Data on built-up surfaces around the world were collected via a Geo-Wiki campaign, where this data set is intended for use as an independent validation of global maps of built-up surfaces.

There are now several maps available of urban areas at a global, regional and national scale. Some of these are produced using remote sensing, others employ population data from censuses or a combination of data sets, while others break down the urban class into multiple detailed classes of urban form, e.g., the Copernicus Urban Atlas. Two recently produced high resolution products are the Global Human Settlement Layer from the Joint Research Center (JRC) of the European Commission, and the World Settlement Footprint from the German Aerospace Center (DLR). These products have been validated in different ways but generally using the layer itself to produce the validation data sample.

Instead, validation using an independent data set would be a better way of determining how well these products represent built-up areas. Such an independent reference data set has the advantage that it can be used on multiple products, and it can be updated in the future for validating new products as they are produced.

Geo-Wiki Built-up Campaign © IIASA

Figure 1: Screenshot from the Geo-Wiki Global Built-up Surface Validation application showing the three main steps that users followed for data collection: Step 1: moving between the Google Maps and Microsoft Bing image to look for change (Step 2) and then Step 3: shading the cells for evidence of built-up areas. Source of imagery: Google.

Thus in 2020, we ran a Geo-Wiki campaign to collect an independent reference data set on built-up areas at 50K locations globally. We used a stratified-random sampling design that used independent layers such as income and land cover to produce the stratification. The crowd then used Geo-Wiki to visually interpret very high-resolution satellite imagery from Google Maps and Microsoft Bing Maps for built-up surfaces. First, volunteers were asked to examine pairs of images at the same location from Google Maps and Microsoft Bing Maps to look for evidence of change in built-up areas followed by shading 10m cells for built-up presence in an 80x80 m grid placed on top of Google Maps satellite imagery. The Geo-Wiki interface was adapted specifically for this campaign and is shown in Figure 1 above.

In the campaign, we used gamification, co-authorship and Amazon vouchers as incentives to encourage participation. The built-up areas identified during the campaign are shown in Figure 2, where the full details can be found in See et al. (2022), which includes winners of the campaign as co-authors.

Geo-Wiki Figure 2 © IIASA

Figure 2: Built-up areas shown globally

See, L., Georgieva, I., Duerauer, M., Kemper, T., Corbane, C., Maffenini, L., Gallego, J., Pesaresi, M., Sirbu, F., et al. (2022): A crowdsourced global data set for validating built-up surface layers. Scientific Data.
Data Set available in IIASA PURE:


Olteanu-Raimond, A.-M., See, L. , Schultz, M., Foody, G., Riffler, M., Gasber, T., Jolivet, L., le Bris, A., Meneroux, Y., Liu, L., Poupée, M., & Gombert, M. (2020). Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change. Remote Sensing 12 (7) 10.3390/rs12071186.

See, L. , Fritz, S. , Perger, C., van der Velde, M., Albrecht, F., Schill, C., McCallum, I. , Schepaschenko, D. , & Obersteiner, M. (2013). Urban Geo-Wiki: A crowdsourcing tool for improving urban land cover. In: Citizen E-Participation in Urban Governance: Crowdsourcing and Collaborative Creativity. Eds. Silva, CN, Hershey: IGI Global. ISBN 9781466641709 10.4018/978-1-4666-4169-3.ch008.