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Call for Abstracts: 4th PhD Colloquium on “Deep Learning in Photogrammetry, Remote Sensing and Geospatial Information Processing”

May 15-16, 2019 in Rostock

The Division on Geoinformatics (Abteilung Geoinformatik) of the German Geodetic Commission (Deutsche Geodätische Kommission, DGK) and the Working Group on Geoinformatics (Arbeitskreis Geoinformatik) of the German Society for Photogrammetry, Remote Sensing and Geoinformation (Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation, DGPF) will hold their fourth joint PhD colloquium on May 15-16, 2019, at Rostock University.

The colloquium aims to stimulate scientific exchange between young researchers in the interdisciplinary fields of photogrammetry, remote sensing, cartography, geoinformatics and others. It is targeted at PhD students who have already made considerable advances in their PhD projects and are motivated to share their findings as well as open for feedback and discussions. PhD students from all disciplines dealing with geospatial information processing (e.g., geoinformatics, photogrammetry, computer science, cartography, geography, remote sensing, etc.) are welcome.

We particularly invite PhD students working on problems related to the following focus topic of this year’s PhD colloquium “Deep Learning in Photogrammetry, Remote Sensing and Geospatial Information Processing”.

Contributions must adhere to the following guidelines:

  • Each contribution must be summarized and submitted in form of an abstract of about two pages. Based on the submissions PhD students will be invited.
  • Each accepted abstract will be presented either in a short (5 minute) talk or in a full-length talk of approx. 30 minutes.
  • We encourage presenters of both short and full-length talks to address open problems rather than to report their published results.

The language of the colloquium is English. The colloquium will be chaired by multiple professors from geoinformatics.

Advanced PhD lectures on the focus topic will be given by Prof. Franz Rottensteiner (University of Hannover) and Prof. Ribana Roscher (University of Bonn).

Participation is free of charge. Applications (including name, affiliation, and abstract) are to be sent by January 27, 2019 via e-mail to Jan-Henrik Haunert (haunert@igg.uni-bonn.de).

The Organizers:

  • Prof. Dr.-Ing. Jan-Henrik Haunert, Bonn
  • Prof. Dr. Bernhard Höfle, Heidelberg
  • Prof. Dr.-Ing. Ralf Bill, Rostock

Welcome back to the second part of the blog series how to become ohsome. If you have not read the first part yet, better go and check it out now. It explains how you can create an ohsome visualization of the historical development of the OSM data from a city of your choice.

This second part shows how to use historical OSM data from the ohsome API to compare different regions based on their attribute completeness. We will look at streets (every way with a highway key) and compute the ratio of streets having the tag surface=* divided by all streets. This will give us an insight on the attributive completeness for the tag surface=*. The response will be visualized in diagrams to be easily understandable and interpretable. Two main steps are necessary to achieve that:

1) Get the OSM data using the ohsome API

Using a lately implemented feature, the csv data extraction, we send a request to the Germany instance of the ohsome API with the following parameters:

bpolys = geojson // spatial parameter using a GeoJSON FeatureCollection containing data from Bamberg, Karlsruhe and Köln (you find a link to the data below)

time = 2008-01-01/2018-01-01/P1Y  // temporal parameter using the format startTimestamp/endTimestamp/intervalSize

types = way

keys = highway

types2 = way

keys2 = highway,surface

format = csv

By accessing the /length/ratio/groupBy/boundary resource, we get the absolute values plus the ratios grouped by the given boundary information, in this case: The administrative boundaries of the cities Bamberg, Karlsruhe and Köln.

We store the parameters in a text file and use cURL to send an HTTP Post request to the API. The response gets stored in a simple csv file. Here you can find the used parameters, the curl command, as well as the returned response.

2) Load response into Excel and create diagrams

Once we have the csv data, it only needs to be imported into some spreadsheet software like e.g. Excel. As the data is already in an adequate form to produce diagrams, we can do that directly by marking the respective columns and just creating them.

The first two diagrams show the length of OSM ways in meters tagged with the key highway (1) and those with the keys highway and surface (2).



