A crowdsourced global data set for validating built-up surface layers

See, L. ORCID: https://orcid.org/0000-0002-2665-7065, Georgieva, I. ORCID: https://orcid.org/0000-0002-5556-794X, Dürauer, M., Kemper, T., Corbane, C., Maffenini, L., Gallego, J., Pesaresi, M., Sirbu, F., Ahmed, R., Blyshchyk, K., Magori, B., Blyshchyk, V., Melnyk, O., Zadorozhniuk, R., Mandici, M.-T., Su, Y.-F., Rabia, A.H., Pérez-Hoyos, A., Vasylyshyn, R., et al. (2022). A crowdsourced global data set for validating built-up surface layers. Scientific Data 9 (1) 10.1038/s41597-021-01105-4.

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Abstract

Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas.

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