Feed on

We published a new jupyter notebook which depicts how to use the OpenRouteService Isochrones API to analyse health care acessibility in Madagascar.

In the case of a disaster (natural or man made), a country is not only affected by the intensity of the disaster but also by it’s own vulnerability to it. Countries have different kind of opportunities to prepare for such catastrophes, to respond finally to start the recovery. Many less developed countries, e.g. Madagascar, are in particular prone to disasters, not only because of the higher probability of occurence, but also due to a potentially lower ability to cope up during and after the event.

In this example we will focus on vulnerability in terms of access to health care. The access to health facilities can be highly unequal within a country. Consequently, some areas and communities are more vulnerable to disasters effects than others. Quantifying and visualizing such inequalities is the aim of this notebook.

The notebook gives an overview on health sites distribution and the amount of population with access to those by foot and by car for Madagascar. Open source data from OpenStreetMap, the Humanitarian Data Exchange platform and tools (such as the OpenRouteService) were used to create accessibility isochrones for each hospital and to derive analysis results about the population percentage with access to health facilities per district. The findings show that the inhabitants of 69 of 119 (58%) districts don’t have any access to hospitals in an one hour foot walking range and those of 43 of 119 (36%) districts in an one hour car driving range.

Figure 1: Input Datasets from the Humanitarian Data Exchange portal

Figure 2: Isochrones from OpenRouteService API and health care accessibility per district


  • Preprocessing: Get data for districts, health facilities, population density, population count per disctrict.
  • Analysis: Compute accessibility to health care facilities using OpenRouteService API, Derive the percentage of people with access to health care per district.
  • Results: Visualize results as choropleth maps.
Datasets and Tools:

As part of the practical field training “3D Geodatenerfassung im Hochgebirge (Ötztal)”, 29
July - 04 August, 16 students explore pyhsical geography in an impressive high-mountain
environment in the Ötztal valley, Austria.

With the help of terrestrial LiDAR, RTK GNSS, close range photogrammetry and electrical resistivity tomography (ERT), multi-source datasets will be captured for the analysis of surface and subsurface characteristics of different landforms (e.g. a glacier and a moraine). After exhausting field work the Obergurgl University Center provides us with great accommodation and a perfect working environment for data processing.

Yesterday the field trip has started with an overview hiking tour from Obergurgl via Hohe Mut mountain to the Rotmoosferner glacier in the beautiful Rotmoos valley. Find some impressions in the pictures below.

Today one group captured the lower tongue area of the Rotmoosferner glacier with terrestrial LiDAR. A second group measured an ERT profile across an end moraine of the Rotmoosferner glacier from the year 1850. A third group did photogrammetric and RTK GNSS measurements around the area of this end moraine.

We will keep you updated about the field trip with daily posts - stay tuned!

P.S.: You would like to experience this impressive high-mountain environment yourself and
are interested in innovative geodata processing methods in mountain research? Then
the Innsbruck Summer School of Alpine Research 2019 is the perfect opportunity!
Find impressions of the first and second editions of the
now established Summer School of Alpine Research.

Maps, maps, maps! After a great state of the map conference in Milan, the OpenStreetMap community can already get excited for the next global gathering in 2019:

We are very honored to have been selected to welcome the global OSM community in Heidelberg in 2019!

The good news have been shared during the closing ceremony of the 2018 State of the Map conference in Milan where more than 400 OSM enthusiasts gathered to discuss current topics, ideas and projects all around OSM.

We are very looking forward to further planning with the SotM Organizing Committee and OSM Foundation and most of all to inviting the global OSM community to our beautiful city.

Stay tuned for updates, and already make sure to save the date: September 21 to 23, 2019.

Group picture of attendees of SotM 2018.

Group picture of attendees of SotM 2018.

Looking forward to welcome you in Heidelberg soon!

In a few days - THIS Saturday July, 29. - the State of the Map 2018 Conference in Milan will opening its doors with many interesting talks and workshops related to OpenStreetMap. HeiGIT and the GIScience Research Group at Heidelberg University will be there with several persons and give the following presentations and even a hands-on workshop about the recently introduced Ohsome plattform. Stay tuned for great upcoming news about it ;-)
In these blogposts (1 , 2 , 3 , 4, 5)  you can read a bit background information on Ohsome and there are also related research papers (A, B ) with examples of using the Ohsome technology.

We are looking forward to meeting you there! Contact us at info@heigit.org if you are interested in getting to know more about the ohsome framework.

More information will be presented a at the State of the Map Conference 2018, Milan. Looking forward to see you there! Stay tuned for further updates!

Related work:


Auer, M.; Eckle, M.; Fendrich, S.; Griesbaum, L.; Kowatsch, F.; Marx, S.; Raifer, M.; Schott, M.; Troilo, R.; Zipf, A. (2018): Towards Using the Potential of OpenStreetMap History for Disaster Activation Monitoring. ISCRAM 2018. Rochester. NY. US.


