heidelberg) die Rolle der Wissenschaft im aktuellen Diskurs zum Klimawandel.

HeiGIT|GIScience HD beteiligt sich auch dieses Jahr am Fachaustausch geoActive (28.11.2019,  12.00 - 16.00 Uhr, halle02, Heidelberg) des GeoNet.MRN. In diesem Jahr werden wir als Teil des Open Space Konzeptes den aktuellen Stand der App meinGrün vorstellen und Informationen zu den Hintergründen des Projektes liefern.

Das Projekt hat es sich als Ziel gesetzt, die Nutzung urbaner Grünflächen zu vereinfachen. Die hierfür in Entwicklung befindliche mobile App ermöglich einerseits die Suche nach geeigneten Grünflächen anhand verschiedener Kriterien der Grünflächen. Auf der anderen Seite schlägt die App zudem angenehme (grüne, ruhige,…) Routen für den Weg zur ausgewählten Grünfläche vor. Grundlage der Navigation ist der OpenRouteService.

Weitere Informationen zum Projekt unter meinGrün - Informationen und Navigation zu urbanen Grünflächen in Städten sowie im SotM Vortrag von Christina Ludwig:
Assessing the Completeness of Urban Green Spaces in OpenStreetMap

Die Arbeiten werden zusätzlich durch Studien in Nature Neurocience motiviert, die den direkten Zusammenhang zwischen innerstädtischen Grünflächen und dem Wohlbefinden und der mentalen Gesundheit der Stadtbewohner belegen:

H. Tost, M. Reichert, U. Braun, I. Reinhard, R. Peters, S. Lautenbach, A. Hoell, E. Schwarz, U. Ebner-Priemer, A. Zipf, and A. Meyer-Lindenberg (2019): Neural correlates of individual differences in affective benefits of real-life urban green space exposure. Nature Neuroscience (published online 29 July 2019). https://doi.org/10.1038/s41593-019-0451-y

These findings motivate also our work on pleasant route planning that suggest user-dependent pedestrian routes that have particularly high shares of green areas or particularly low noise levels:

Novack, T.; Wang, Z.; Zipf, A. (2018): A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors 2018, 18, 3794


CALL FOR PAPERS for the GIS track at

17th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2020)

May 24-27, 2020, Virginia, USA


Geospatial Technologies and Geographic Information Science for Crisis Management (GIS)


Deadline for paper submissions: December 6, 2019

Track Description

With disasters and disaster management being an “inherently spatial” problem, geospatial information and technologies have been widely employed for supporting disaster and crisis management. This includes SDSS and GIS architectures, VGI, spatial databases, spatial- temporal methods, as well as geovisual analytics technologies, which have a great potential to build risk map, estimate damaged areas, define evacuation routes, and plan resource distribution. Collaborative platforms like OSM have been also employed to support disaster management (e.g., near real-time mapping). Nevertheless, all these geospatial big data pose new challenges for not only geospatial data visualization, but also data modeling and analysis; existing technologies, methodologies, and approaches now have to deal with data shared in various formats, different velocities, and uncertainties. Furthermore, new issues have been also emerging in urban computing and smart cities for making communities more resilient against disasters. In line with this year’s conference theme, the GIS Track particularly welcomes submissions addressing aspects of individual-centric geospatial information in disaster risk and crisis research. This includes SDSS, near-real-time mapping, situational awareness, VGI, spatiotemporal modeling, urban computing, and other related aspects. We seek conceptual, theoretical, technological, methodological, empirical contributions, as well as research papers employing different methodologies, e.g., design- oriented research, case studies, and action research. Solid student contributions are welcome.

Track topics are therefore focused on - but not limited to - the following list:

1. Geospatial data analytics for crisis management

2. Location-based services and technologies for crisis management

3. Geospatial ontology for crisis management

4. Geospatial big data in the context of disaster and crisis management

5. Geospatial linked data for crisis management

6. Urban computing and geospatial aspects of smart cities for crisis management

7. Spatial Decision Support Systems for crisis management

8. Individual-centric geospatial information

9. Remote sensing for crisis management

10. Geospatial intelligence for crisis management

11. Spatial data management for crisis management

12. Spatial data infrastructure for crisis management

13. Geovisual analytics for crisis management

14. Spatial-temporal modeling in disaster and crisis context

15. Crisis mapping and geovisualization

16. Collaborative disaster mapping

17. Public policies for geospatial information

18. Empirical case studies

Important Dates

Full research and insight papers:

– Submission deadline: December 6, 2019

– Decision notification: January 17, 2020

Short (WiPe) papers and Practitioner papers:

– Submission deadline: January 28, 2020

– Decision notification: February 28, 2020

Paper submission guidelines


Track Chairs

Prof. Dr. João Porto de Albuquerque (primary contact)

University of Warwick, United Kingdom


Prof. Dr. Alexander Zipf

University of Heidelberg, Germany

Dr. Flávio Eduardo Aoki Horita

Federal University of ABC, Brazil‌

On November 12-13, Jannika Schäfer from KIT presented the SYSSIFOSS project at the 2nd symposium on satellite-based earth obersvation (2. Symposium zur angewandten Satellitenerdbeoachtung) in Cologne.

SYSSIFOSS is a joint project between the Institute of Geography and Geoecology (IFGG) of the Karlsruhe Institute of Technology (KIT) and the 3DGeo Research Group of Heidelberg University.

In this project a new approach to create synthetic LiDAR data is suggested by combining the outputs of an established forest growth simulator with a to-be-created database of species-specific model trees extracted from real LiDAR point clouds. This approach will result in inventory information at the single tree level and a matching 3D forest structure for large areas.

The presented poster can be found here:

Schäfer, J., Faßnacht, F., Höfle, B. & Weiser, H.(2019): Das SYSSIFOSS-Projekt: Synthetische 3D-Fernerkundungsdaten für verbesserte Waldinventurmodelle. In: 2. Symposium zur angewandten Satellitenerdbeoachtung, Cologne, Germany, pp.1-1.

After a busy summer of data acquisition (UAV-borne and terrestrial laser scanning, field inventories), the team is now working on combining the different data sources, segmenting individual trees, exctracting tree parameters and generating tree models for virtual scanning. Moreover, a database of species-specific model trees will be set up. Find some first impressions of the acquired data below.

Find more details on the SYSSIFOSS project on the project website and in recent blog posts.

The project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number: 411263134.

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