🌮 Trash Annotations in Context Dataset Toolkit

AI to Combat Environmental Pollution - detecting plastic waste in the environment to combat environmental pollution and promote circular economy (Deep Learning, PyTorch)

Source Code for TrashMob.eco

pLitter is a standardized, deep learning friendly dataset and pre-trained model that can be used for detecting plastic litter in streets , road-sides, etc. Additionally, all supplementary codes related to this repository are also published here.

A spatially explicit trait- and individual-based microbial systems modelling framework

Not in Philly

A project that explores the relationship between deprivation and litter in Glasgow City. 🚯

Open Litter Map Documentation

The project focuses on finding & realizing effective IT techniques to detect and reduce litter.

Clean Up Cork City is a community-driven app that will allow people to create a map of litter dumps around Cork City. People can register on the website and add details about a location that is polluted with litter. Events are organised for the volunteers who will come to one of the locations and clean up the litter.

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…

Repo for resources and analysis relating to IRT project by Jody Holland

An analysis of beach litter inventories conducted on Lake Geneva 2015-2018.

Repo for hammerdirt California's(hdC) Cordova Creek 2(cc_2) project.

Selection of Adjusted Litter Scene Annotations (SALSA) dataset toolkit

A Ruby gem that parses a log of collected litter. For avid trash-picker-uppers.

An open data model for exchange and storage of beach debris data

🚛 TrAsh DAtaset based on Korea Ministry of Environment guidelines

This dataset takes litter activity from 2016 in two counties in Washington State, King and Grant to compare and also compares voter turnout to correlate attitudes in voting turnout and littering behavior, as well as voting records by political party. The intended audience is researchers in public policy and or public health.