Feed on

Maps of the spatial distribution of crop heights can strongly support agriculture in terms of efficiency and yield optimization. Recently published results of experiments of the 3D Spatial Data Processing research group describe an approach to easily extend regular agricultural machines with low-cost sensors for capturing crop heights while the machine is in the field.
Based upon a comparison between crop height values derived from 3D geodata captured with the low-cost approach, and high-end terrestrial laser scanning reference data, minimum RMS and standard deviation values of 0.13 m (6.91% of average crop height), and maximum R² values of 0.79 were achieved. A main conclusion of the study is that the crop height measurements derived from data captured with the introduced setup can provide valuable input for tasks such as biomass estimation.
Get more details of the study in:

Hämmerle, M. & Höfle, B. (2017): Mobile low-cost 3D camera maize crop height measurements under field conditions. Precision Agriculture, pp. 1-16. https://doi.org/10.1007/s11119-017-9544-3 - read the PDF online via Springer Nature SharedIt: http://rdcu.be/w24P

Check also other work about agricultural crop height conducted by the 3D Spatial Data Processing research group:

Hämmerle, M., Höfle, B. (2016): Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements. Plant Methods 2016(12:50). http://dx.doi.org/10.1186/s13007-016-0150-6

Marx, S., Hämmerle, M., Klonner, C. & Höfle, B. (2016): 3D Participatory Sensing with Low-Cost Mobile Devices for Crop Height Assessment – A Comparison with Terrestrial Laser Scanning Data. PLOS ONE. Vol. 11 (4), pp. 1-22. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152839

Crommelinck, S. & Höfle, B. (2016): Simulating an Autonomously Operating Low-Cost Static Terrestrial LiDAR for Multitemporal Maize Crop Height Measurements. Remote Sensing. Vol. 8 (3), pp. 1-17. http://dx.doi.org/10.3390/rs8030205

Hämmerle, M., Höfle, B. (2014): Effects of Reduced Terrestrial LiDAR Point Density on High-Resolution Grain Crop Surface Models in Precision Agriculture. Sensors, Vol. 14, pp. 24212-24230. http://www.dx.doi.org/10.3390/s141224212

Crowdsourcing for Urban Geoinformatics

Aims and Scope
Modern mobile devices are pervasively equipped with embedded sensors and cameras, and allow the positioning of media contents within geographic space. In combination with the Web 2.0 paradigm, this has led to the crowdsourcing approach, which in turn has become an important data acquisition technique. It is now possible to collect large amounts of geospatial data in a timely fashion and at low costs, especially in urban areas that feature vast numbers of contributors.

Crowdsourcing thus opens up new possibilities for the disclosure of social processes, and for tackling a range of societal and environmental issues related to urban conurbations. For instance, crowdsourcing allows the integration of user-generated information into urban planning and management workflows—and is thus a crucial step towards the design of smarter and more sustainable cities.

At the same time, crowdsourcing brings new issues to the research agendas: (a) huge amounts of data need to be processed, (b) more thorough interdisciplinary collaboration is needed, and (c) we are facing a general absence of theorizing on crowdsourced geodata and underlying related processes. Further, researchers as well as practitioners are often sceptical about the suitability of crowdsourced data. This is mostly caused by potential quality issues, heterogeneous data characteristics and a lack of user credibility, semantic ambiguities, and potential positional inaccuracies, among others.


In order to foster the overcoming of the outlined gaps, we call for the submission of papers that address the analysis and application of crowdsourced geographic data, with a specific emphasis on urban research and issues.

We welcome contributions on the following topics:

  • Reviews of the state-of-the-art in using crowdsourced geographic information in urban research, planning, and management.
  • Applications and empirical case studies that investigate urban issues by using crowdsourced geographic data such as OSM, social media data, floating car data, and other types.
  • Data enrichment through crowdsourced geographic data.
  • Extraction of 3D information from crowdsourced geographic data (e.g., from Kinect data, OSM data).
  • The analysis of human behaviours for emergency (disaster) management, tourism, or urban planning and management.
  • Quality assessment for crowdsourcing geographic data.
  • Further topics are welcome if they fit the overall theme.

