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The big spatial data analytics team at HeiGIT is currently developing the ohsome OpenStreetMap history analytics platform. Our aim is to make OSM’s full-history data more easily accessible for various kinds of data analytics tasks on a global scale.

OpenStreetMap (OSM) is a freely available map of the world to which everyone may contribute geographic information. This makes OSM a rich resource that is diverse with respect to feature variety and scale. At the same time, its data quality is of significant regional variance and also constantly changing over time. OSM’s richness makes it often difficult to assess OSM data quality extrinsically, i.e. by comparing it to external reference data sets because many of OSM’s features are not found in those data sets.

Analysing historical OSM data provides great insight into the evolution of the map. This supports assessing OSM data quality intrinsically, i.e., without comparing to other data sets. However, operating on OSM’s raw full-history data is complex and computationally intensive - especially on a global scale and while there are are several methods and tools for some specific purposes no general purpose software is available for such analyses.

The ohsome data analytics platform eases the analysis of OSM history data by providing high-level interfaces to different spatio-temporal data backends. As its central component, the HeiGIT big spatial data analytics team is developing the OpenStreetMap history database (oshdb), which applies big data technology in order to permit one to deploy the ohsome platform in a scalabe cluster computing environment.

Possible applications of the ohsome platform range from web dashboards over data quality assessment to custom data analysis.

Both ohsome and the oshdb are planned to be released as open source software during 2018.

This work is supported by the Klaus Tschira Foundation, Heidelberg. It builds upon earlier and current research on extrinsic and intrinsic OSM data quality analytics of the GIScience Research group and the growing international body of literature.

BTW: ohsome is pronounced awesome ;-)


Selected References:

Barron, C., Neis, P. & Zipf, A. (2013): A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis. Transactions in GIS, DOI: 10.1111/tgis.12073.

Ballatore, A. and Zipf, A. (2015): A Conceptual Quality Framework for Volunteered Geographic Information. COSIT - CONFERENCE ON SPATIAL INFORMATION THEORY XII. October 12-16, 2015. Santa Fe, New Mexico, USA. Lecture Notes in Computer Science, pp. 1-20.

Degrossi L.C., J. Porto de Albuquerque, R. dos Santos Rocha, A. Zipf (2018 accepted): A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information. Transactions in GIS. DOI:10.1111/tgis.12329

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

Jokar Arsanjani, J., Zipf, A., Mooney, P., Helbich, M. (Eds.)(2015): OpenStreetMap in GIScience: Experiences, Research, and Applications. Series: Lecture Notes in Geoinformation and Cartography. 2015, VII, 373 p. Sringer Science. Heidelberg, Berlin. ISBN 978-3-319-14279-1

Neis, P., Zielstra, D. & Zipf, A. (2013): Comparison of Volunteered Geographic Information Data Contributions and Community Development for Selected World Regions. Future Internet. Vol. 5, pp. 282-300.

Neis, P. & Zipf, A. (2012): Analyzing the Contributor Activity of a Volunteered Geographic Information Project – The Case of OpenStreetMap. ISPRS International Journal of Geo-Information. Vol.1(2), pp.146-165. MDPI. DOI:10.3390/ijgi1020146

Roick, O., Hagenauer, J. & Zipf, A. (2011): OSMatrix – Grid based analysis and visualization of OpenStreetMap. SOTM-EU 2011. State of the Map EU. Scientific Track. Wien.

Crowdsourcing has been widely applied to extract information from 2D geodata sources such as satellite imagery. In this new study published in the ISPRS Journal of Photogrammetry and Remote Sensing we apply this technique to the growing field of 3D point cloud analysis. This work has been conducted in our 3D-MAPP Project which was funded by the Vector Foundation. Also have a look at this short video, that explains our work in more detail.

Herfort, B., Höfle, B. & Klonner, C. (2018): 3D micro-mapping: Towards assessing the quality of crowdsourcing to support 3D point cloud analysis. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 137, pp. 73 -83.