Auer, M.; Eckle, M.; Fendrich, S.; Loos, L.; Kowatsch, F.; Marx, S.; Raifer, M.; Schott, M.; Troilo, R.; Zipf, A. (2018): Eine Plattform zur Analyse raumzeitlicher Entwicklungen von OpenStreetMap-Daten für intrinsische Qualitätsbewertungen. AGIT Symposium, Salzburg, Austria.

Further Work:

Mocnik, F.-B., Mobasheri, A., Zipf, A. (2018): Open source data mining infrastructure for exploring and analysing OpenStreetMap.Open Geospatial Data, Software and Standards.

Mocnik, F.-B., Zipf, A., Raifer, M. (2017): The OpenStreetMap folksonomy and its evolution. Geo-spatial Information Science. DOI: 10.1080/10095020.2017.1368193.

3D WebGIS systems have been mentioned in the literature almost since the beginning of the graphical web era in the late 1990s. The potential use of 3D WebGIS is linked to a wide range of scientific and application domains, such as planning, controlling, tracking or simulation in crisis management, military mission planning, urban information systems, energy facilities or cultural heritage management, just to name a few. Nevertheless, many applications or research prototypes entitled as 3D WebGIS or similar are mainly about 3D visualization of GIS data or the visualization of analysis results, rather than about performing the 3D analysis itself online. A recently published research paper aims to step forward into the direction of web-based 3D geospatial analysis. It describes how to overcome speed and memory restrictions in web-based data management by adapting optimization strategies, developed earlier for web-based 3D visualization. These are applied in a holistic way in the context of a fully 3D line-of-sight computation over several layers with split (tiled) and unsplit (static) data sources. Different optimization approaches are combined and evaluated to enable an efficient client side analysis and a real 3D WebGIS functionality using new web technologies such as HTML5 and WebGL.
To ensure comparable test conditions, an artificial dataset has been created, simulating a LiDAR derived Digital Terrain Model. Further, an evaluation framework was set up to measure performance and memory consumption during four different test scenarios. The results show that the applied approach with its holistic view onWebGIS usage and its two levels of optimization (layer-level and tile-level) lead to greatly improved performance, while the streaming and partitioned way of processing of the data leads to an independence between memory consumption and the length of the line-of-sight as well as the resolution of input data, thus showing that the approach is scalable, which is important, especially in web-based environments.

Auer, M.; Zipf, A.(2018): 3D WebGIS: From Visualization to Analysis. An Efficient Browser-Based 3D Line-of-Sight Analysis. ISPRS Int. J. Geo-Inf. 2018, 7, 279.

Modeling the geographic distribution of tourists at a tourist destination is crucial when it comes to enhancing the destination’s resilience to disasters and crises, as it enables the efficient allocation of limited resources to precise geographic locations. Seldom have existing studies explored the geographic distribution of tourists through understanding the mechanisms behind it. In a recently published article we propose to couple maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists in order to facilitate disaster and crisis management at tourist destinations. As one of the most popular tourist destinations in the United States, San Diego was chosen as the study area to demonstrate the proposed approach. We modeled the tourist geographic distribution in the study area by quantifying the relationship between the distribution and five environmental factors, including land use, land parcel, elevation, distance to the nearest major road and distance to the nearest transit stop. The geographic distribution’s dependency on and sensitivity to the environmental factors were uncovered. The model was subsequently applied to estimate the potential impacts of one simulated tsunami disaster and one simulated traffic breakdown due to crisis events such as a political protest or a fire hazard. As such, the effectiveness of the approach has been demonstrated with specific disaster and crisis scenarios.

Yingwei Yan , C.-L. Kuo, C.-C. Feng, W. Huang, H. Fan & A. Zipf (2018) : Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists. International Journal of Geographical Information Science (IJGIS), https://doi.org/10.1080/13658816.2018.1458989

Related earlier work
Yan, Y., M. Eckle, C.-L. Kuo, B. Herfort, H. Fan and A. Zipf (2017): Monitoring and Assessing Post-Disaster Tourism Recovery Using Geotagged Social Media Data. International Journal of Geo-Information, ISPRS IJGI. 6(5), 144; doi:10.3390/ijgi6050144

Our PLATIAL’18 workshop on place-based analysis in September is approaching quickly, and so is the submission deadline. Please be aware that the call closes next week:

Wednesday, 25 July 2018, 11.59 pm (CEST)

Looking forward to your valuable submissions and participation!

