Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX)

Authors

Benjamin Bechtel, Center for Earth System Research and Sustainability, University of Hamburg, Germany
Matthias Demuzere, Department of Forest and Water Management, Ghent University, Belgium
Panagiotis Sismanidis, School of Chemical Engineering, National Technical University of Athens, Athens, Greece
Daniel Fenner, Institute of Ecology, Technische Universität Berlin, Germany
Oscar Brousse, Department of Earth and Environmental Sciences, KU Leuven, Belgium
Christoph Beck, Institute of Geography, University of Augsburg, Germany
Frieke Van Coillie, Department of Forest and Water Management, Ghent University, Belgium
Olaf Conrad, Center for Earth System Research and Sustainability, University of Hamburg, Germany
Iphigenia Keramitsoglou, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Greece
Ariane Middel, School of Geographical Sciences and Urban Planning, Arizona State University
Gerald Mills, School of Geography, University College Dublin, Ireland
Dev Niyogi, Purdue University, West LafayetteFollow
Marco Otto, Institute of Ecology, Technische Universität Berlin, Germany
Linda See, Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Austria
Marie-Leen Verdonck, Department of Forest and Water Management, Ghent University Belgium

Abstract

The World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define here as the collection of data by a bounded crowd, composed of students. In this process, training data for the classification of urban structures into Local Climate Zones (LCZ) are obtained, which are, like most volunteered geographic information initiatives, of unknown quality. In this study, we investigated the quality of 94 crowdsourced training datasets for ten cities, generated by 119 students from six universities. The results showed large discrepancies and the resulting LCZ maps were mostly of poor to moderate quality. This was due to general difficulties in the human interpretation of the (urban) landscape and in the understanding of the LCZ scheme. However, the quality of the LCZ maps improved with the number of training data revisions. As evidence for the wisdom of the crowd, improvements of up to 20% in overall accuracy were found when multiple training datasets were used together to create a single LCZ map. This improvement was greatest for small training datasets, saturating at about ten to fifteen sets.

Comments

This is a PDF of Bechtel, B.; Demuzere, M.; Sismanidis, P.; Fenner, D.; Brousse, O.; Beck, C.; Van Coillie, F.; Conrad, O.; Keramitsoglou, I.; Middel, A.; Mills, G.; Niyogi, D.; Otto, M.; See, L.; Verdonck, M.-L. Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX). Urban Sci. 2017, 1, 15. DOI: 10.3390/urbansci1020015, published by MDPI AG, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Keywords

Local Climate Zones (LCZs); urban climate; crowdsourcing; volunteered geographic information; classification; WUDAPT

Date of this Version

5-9-2017

DOI

10.3390/urbansci1020015

Recommended Citation

Bechtel, B.; Demuzere, M.; Sismanidis, P.; Fenner, D.; Brousse, O.; Beck, C.; Van Coillie, F.; Conrad, O.; Keramitsoglou, I.; Middel, A.; Mills, G.; Niyogi, D.; Otto, M.; See, L.; Verdonck, M.-L. Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX). Urban Sci. 2017, 1, 15.