Abstract: In this paper, we propose a method to crowdsource the task of complex three-dimensional information extraction from 3D point clouds. We design web-based 3D micro tasks tailored to assess segmented LiDAR point clouds of urban trees and investigate the quality of the approach in an empirical user study. Our results for three different experiments with increasing complexity indicate that a single crowdsourcing task can be solved in a very short time of less than five seconds on average. Furthermore, the results of our empirical case study reveal that the accuracy, sensitivity and precision of 3D crowdsourcing are high for most information extraction problems. For our first experiment (binary classification with single answer) we obtain an accuracy of 91%, a sensitivity of 95% and a precision of 92%. For the more complex tasks of the second Experiment 2 (multiple answer classification) the accuracy ranges from 65% to 99% depending on the label class. Regarding the third experiment – the determination of the crown base height of individual trees – our study highlights that crowdsourcing can be a tool to obtain values with even higher accuracy in comparison to an automated computer-based approach. Finally, we found out that the accuracy of the crowdsourced results for all experiments is hardly influenced by characteristics of the input point cloud data and of the users. Importantly, the results’ accuracy can be estimated using agreement among volunteers as an intrinsic indicator, which makes a broad application of 3D micro-mapping very promising.

A free copy can be downloaded here (until April 08, 2018): https://authors.elsevier.com/a/1WaMw3I9×1V1Yx

The winter semester 2017/2018 just has ended last week at Heidelberg University. The final GIScience colloquium presentation was given by Ross Purves (University of Zurich). After his talk we had a good discussion with members of the GIScience Research Group about VGI research and beyond. Looking forward to continue this soon. Stay tuned for the GIScience colloquium series next semester and feel welcome to join!

Each week we also have presentations and discussions in the GIScience Joure fixe. In the image below our Alexander von Humboldt PostDoc Fellow Yair Grinberger presents some ideas on VGI theory .

Freshwater tufas are widespread phenomena in karst environments denoting important terrestrial paleo-environmental and paleoclimate archives. Additionally, many tufa sites are UNESCO world natural heritages, which emphasizes their societal importance (e.g. Jiuzhaigou, China; Plitvice, Croatia) and the demand for comprehensive conservation and monitoring strategies. Formation of tufas is controlled by numerous factors. The latest publication - supported by the Heidelberg Center for the Environment (HCE) - reveals new insights into tufa formation.

Ritter, S.M., Isenbeck-Schröter, M., Schröder-Ritzrau, A., Scholz, C., Rheinberger, S., Höfle, B. & Frank, N. (2018): Trace element partitioning in fluvial tufa reveals variable portions of biologically influenced calcite precipitation. Geochimica et Cosmochimica Acta. Vol. 225, pp. 176 -191.

Abstract: The formation of tufa is essentially influenced by biological processes and, in order to infer environmental information from tufa deposits, it has to be determined how the geochemistry of biologically influenced tufa deviates from equilibrium conditions between water and calcite precipitate. We investigated the evolution of the water and tufa geochemistry of consecutive tufa barrages in a small tufa-depositing creek in Southern Germany. High incorporation of divalent cations into tufa is ubiquitous, which is probably promoted by an influence of biofilms in the tufa element partitioning. The distribution coefficients for the incorporation of Mg, Sr and Ba into tufa at the Kaisinger creek D(Mg), D(Sr) and D(Ba) are 0.020–0.031, 0.13–0.18 and 0.26–0.43, respectively. This agrees with previous research suggesting that biofilm influenced tufa will be enriched in divalent cations over equilibrium values in the order of Mg < Sr < Ba. Furthermore, the incorporation of Mg, Sr and Ba into tufa of the Kaisinger creek decreases downstream, which can be attributed to changes of the relative portions of bio-influenced tufa formation with likely higher distribution coefficients and inorganically-driven tufa formation with likely lower distribution coefficients. Additionally, the distribution coefficients of metals in tufa of the Kaisinger creek D(Cd), D(Zn), D(Co) and D(Mn) show values of 11–22, 2.2–12, 0.7–4.9 and 30–57, respectively. These metals are highly enriched in upstream tufa deposits and their contents in tufa strongly decrease downstream. Such highly compatible elements could therefore be used to distinguish easily between different lateral sections in fluvial barrage-dam tufa depositional systems and could serve as a useful geochemical tool in studying ancient barrage-dam tufa depositional systems.

