Open citizen-science litter mapping with geotagged, brand-level data
#00097
Let anyone photograph and geotag litter via an app that records type, material, and brand into an open database. Crowdsourcing builds real-time, street-level maps revealing hotspots and brand-level evidence for producer accountability.
Parent issue
#00081 Litter sources and hotspots are poorly measured at an actionable granularity
Sustainable Development Goals
Location
Description
Mechanism
Provide a smartphone app that lets anyone log litter by photographing it; each entry records location, item type, material and (where possible) brand, often with AI-assisted tagging, into an openly accessible database. Crowdsourcing scales data collection far beyond manual surveys, producing real-time, street-level maps of where litter concentrates and which products and brands recur.
Where it fits
A core approach to the measurement facet, and the data backbone other interventions depend on: it tells cleanups and infrastructure where to go, supplies brand-level evidence for producer-responsibility and policy, and lets programmes prove impact. Open data maximises reuse across researchers, NGOs and governments.
Operating profile and limits
Cheap, scalable and powerful for accountability, but data is uneven (concentrated where contributors are active) and depends on sustained participation and consistent tagging; representativeness must be handled with care. Strongest when paired with cleanup movements that double as data collectors.
Sub-issues
0Case studies
4