Case study of
#00097 Open citizen-science litter mapping with geotagged, brand-level data
Global (origin San Francisco, USA)
#00091
OngoingGlobal
Implementer
Litterati
Location
Global (origin San Francisco, USA)37.7749, -122.4194
Description
Litterati is a citizen-science app originating in San Francisco in which users photograph litter; AI assists in tagging each item's type, material, and brand into an open database. The brand-level data has been used in extended-producer-responsibility and legal contexts, and cities have used it to plan targeted cleanups.
Lessons learned
- AI-assisted brand tagging converts street-level litter photos into brand-attributable evidence usable in producer-responsibility and legal proceedings — a replicable model for accountability campaigns.
- Cities have used the open dataset to plan cleanups, demonstrating that open-access data licensing directly expands downstream reuse by municipal actors.
Sources
1Documented Jun 26, 2026