When we compare these two charts, we can see that the level of saturation of the curves (when there is no more significant incline) is reached at different points in time, or not at all. This effect occurs when not many edits of a certain tag are performed (but there is still overall mapping activity in that region, as explained in Neis et al. 2011, 2012, Barron et al. 2013), e.g. when most streets of a region most likely have already been mapped. Karlsruhe and Köln though have not reached their level of saturation yet when looking at the second diagram, in contrary to Bamberg, in spite of their active mapping community.

This situation is also reflected in the last diagram (3) showing the ratio between these graphs for every region.


Here we clearly see that the ratio is highest for Bamberg. At the beginning of 2018, about 75% of the mapped streets in Bamberg had the surface tag. What is also visible here (like in diagram 2) is the positive trend of the other two graphs. More and more streets in Karlsruhe and Köln get the information about its surface added to them. This implies that the attributive completeness when looking at the tag surface=* is increasing for these cities. What we cannot say here though is if the added tags comply to defined standards. This topic was tackled in two other recently published posts, also dealing with the spatial version of compliance.

This blog post showed you how you can extract historical OSM data, visualize it and make simple statements about its quality and trend. You can also check out one of our dashboards, another easy to use component built on top of the ohsome framework. To contact us, just write us an email to info@heigit.org. Keep tuned for the next blog of the ohsome series, which is already in the pipeline and will take a look at varying mapping behaviors for different regions.

From 01-04 April 2019, the 3DGeo and FCGL research groups are organizing a compact course and workshop on Spatial and Temporal Analysis of Geographic Phenomena (STAP19) at the Interdisciplinary Center for Scientific Computing (IWR, Heidelberg University).

The course will teach participants state-of-the-art methods of 3D spatial data processing and analysis with a focus on spatial and temporal analyses in geographic applications. There will be a mix of lectures and hands-on sessions led by multiple researchers from the organizing groups. Core contents are:

  • Automatic methods for 3D geospatial data processing
  • Geographic applications of 3D data analysis
  • Hands-on: 3D point cloud and mesh analysis
  • Programming and research challenge: Development of computational methods for 3D information extraction

As highlight, we are welcoming two invited speakers:

Seize the opportunity to learn from and discuss with a project leader of 3DTK and a main developer of HELIOS - two powerful (and open!) 3D processing tools!

We are looking forward to meeting interested 3D-enthusiasts! Registration is now open.

Stay tuned for further information coming soon! Keep updated on this blog and Twitter: #STAP19

Find further information and a first peek on the program on the website: https://www.uni-heidelberg.de/stap19

All motivated PhD and master students from Geoinformatics, Geography, Computer Science and related fields are cordially invited to register. Please note that participants not enrolled at Heidelberg University or member of HGS MathComp are required to pay a participation fee (find details on the STAP19 website).

STAP19 is in part supported by the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (HGS MathComp), founded by DFG grant GSC 220 in the German Universities Excellence Initiative.

Our workshop GeoCultGIS - GEOgraphical and CULTural aspects of Geo-data: Issues and Solutionshas been accepted for the 22nd AGILE Conference on Geo-information Science, the annual conference of the Association of Geographic Information Laboratories in Europe (AGILE). The event will be held in Limassol, Cyprus on 17-20 June, 2019.

Workshop theme:

While some geo-datasets offer global coverage and spatial methods attempt to be generic, applications frequently are of local nature. Local geographic and social-cultural idiosyncrasies lead to heterogeneity in data production practices and in interpretations of abstract geographical concepts. This, in its turn, limits the transferability of methods and theoretical approaches. In this workshop, the challenges involved and the general conceptual, methodological, technical, and empirical approaches for tackling such issues will be discussed. This workshop will thus contribute to the strengthening and networking of a community of geo-information researchers and practitioners facing and attending to these issues. While some geo-datasets offer global coverage and spatial methods attempt to be generic, applications frequently are of local nature. Local geographic and social-cultural idiosyncrasies lead to heterogeneity in data production practices and in interpretations of abstract geographical concepts. This, in its turn, limits the transferability of methods and theoretical approaches. In this workshop, the challenges involved and the general conceptual, methodological, technical, and empirical approaches for tackling such issues will be discussed. This workshop will thus contribute to the strengthening and networking of a community of geo-information researchers and practitioners facing and attending to these issues.


