Urban litter, such as cans, packaging, and cigarettes, has significant impacts and yet little is known about its spatio-temporal distribution, with little available data. In contexts of data scarcity, crowdsourcing provides a low-cost approach to collecting a large amount of geo-referenced data. We consider 1.7 million litter observations in the Netherlands, collected by the crowdmapping project Litterati. First, we analyze the biases of this data at the province and municipality level. Second, in a local case study with high-quality data (the city of Purmerend), we investigate the spatial distribution of urban litter and the points of interest that attract it. This study’s findings can support both the crowdmapping process, steering volunteers efforts, and policy-making to tackle litter at the urban level.
The data used to generate the figures in the article can be found in the following subfolders in datasets. Each folder is documented with a readme file.
The Google Points of Interest data is available only in aggregated form.
- Figure 1: Diagram, no data
- Figure 2:
netherlands_litterati_litter - Figure 3:
netherlands_population_litter - Figure 4:
purmerend_litter_pois - Figure 5:
purmerend_litter_pois - Figure 6:
purmerend_litter_pois - Table 1:
netherlands_population_litter - Table 2:
purmerend_litter_pois
A. Ballatore, T. J. Verhagen, Z. Li, S. Cucurachi, "This city is not a bin: Crowdmapping the distribution of urban litter", Journal of Industrial Ecology, 2021
Dr Andrea Ballatore (https://aballatore.space)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