A free copy can be downloaded here (until April 04, 2018): https://authors.elsevier.com/c/1WZ2d3p4ZCXik

The same tufa site was already investigated in detail by using bathymetric LiDAR:

Profe, J., Höfle, B., Hämmerle, M., Steinbacher, F., Yang, M.-S., Schröder-Ritzrau, A. & Frank, N. (2016): Characterizing Tufa Barrages in Relation to Channel Bed Morphology in a Small Karstic River by Airborne LiDAR Topo-Bathymetry. Proceedings of the Geologists’ Association. Vol. 127 (6), pp. 664-675.

The first mapathon in the MAMAPA framework was held on January 23, 2018 at the Abendakademie in the city center of Mannheim.

Project organizer Robert Danziger, Board member at CartONG and member of the disastermappers heidelberg, presented the project in several different locations in Mannheim in the weeks leading to the event. Immigrant language and integration course participants at the Abendakademie, the Goethe Institute and Internationaler Bund were informed about the project and encouraged to add their names to the project contact list.

Among the numerous persons who did register, 16 were present on the afternoon of the mapathon. Since one of the central aspects of the project is to stimulate integration while making a humanitarian contribution via the mapathon activity, these participants were each “partnered” with a German resident at a PC. A group of students and researchers from disastermappers heidelberg/GIScience brought with them their extensive mapathon experience. A number of dyed-in-the-wool Mannheim residents also volunteered their time as did a member of the Board of CartONG, coming from Paris for the event.

CartONG, formal sponsor of the project and co-member of disastermappers heidelberg/GIScience in Missing Maps, prepared a beginner-level task in the HOT Tasking Manager for the mapathon in the context of its cooperation with the UNHCR. The task requested the identification of buildings in Bangladesh, in an area of arrival and encampment of Rohingya refugees from Myanmar. Two colleagues from CartONG made Skype guest appearances to talk to the participants about a few aspects of the specific task being mapped.

Among the immigrant mapathoners, the largest number were from Syria, but present as well were citizens of Turkey, Ghana, Afghanistan, Morocco, Bulgaria and Israel. The mapathon lasted almost 3 hours and — as usual — in a friendly and relaxed atmosphere. Most of the activity was communicated in German (providing language practice also being a goal of the project) but injection of moments of English and French into the conversations contributed noticeably to the conviviality of the group.

Judging from the feedback collected from a short questionnaire distributed at the end of the mapathon, the experience was unanimously positive. All respondents said that they would like to continue to participate in future project mapathons. You can view photos taken during the Mapathon here.

To maintain the momentum created by this mapathon, a second Mapathon is already planned on February 28, 14:30 in the Mannheimer Abendakademie.

If you are interested in supporting the project and for further information and updates, visit the MAMAPA website. If you are interested in joining as a “Mapathon Tandem Partner” please also visit the registration site here.

Tailored routing and navigation services utilized by wheelchair users (such as provided by OpenRouteService.org ) require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is often not sufficiently present in current versions of crowdsourced mapping databases including OpenStreetMap. In a recent study (1) we aim to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The algorithm is composed of four main steps (followed by an enrichment step): pre-processing and cleaning; data clustering and significant point filtering; map matching and candidate point selection; and sidewalk network construction. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions. Note that the length of the path is only one important factor for efficient wheelchair navigation. Further considerations are: (1) presence of a curb cut (roadway access point); (2) presence or enrichment of crosswalks; (3) the running slope and (more critically) the cross slope of the walkway; and (4) walkway surface materials. Hence, future research study needs to be done for developing methods to collect and enrich attributes of sidewalks such as sidewalk width, incline, surface texture, etc. Moreover, the assumption that GPS traces represent the sidewalk travelled is not always true. Also deviations from a sidewalk are very common in an urban setting, and are caused by wheelchair users needing to travel in the roadway around obstacles. These deviations (and their causes) are important to explore in future work.