We encourage participants to submit short papers presenting conceptual and methodological developments, applications or study cases, and critical reviews which discuss the effects of geo-social-cultural aspects on the production, usage and analysis of collaborative, user-generated and authoritative geo-datasets.


Dr.-Ing. Tessio Novack, GIScience, Heidelberg University

Dr. A. Yair Grinberger, GIScience, Heidelberg University

Dr. Michael Schultz, GIScience, Heidelberg University

Prof. Dr. Alexander Zipf, GIScience, Heidelberg University

Dr. Peter Mooney, Department of Computer Science, Maynooth University

Sty tuned for further details and updates.

Ecosystem service research is high on the policy agenda. Strategies to synthesize individual success stories and derive generalized results to provide guidance for policymakers and stakeholder is central to many science-policy initiatives, such as IPBES, ELD, WAVES and TEEB. However, to successfully transfer knowledge from ES case studies to environmental policies, it is necessary to develop a sound knowledge base with respect to effects of global change on the provisioning of ES

Together with colleagues from Free University of Amsterdam, the Helmholtz Centre for Environmental Research, the Universities of Freiburg, Bonn and the KIT we identified blind spots in ecosystem service research that might hinder the generalization. Details can be found in a recent journal paper.

The analysis was structured along five facets that characterize the holistic ideal of ecosystem services research: (i) social-ecological validity of ecosystem data and models, (ii) consideration of trade-offs between ecosystem services, (iii) recognition of off-site effects, (iv) comprehensive and shrewd involvement of stakeholders, and (v) relevance and usability of study results for the operationalization of the ecosystem service concept in practice. Results show that these facets were not addressed by the majority of case studies including more recent studies.

Among the key findings are:

  • Geographic coverage of ecosystem service studies was uneven – large parts of the global south are underrepresented which is in contrast to the large value that their ecosystems produce.
  • Coverage of the different ecosystem services wass uneven – this leads potentially to suboptimal decision making since important ecosystem services stay unevaluated.
  • Uncertainty of model results was often unquantified. Validation of model results was missing frequently.
  • Assessments concentrated on the current situation ignoring future developments.
  • Most studies did not provide specific recommendations for decision making or environmental management.
  • Off-site effects were rarely considered.
  • Mapping of ecosystem services relied in many studies on land use composition, ignoring the important aspects of land use configuration and land use intensity.
  • Aspects of the demand for ecosystem services (beneficiaries) were analyzed in a minority of studies.
  • Stakeholders were only involved in about 40% of the studies.
  • Trade-offs and interactions between ecosystem services were only analyzed in a minority of the studies analyzed.
The size of the countires reflects the number of ecosystem service studies in the analyszed sample (n=504). Countries that were not included in our sample or not displayed. It is clearly visible that the EU, the USA and China are relatively well studied while many countries in the global south are not well represented.

DIstribution of ecosystem service studies at the country level. The size of the countires reflects the number of ecosystem service studies in the analyszed sample (n=504). Countries that were not included in our sample or not displayed. It is clearly visible that the EU, the USA and China are relatively well studied while many countries in the global south are not well represented.

To effectively operationalize the concept of ecosystem services, the blind spots need to be addressed by upcoming studies. Therefore, we provided a list of critical questions to raise the awareness of the blind spots both for synthesis of existing knowledge and for future research agendas. Clusters of ecosystem services studied together were prone to different blind spots – learning across those research clusters might offer potential for improvement.

