Mikusch, G., Petz, A., Steiner, E., Tabakovic, M., & Tellioglu, H. (2023). Environmental data sensing through participatory urbanism. A best-practice analysis and city-administration perspective. GI_Forum - Journal for Geographic Information Science, 11(2), 3–17. https://doi.org/10.1553/giscience2023_02_s3
E193-04 - Forschungsbereich Artifact-based Computing & User Research
-
Journal:
GI_Forum - Journal for Geographic Information Science
-
ISSN:
2308-1708
-
Date (published):
Dec-2023
-
Number of Pages:
15
-
Peer reviewed:
Yes
-
Keywords:
dense sensor networks; environmental data collection; participatory urbanism; quality of public space; sustainability
en
Abstract:
The number of easy-to-use artefacts for environmental data collection is rising. Various scientific projects and private initiatives are addressing how to measure urban data in dense sensor networks by applying devices to public infrastructure or by using citizens. The latter is often done to raise both public awareness and that of administrations and governments. Best practices that use or collect environmental parameters and measurements related to the quality of public spaces (e.g., noise, heat, particulate matter) are central. This work presents data points, analysis parameters and a structured overview of best practices in this field. The results show applications of best practices, ranging from permanently mounted sensors mainly driven by municipalities, to participatory urbanism approaches, where users actively collect environmental data. Additionally, the example of the City of Vienna gives an administrative perspective on incorporating co-creation approaches. Supporting factors for cooperation with private initiatives operating participatory sensing projects are shown; challenges arise when urban participation meets administrative structures.
en
Research Areas:
Urban and Regional Transformation: 20% Visual Computing and Human-Centered Technology: 70% Sensor Systems: 10%
-
Science Branch:
1059 - Sonstige und interdisziplinäre Geowissenschaften: 10% 5090 - Andere Sozialwissenschaften: 10% 1020 - Informatik: 80%