Submission Guidelines

Manuscripts should be submitted online: here.

Submitted articles should not have been published previously, or be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. All accepted manuscripts will be published open access in GSIS.

All article publishing charges (APC) will be covered by Wuhan University, so you can enjoy the benefits of publishing open access at no cost. Authors are recommended to prepare their manuscript by following the full instructions for authors: here.

Important Dates:

Submission deadline of finalized manuscripts: November 20, 2017
Deadline of print-ready version: April 30, 2018
Expected inclusion in an issue: June−August, 2018

Editorial information

Submit your paper to Geo-spatial Information Science (GSIS), an open access journal by Taylor & Francis with no article publishing charge (APC)!

Special issue call for papers: Crowdsourcing for Urban Geoinformatics

Just recently the GSIS Special Issue on “VGI Analytics” has been published including our article on The OpenStreetMap folksonomy and its evolution by Mocnik, Zipf and Raifer.

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

Automatic Reconstruction of Buildings with Complex Roof Shapes

Andreas Wichmann
Institute of Geodesy and Geoinformation Science, Technische Universität Berlin

Time and date: Mon, October 23, 2:15 pm
Venue: INF 348, Room 015, Department of Geography, Heidelberg University

Digital 3D city models are of crucial importance in many applications such as urban and regional planning and enable in the environmental field precise analyses and simulations of pollutant, flood, and noise propagation. Their manual reconstruction provides good results, but is usually very time-consuming and expensive. In order to overcome this issue, the development of automatic reconstruction approaches for the time-efficient and cost-effective generation of 3D building models has become of great interest in recent years. In this talk, a fully automatic building reconstruction approach will be presented which uses building points of an aerial LiDAR data set. The approach is characterized by a strong integration of building knowledge, which is automatically derived during the reconstruction through the application of a graph grammar. It utilizes half-space modeling techniques for the construction of 3D building models to ensure their topological correctness. The resulting building models feature many details and provide in addition to the geometric information also semantic information if required. Thus, they are well suited for different applications. The talk will conclude with a brief overview of related research activities of the speaker.

We are proud to announce our partnership with the German Federal Agency for Cartography and Geodesy [German: Bundesamt für Kartographie und Geodäsie (BKG)] which is the central service provider of topographic data, cartography, and geodetic reference systems for the German government. The agency works under the Federal Ministry of the Interior, with specialist departments in geodesy and geoinformation.

The BKG offers a whole stack of interesting services and amongst these are a various geospatial API’s based on openrouteservice (ORS) using OpenStreetMap (OSM) data. To this end, the BKG is now running a clone of the openrouteservice infrastructure in their cloud center offering geocoding, directions and isochrones.

The cooperation is particularly interesting as we will not only benefit from interesting feature requests but also from new data sets enabling a higher quality for directions, especially in terms of elevation data.

More features for Cyclists:
Furthermore we have introduced 3 new interesting features to the ORS API, especially suitable for cyclists.

Continue straight

Continue straight forces your route to keep going straight at specific waypoints even if u-turns would be faster. It basically makes your route more pleasant.


Bearings filters the segments of the road network a waypoint can basically snap to. It can be passed to the API as a comma-separated list that can consist of one or two float values, where the first value is the bearing and the second one is the allowed deviation from the bearing. The bearing can take values between 0 and 360 clockwise from true north.


With radiuses you can limit the search of nearby road segments to every given waypoint. The values are given in meters and must be greater than 0, the value of -1 specifies no limit in the search.


Openrouteservice API documentation

Yesterday, GIScience Heidelberg was welcoming our new master students. After a general introduction into our teaching philosophy, our core courses and our institutes (HeiGIT, HCE, IWR), we were giving insights into the  specialization in GIScience/Geoinformatics, which is possible in the Geography Master Programme.

As our teaching is research-based and research-oriented we were presenting most recent state-of-the-art insights into the following topics:

Our slides are provided on Moodle: https://elearning2.uni-heidelberg.de/course/view.php?id=16932

The entry key for self-enrolment will be provided via the mailing list for master students. For adding yourself to the mailing list, please refer to: http://www.geog.uni-heidelberg.de/studium/verteiler.html

We are looking forward to fruitful work together the next four semesters.