Lautenbach, S., Mupepele, A.-C., Dormann, C. F., Lee, H., Schmidt, S., Scholte, S. S.K., Seppelt, R., van Teeffelen, A. J.A., Verhagen, W., Volk, M. (2019): Blind spots in ecosystem services research and implementation, Regional Environmental Change, doi.org/10.1007/s10113-018-1457-9

The GIScience group cordially invites everybody interested to our next open GIScience colloquium talk about:

The German Red Cross (GRC) is part of the worldwide Red Cross and Red Crescent Movement with its presently 191 recognized National Red Cross or Red Crescent Societies. A major focus of the GRC’s international cooperation is on supporting the most vulnerable people around the world in addressing the impacts of natural hazards like tsunamis or floods. The presentation is going to give insights into approaches and activities in the area of Disaster Risk Reduction. Nevertheless it is also supposed to trigger a dialogue about how humanitarian organizations like GRC could strengthen their work through the use and the integration of Geographic Information Systems.

Last year the German Red Cross and GIScience HD/HeiGIT signed a Memorandum of Understanding to strengthen the strategic partnership to conduct joint activities related to research as well as development of GIS technologies, skills, workflows and communities. Over the past GIScience/HeiGIT have already supported the GRC through presentations, e.g. at the Dialogue Platform German Conference on Disaster Risk Reduction (“Fachtagung Katastrophenvorsorge), and the organization of mapathon events. Furthermore, the organizations have already published a joint journal paper about Missing Maps, also involving the British Red Cross. HeiGIT is happy to share and extend the tools and services related to humanitarian activities such as (openrouteservice for disaster management, ohsome analytics for disaster management, MapSwipe Analytics, deepVGI etc.) in order to improve the work on disaster risk reduction together with the Red Cross.

Feel most welcome to join the event!

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 Sensing 2018, 10(8), 1239, doi: 10.3390/rs10081239.

State of the Map 2019 conference will be held in Heidelberg, September 21-23 2019.

Interested in sponsoring?
Want to help build bridges through scholarships?
Sponsorship packages are available at

Special issue information:

The last decade has seen a rapid growth in open source geospatial software and data developments. Open geospatial data applies the principles of free and openness to geospatial information, allowing communities to collaborate on a data product. Applying the lessons learned in the open source industry to geo-data collection and maintenance has led to a new generation of data products. This is more than publishing information for free access. Open data provides a mechanism for participants to contribute back as equal partners in data collection and review. Nowadays, open data play a fundamental role especially that data science and Artificial Intelligence (AI) methods are becoming so pivotal in science development. Examples of successful open geo-data platforms include OpenStreetMap and Natural Earth, to name a few.

Open Education applies the principles of open source to the creation of teaching materials allowing organizations to share syllabus materials with the aims of reducing costs and reaching a wider audience. Promoting collaboration between involved parties is central to open education. As the Open Education Consortium says: “sharing is probably the most basic characteristic of education: education is sharing knowledge, insights and information with others, upon which new knowledge, skills, ideas and understanding can be built.”

Free and Open Source Geospatial Software addresses the design, implementation, characterization, and use of open tools for geospatial and environmental analysis, mapping, remote sensing, and spatial information science. Open standards are the key to developing sustainable software. Open standards promote interoperability between applications, organizations, and fields of endeavor. Open standards are key tools allowing geospatial practitioners to work together, with the added benefit of avoiding technology lock-in.

Finally, Open Science combines all these ideas by both sharing the data used to support a conclusion, alongside the code and/or the parameters used with an open source software for carrying out the analysis. This leads to the development of innovative concepts and standards based on free and open source software for scientific global inter-disciplinary research, as well as for education and business projects.

We invite original research contributions on all aspects of open source geospatial science, software, and education, as well as its applications. We particularly encourage submissions focusing on the following themes:

  • Architectures and frameworks for open source software and data
  • The use of open source geospatial software and data, in and for scientific research
  • Open source implementations and Open SDI
  • Human computer interfaces and usability in and around Open GI systems
  • Use of Open Data and Big Data in research projects
  • Open data and Artificial Intelligence (AI) in Geospatial Applications
  • Open Geospatial Data quality
  • Open Source Software quality
  • Open Geospatial Standards
  • Crowdsourced Geographic Information and Participatory GIS
  • Teaching geospatial sciences with open source solutions and open data
  • Open Source GIS application use cases: environment, climate change, health, energy, government, participatory GIS, location based services, etc.