Reference / further reading:

Mobasheri A., Huang H., Degrossi L.C. and A. Zipf (2018): Enrichment of OpenStreetMap Data Completeness with Sidewalk Geometries Using Data Mining Techniques. Sensors 2018, 18(2), 509; doi:10.3390/s18020509

Selected earlier work

Call for Papers: ISPRS IJGI Special Issue “Volunteered Geographic Information: AnaLysis, Integration, Vision, Engagement (VGI-ALIVE)”

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 30 November 2018

The steady rise of data volume shared on already-established and new Volunteered Geographic Information (VGI) and social media platforms calls for advanced analysis methods of user contribution patterns, leads to continued challenges in data fusion, and provides also new opportunities for rapid data analysis for event detection and VGI data quality assessment. Questions regarding the future of VGI and social media platforms include the prospect of continued user growth, engagement of new user groups, further expansion of VGI to educational activities, and closing data gaps in geographically underrepresented areas.

Although some papers for this Special Issue will be drawn from a related one day VGI-ALIVE workshop at the AGILE 2018 conference, other original submissions aligned with this area of research are also highly welcome. The workshop evolves around a wide range of VGI and social/media research topics including cross-platform data contributions, innovative VGI analysis approaches, current data fusion methods, data interoperability, real-world applications, and the use of VGI and social media use in education. Contributions that discuss future challenges of VGI and social media, may it be on the legal or technical side, that formulate a vision for VGI and social media usage and analysis for the near future, and that demonstrate analysis workflows or the integration of VGI into education are also welcome. This Special Issue offers an outlet for publishing papers relevant to the scope of this workshop. Papers will be reviewed on a continuing basis until the submission deadline.

Article processing fees of IJGI can be waived for a limited number of papers, where priority is given to papers presented during the VGI-ALIVE workshop at the AGILE 2018 conference and early submissions. Please contact the Guest Editors for more information.

Special issue topics include (but are not limited to):

  • Activity patterns and collaboration across multiple VGI and social media platforms
  • (Quasi) real-time analysis of VGI and social media content
  • Technical and legal aspects of crowd-sourced data fusion
  • Opportunities, challenges, and limitations for the future of VGI
  • VGI and social media analysis in geographic areas with sparse data coverage
  • Novel methods of VGI data quality assessment
  • Mobility patterns from VGI and social media
  • User engagement and VGI education
  • Closing the gaps in VGI data coverage

Guest Editors:

  • Dr. Peter Mooney
  • Dr. Franz-Benjamin Mocnik
  • Prof. Dr. Alexander Zipf
  • Dr. Jamal Jokar Arsanjani
  • Dr. Hartwig H. Hochmair
  • Dr. Kiran Zahra

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI’s English editing service prior to publication or during author revisions.

isprs ijgi

Die Abteilung Geoinformatik sucht Studentische Hilfskräfte zur Unterstützung in mehreren hoch aktuellen Forschungsbereichen in einem interdisziplinären dynamischen Team, u.a. z.B. für:

  • Big Spatial Data Analytics z.B. OpenStreetMap History Analysen, Social Media Analytics etc. z.B.  http://ohsome.org
  • Landnutzungsklassifikation auf Basis von OpenStreetMap, Satellitenbildern, etc. z.B. http://OSMlanduse.org
  • Disaster-Management für humanitäre Hilfe (Geoinformatik für Katastrophenmanagement)
  • Intelligente Ortsbasierte Dienste und Navigation, personalisierte Routenplanung http://OpenRouteService.org

