The role of urban designers is to shape the physical features of a city with the goal of making the city functional and pleasant to live in. For this, the urban designer has to gather information about the current situation, design improvements, and communicate these to stakeholders. The use of space and the spatial relationships between physical features play a significant role in urban design, therefore much of the information that is collected and manipulated is georeferenced. In this paper we review and evaluate open source geospatial technologies that can be used for the collection, storage, manipulation and visualization of geospatial data in urban design projects. Based on this, an open geospatial toolbox for urban design projects is presented.

We followed a scenario-based approach for collecting the requirements. Three researchers were asked to explain how they collect and use data for their urban design projects. Their backgrounds were in spatial planning and architecture. The first scenario involves an urban designer who is requested to guide and advise the local municipality on improvements in a neighborhood that has become dilapidated over time, and therefore unsafe. In the second scenario, the aim was to identify crime hotspots in a neighborhood and to propose preventative crime measures through environmental design.

By analyzing the scenarios, we determined both functional and non-functional requirements, and categorized them into requirements related to data collection, data storage and management, and data visualisation respectively. A set of open source geospatial technologies were evaluated against these requirements. Tools were evaluated against requirements relevant to a category, e.g. for data storage and management, the user should be able to upload geospatial data, upload newer versions of the data, create and edit metadata about the data, and share the data in various formats using web services. Furthermore, the evaluation results show how tools meet individual requirements, i.e. tools that meet only one of several requirements were not excluded. The resulting open geospatial toolbox is modular, allowing urban designers to swap out a tool in a category for another one in that category, or swap out a tool that meets one requirement for another tool that meets that requirement.

Each of the evaluated tools fulfilled the functional requirements to some degree; the real difference emerged from the non-functional requirements, such as perceived usability for novice users and documentation or support available. The results in this paper are based on requirements of urban designers, but are equally applicable for others who collect data at the neighbourhood level. Future work will focus on aspects of provenance for preserving and making data collected for urban design studies available for longitudinal studies.

When disaster strikes developing countries, a lack of geographic data is often a hindrance to first response and relief operations. To address this lack of geographic data, remote mapping and especially mapathons have played an important role in collecting geographic data in OpenStreetMap (OSM) that can be used to plan activities in areas effected by disaster or other humanitarian efforts. During mapathons, volunteers from various backgrounds get together to map a specific area using satellite imagery or aerial photographs. The expertise and motivation of these volunteers generally differ. Even though the geographic data in OSM is invaluable in cases where little to no data is available, the quality of the data collected during mapathons is often questioned. In this paper, we present our results from an evaluation of university students’ motivation for participating in mapathons and their productivity (i.e. how much data they contributed).

To achieve our aim, we hosted four mapathons for final year university students where the participants were asked to complete a short questionnaire to determine their motivations and personal opinions of the mapathon. Afterwards, the productivity for two mapathons were evaluated. Final year students enrolled in a geoinformatics module were offered extra credit for participating in the mapathons. As a result, the majority of the students participated in all four mapathons and the answers did not differ significantly between the four mapathons.

One of the main reasons mentioned, apart from extra credit, was that the participants felt a sense of humanitarianism through contributing to communities in need by assisting. Additionally, the social aspect also came through with a large percentage of the participants indicating that mapathons are fun and that they learned something new, for example by improving their digitizing skills or that humanitarian organizations need help. Participants also indicated that the tools (i.e. OSM and iD editor) were easy to use, but that the imagery is sometimes not good enough due to cloud coverage. The general productivity for two mapathons was evaluated and we found that with more experience the participants were generally more productive. A further step was taken by investigating five individuals productivity. It was clear that their productivity increased, and that they made fewer errors during the subsequent mapathons.

The results from this evaluation provided insight and knowledge that could assist mapathon organisers to create a more productive environment for participants with the hopes of encouraging them to produce high quality data. The feedback from students was clear that if they receive information about the aim of a mapathon and why the data is important, they are more motivated to produce high volumes of quality data.