Important Dates:

Abstracts Due: 15/02/2019 (by email to: a.mobasheri@uni-heidelberg.de)
Approved Abstracts: 01/03/2019 (put as planned papers online)
Manuscripts Due: 31/08/2019
Decision to Authors: 15/11/2019
Final Papers Due: 31/01/2020

Guest Editors:

Amin Mobasheri, GIScience research group, Heidelberg University, Germany (a.mobasheri@uni-heidelberg.de)

Helena Mitasova, Center for Geospatial Analytics, NC State University, USA

Markus Neteler, mundialis GmbH & Co. KG, Germany

Alex Singleton, Department of Geography and Planning, University of Liverpool, UK

Hugo Ledoux, 3D geoinformation, Delft University of Technology, the Netherlands

Maria Antonia Brovelli, GEOlab, Politecnico di Milano - DICA, Italy

You can also read the CfP in the journal website by clicking here.

The new year started in the openrouteservice team at HeiGIT with the release of openrouteservice 4.7.2. In this release there were a number of bug fixes, but also some new features. The main one of these is the inclusion of information about access restrictions when your route takes you over roads that are marked in OpenStreetMap as restricted (e.g. destination only roads, private roads etc.).

Destination access restrictions

Destination access restrictions

Road access restriction information

Destination access restrictions

Now whenever you request a route (through the map or the API) and the route generated crosses a restricted road, you will get information about the type of restriction and where it is. On the map page this appears in the bar on the left under the “Additional information” section, and in the API response it is in a new warning message object.

If you want to avoid obstacles from other data sources than OSM in a dynamic way per request you still have the option to use “avoidpolygons” or similar options both in the map client and the API as explained in this Jupyter notebook.

In the future we will be looking into other ways to use the new functionality, so keep an eye out for new things coming up in the near future.

For a full list of updated features in this release, see our changelog over in the openrouteservice GitHub repository.

Also, watch this space for information about a whole new API that is coming for openrouteservice in the near future.

We cordially invite everybody interested to our next open GIScience colloquium talk

The speaker is Prof. Dr. Silvio Jorge Coelho Simoes
Universidade Estadual Paulista Júlio de Mesquita Filho, Instituto de Ciência e Tecnologia - Campus de São José dos Campos, Brasil

When: Monday 14.01.2019, 2:15 pm

Where: INF 348, room 015 (Institute of Geography, Heidelberg University)

3D Model and Geovisualization for monitoring and prediction of landslides in Brazil - The RedeGeo Project (Cemaden and UNESP Collaboration)

Landslides have a high degree of uncertainty requiring new methods for their analysis, monitoring and forecasting. In Brazil, Cemaden (Brazilian Center for Early Warning and Monitoring for Natural Disasters) is responsible for actions related to natural disasters. Recently, a collaboration with Sao Paulo State University (UNESP) was started to study landslide-prone areas situated in different regions of the country. This talk presents the proposal of implanting a laboratory of modeling and geovisualization to improve the processes of analysis, monitoring and prediction of landslide phenomena that occur mainly in areas unsuited to habitation due to the geologic and geomorphologic conditions. The laboratory consists of three parts: A) Field surveys to obtain high resolution images from unmanned aerial vehicles and to obtain the internal geometry of outcrops from geophysics methods B) 3D modeling allowing the analysis of multivariate data such as superficial and sub-superficial geologic maps, boreholes, cross sections and geophysical data considering their volumetric properties; C) Geovisualization and Virtual Reality (VR) where the images obtained in the fieldwork can be observed from a human-machine interface which allows that the researchers have a full immersion in the selected areas. The creation of this laboratory related to the natural disasters including geovisualization and VR stimulates the active participation of the researcher team and creates mechanisms for the participation of technologies developers, managers, civil defense agents and even the population that lives in the risk-prone areas.

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