Dazu sind die folgenden Voraussetzungen notwendig:

  • Spaß an der Entwicklung von in der Praxis genutzten Softwaresystemen (Open Source)
  • Gute Kenntnisse in einer der folgenden Programmiersprachen:
    • JAVA, C++, Python, R, JavaScript, SQL (PostGIS)
  • Selbstständigkeit, Flexibilität und Teamgeist

Mögliche Themen- und Aufgabenbereiche:

  • Geodatenerfassung und -verarbeitung (insb. OSM)
  • Geodatenbanken
  • GIS Analysen
  • Machine Learning / Spatial Data Mining
  • WebGIS-Entwicklung (Client- oder Serverseitig)
  • etc.

In den genannten Bereichen bieten sich zudem Möglichkeiten zur Durchführung von Qualifikationsarbeiten. (Praktika ab 6 Monate möglich)

Weitere Informationen: http://uni-heidelberg.de/gis und http://heigit.org

· http://www.geog.uni-heidelberg.de/gis/forschung.html

· http://www.geog.uni-heidelberg.de/gis/online.html

Haben wir Ihr Interesse geweckt? Für weitere Informationen melden Sie sich bitte per email unter Angabe Ihrer Interessen und kurzem Überblick zu IT-Kenntnissen bei:

Prof. Dr. Alexander Zipf, Abteilung Geoinformatik, Geographisches Institut
Im Neuenheimer Feld 368, D-69120 Heidelberg
zipf at uni-heidelberg.de

A new abstract has been accepted at EGU about Citizen Science for Big Earth Observation Data Analytics in Land Use and Land Cover Change Monitoring: From Scope to Future Directions

in the Session Citizen Science in the Era of Big Data at European Geosciences Union (EGU) General Assembly 2018 Vienna | Austria | 8–13 April 2018

Land use and cover changes (LUCC) monitoring is a basic need for understanding sociopolitical, ethical and economic aspects of local to global size. Several techniques, auxiliary data sets
and remote sensing tools provide mechanisms to track LUC over large areas. This combination is a time-consuming task considering the growing numbers of satellite imagery. Yet, scientists still lack of ways to organize thousands of downloaded files and analyze the high variability of their spectral and spatial attributes.
Studies moved toward a new architecture of analysis called big Earth Observation (EO) data analytics. This allows to develop and adapt methods with minimal reworking for generating and sharing LUCC results in a collaborative and replicable manner. Scientists seek an automated and generalized method to mitigate the burden on generating LUCC classification maps. Yet it is hard to achieve accurate and efficient results without extensive human supervision. Human visual image interpretation and collection of in situ data are still the simplest and qualitative methods. A manual approach allows non-specialists to collaborate with LUCC information through field-based and online contributions.

The challenge here is how to promote a more active scientific citizenship approach with big EO data analytics for LUCC monitoring. With that in mind, we aim to discuss the scope and future directions on how to collect, organize, incorporate and improve society’s judgements (lots of citizens) into generated automated LUCC maps. See you at EGU 2018!

Related work:

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

OSMlanduse.org Our WebService providing LULC information derived from OpenStreetMap (and Remote Sensing).
OSMatrix Our WebService providing quality related metadata maps for OpenStreetMap

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.

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.

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

Törnros, T., Dorn, H., Hahmann, S., and Zipf, A. (2015): Uncertainties of completeness measures in OpenStreetMap - A Case Study for buildings in a medium-sized German city, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 353-357, doi:10.5194/isprsannals-II-3-W5-353-2015.

Wie komme ich als Rollstuhlfahrer am besten vom Marktplatz zur Stadthalle? Und welche Wege ohne Hindernisse bieten sich für Eltern mit Kinderwagen durch die Altstadt an? Ein neuer Routenplaner auf Basis von openrouteservice.org soll künftig barrierefreie Wege in Heidelberg aufzeigen, zunächst in der Altstadt und in Bergheim. Seit Dezember 2017 arbeitet die Stadt Heidelberg in Kooperation mit dem Bereich Geoinformatik (GIScience) des Geographischen Instituts der Universität Heidelberg und weiteren Partnern an der Umsetzung des Best Practice Projekts.