On Monday 09 October 2017 the GIScience group of Heidelberg university organised another Wheelmap mapping event for SAP volunteers in the course of the “SAP month of service“. Volunteers of SAP already supported the CAP4Access team in merging volunteered accessibility data (from Wheelmap.org) and expert accessibility data (from Heidelberg Hürdenlos) two years ago and by improving/completing of Wheelmap.org at Heidelberg last year.

Wheelmap.org is a map for finding wheelchair accessible places and it is run by one of our CAP4Access project partners, the nonprofit organization Sozialhelden e.V.. The map is based on OpenStreetMap and works similar to Wikipedia which means that anyone can contribute and mark public places around the world according to their wheelchair accessibility.

During the event, a total number of 7 SAP-volunteers performed mobile mapping using the Wheelmap App on their smartphones. Before the mapping started, the participiants made themselves familiar with the Wheelmap traffic light system, a simple and easy to understand way to rate the accessibility of public places („green” = fully, „orange” = partially, „red” = not and „grey” = unknown wheelchair accessible). Afterwards, the volunteers split into 2 groups and mapped parts of Heidelberg Altstadt that still had many unmarked places.

As a result of the mapping event, almost 140 public places have been marked by volunteers or checked for their up-to-dateness.

In short, the mapping event was a great success and we would like to thank all of the volunteers of SAP for their social engagement!

This monday the nice weather was reason enough to have another spontaneous GIScience HD group photo after the jour fixé. And well, as often indeed there are a number of new faces, too :-)
“The only thing constant in life is change”
Feel welcome and enjoy!

Dear Mapping Enthusiasts,

We want to welcome the freshman students to Heidelberg University and start the new semester with our next mapathon!

At our Ersti-mapathon we want to introduce everyone interested to OpenStreetMap mapping. Therefore, no previous knowledge is necessary. In addition our MapSwipe App will be presented. We will show how you can create geo data urgently needed for the acitvity of humanitarian organisations.

If available, bring your Laptop/mouse or smartphones! We will also have access to the PC pools and tablets of the Institut of Geography.

When? Tuesday 24.10.2017, 6 pm

Where? Großer Hörsaal, Geographisches Institut, Berliner Straße 48

As always we will provide snacks and drinks! We’re looking forward to start mapping with you guys!

Today Prof. Alexander Zipf is giving an invited keynote speech at the German Aerospace Center (DLR) in Oberpfaffenhofen, the national aeronautics and space research centre of the Federal Republic of Germany.
The DLR organises a two day workshop called “DLR.Open II - Open Data Science und Open Geodata“. This is the second workshop on Open Data and Open Science held at the DLR. This emphasises the growing importance of open geodata and open data science. Prof. Zipf will highlight examples of research on the quality, integration and machine learning based enrichment of open geodata, as well as examples on innovative applications based on these from different domains like disaster response and humanitarian aid, landuse, navigation as well as health and planning. The focus will be on user generated geodata such as OpenStreetMap and related data sources, based on the work and research projects at the GIScience Research Group Heidelberg and the Heidelberg Institute for Geoinformation Technology (HeiGIT), including analytics of crowdsourcing applications like MapSwipe, the OSM history analytics platform ohsome.org and of course latest news from OpenRouteService.

Dear master students,

we warmly welcome you to Heidelberg and to our institute! You are cordially invited to an introduction to the GIScience research group, which takes place on Wednesday (18 October, 4 pm - 6 pm). We will provide you an introduction to our offered lectures, seminars and give you an overview of our ongoing research:

  • General introduction on the group and the study programme (Prof. Dr. Bernhard Höfle)
  • Social media research (René Westerholt)
  • Analysis of user-generated geoinformation (Dr. Franz-Benjamin Mocnik)
  • Disaster mapping (Carolin Klonner)
  • 3D geospatial analysis/LiDAR (Prof. Dr. Bernhard Höfle)

The presentations will take place at room 015 in INF 348 (the lecture hall). Looking forward to seeing you soon!

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