Another chapter in machine human fusion land use device narrative: new Sentinel 2 osmlanduse.org product results based on OpenStreetMap plus Sentinel 2 data plus Machine Learning were presented at ToulouseSpaceShow 2018 during a European Space Agency (ESA) Research and User Support (RUS) event. Stay tuned: The new product will soon be available for all EU countries @10m resolution using Corine Land cover/use nomenclature! https://photos.app.goo.gl/7rgRwNa2ZW4YqRMp9 # photos + slides from the event https://www.toulousespaceshow.eu/tss18/ # Toulouse space show 18 https://rus-copernicus.eu/portal/ # RUS service Related earlier work:

Schultz, M., Voss, J., Auer, M., Carter, S., and Zipf, A. (2017): Open land cover from OpenStreetMap and remote sensing. International Journal of Applied Earth Observation and Geoinformation, 63, pp. 206-213. DOI: 10.1016/j.jag.2017.07.014

Novack, T., J. Voss, M. Schultz, A. Zipf (2018, accepted): Associating OpenStreetMap tags to CORINE land-cover classes using text and semantic similarity measures. VGI-ALIVE Workshop at AGILE 2018. Lund, Sweden.

Chen, J., Zipf, A. (2017): Deep Learning with Satellite Images and Volunteered Geographic Information. In: Karimi, H. A. and Karimi, B. (eds.): Geospatial Data Science: Techniques and Applications. Taylor & Francis.Jokar Arsanjani, J., Mooney, P., Zipf, A., Schauss, A., (2015): Quality assessment of the contributed land use information from OpenStreetMap versus authoritative datasets. In: Jokar Arsanjani, J., Zipf, A., Mooney, P., Helbich, M., OpenStreetMap in GIScience: experiences, research, applications. ISBN:978-3-319-14279-1, PP. 37-58, Springer Press.

Dorn, H., Törnros, T. & Zipf, A. (2015): Quality Evaluation of VGI using Authoritative Data – A Comparison with Land Use Data in Southern Germany. ISPRS International Journal of Geo-Information. Vol 4(3), pp. 1657-1671, doi: 10.3390/ijgi4031657

Jokar Arsanjani, J., Helbich, M., Bakillah, M., Hagenauer, J., & Zipf, A. (2013). Toward mapping land-use patterns from volunteered geographic information. International Journal of Geographical Information Science, 2264-2278. DOI:10.1080/13658816.2013.800871.

FOSS4G Europe as the European community event on free and open source gis is taking place this week July 16 to 20th, 2018 in Guimarães Portugal.
A. Zipf is giving a talk about supporting personalised pedestrian routing options (like healthy and quiet routing) as well as wheelchair routing and navigation based on open source and open data. He’ll share how this is being realized in Openrouteservice using mainly OSM data.

Recent examples with main contributors from HeiGIT and GIScience Heidelberg include healthy greenquiet routing, Landmark based navigation, routing across open spaces and much more… E.g. for the ORS API exists a QGIS plugin, geoJSON support, a very handy Python library and a library for R users for all service from routing (directions), isochrones, geocoding, POI search, to time-distance matrixes. Enjoy! and contribute: open source code in GitHub

Try ORS API: https://go.openrouteservice.org

or ORS Online Clienthttps://maps.openrouteservice.org


Flood events caused serious harm in wide areas of Japan and Sri Lanka over the last couple of weeks. Heavy rain, floods and landslides occured in South West area of Japan and monsoon rains have caused severe flooding in the Kurunagala and Puttalam districts of Sri Lanka.

The Humanitarian OpenStreetMap Team (HOT) has received requests from the Japan Red Cross Society as well as from the Disaster Management Centre of Sri Lanka to trace buildings in the inundated areas.

disastermappers heidelberg and HeiGIT/GIScience Research Group invite you to our end of semester Mapathon to support HOT in these efforts! In contrast to previous events, this time you will not only learn about OpenStreetMap (OSM) and how to contribute, but also get familiar with OSM data validation.

Why? Map data creation is crucial in disaster scenarios and the contributed data can help first responders and the local community to coordinate efforts. The value of OSM data furthermore increases when it is reviewed and lessons learned are ultimately applied. Accurate maps can then help to enable confident use of the data.

Russ Deffner, HOT Associate Project Manager and Activation Working Group, will also be joining use via Skype and provide insights about the projects and the use of the data on the ground.


When?       Thursday 19.07.2018, 6 pm

Where?     Großer Hörsaal, Geographisches Institut, Berliner Straße 48

As usual, we will provide an introduction to OSM mapping, therefore there is no previous knowledge needed. Additionally, an introduction into validation of OSM data in the Tasking Manager is offered.

We also reserved the PC Pools, however due to limited availability, bring your own laptop and mouse if available.

Snacks and drinks will for sure be provided!

To round up the Mapathon and enable further get together and exchange, we will moreover fire up the BBQ! Therefore, make sure to bring your ribs or veggies.

We are looking forward to seeing you on Thursday,

your disastermappers

« Newer Posts - Older Posts »