Erleichterung für Menschen mit Behinderungen und viele mehr

Das Projekt „Routenplanung für Barrierefreiheit“ soll das bestehende digitale Serviceangebot der Stadt wie „Heidelberg hürdenlos“ und den Inklusionsatlas ergänzen: Mit dem Routenplaner können sich künftig Menschen mit Behinderung, aber auch Eltern mit Kinderwagen oder Touristen mit Koffern auf ihren Smartphones eine barrierefreie Route von einem Start- zu einem Zielpunkt anzeigen lassen. Dadurch wird Menschen mit Behinderung nicht nur die Bewegung im öffentlichen Raum erleichtert, sondern auch eine noch stärkere Teilhabe am gesellschaftlichen Leben ermöglicht. Das Projekt wird als eines von 19 wegweisenden kommunalen Digitalisierungsprojekten im Rahmen des Programms „Städte und Gemeinden 4.0 – Future Communities“ vom Ministerium für Inneres, Digitalisierung und Migration Baden-Württemberg gefördert.

Durch die Nutzung der freien Geodatenbank OpenStreetMap ist eine Übertragbarkeit auf andere Kommunen und Regionen gut möglich.

Nun steht der nächste Schritt in der Entwicklungsphase an: Die Straßen und Bordsteine in der Heidelberger Innenstadt werden systematisch erfasst.

Ein Messfahrzeug wird für den barrierefreien Routenplaner die Daten von Straßen und Gassen zunächst in der Altstadt und in Bergheim erfassen. (Foto: Streetguard GmbH)

Dafür wird bis Ende März an einzelnen Tagen ein spezielles Fahrzeug in der Altstadt und in Bergheim unterwegs sein. Die von der Stadt beauftragte Firma Streetguard GmbH wird mit einem gelben VW-Kleinbus Bilder von den Straßen und Gassen machen. Dafür ist er mit entsprechender Messtechnik auf dem Dach ausgestattet. Aus den so erfassten Daten und Bildern werden dann die für die Routenplanung erforderlichen Informationen zur Barrierefreiheit generiert. Die Bilder dienen allein dem internen städtischen Gebrauch und werden nicht weitergegeben oder veröffentlicht. Der Anbieter wurde außerdem dazu verpflichtet, Gesichter und Autokennzeichen bei der Erfassung automatisch zu verpixeln und damit unkenntlich zu machen. Aufgrund der geringen Geschwindigkeit des Messfahrzeugs kann es zu punktuellen Verkehrsbehinderungen kommen. Da die Datenerfassung von guten Wetterbedingungen abhängig ist, erfolgt diese kurzfristig. Die Befahrungstermine können daher nicht benannt werden. Im weiteren Jahresverlauf sollen in einer zweiten Befahrung auch die übrigen Heidelberger Stadtteile erfasst werden.

http://openrouteservice.org
Literatur

Miksch, J., Hahmann, S., Resch, B., Lauer, J., Zipf, A. (2017): Routing Through Open Spaces - A Performance Comparison Of Algorithms. Geo-Spatial information Science, 2017. Taylor & Francis. Geo-Spatial information Science, 2017. Taylor & Francis. https://doi.org/10.1080/10095020.2017.1399675

Zipf, A., Mobasheri, A., Rousell, A. ,Hahmann, S. (2016): Crowdsourcing for individual needs - the case of routing and navigation for mobility-impaired persons. In: Capineri, C, Haklay, M, Huang, H, Antoniou, V, Kettunen, J, Ostermann, F and Purves, R. (eds.) European Handbook of Crowdsourced Geographic Information, p. 325–337. London: Ubiquity Press. DOI: dx.doi.org/10.5334/bax.x

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