On June 30th, GIZ in cooperation with UN-Habitat, wasteware and the German Aerospace Centre conducted the training event:
How zero waste is your city? Leveraging data to guide urban action towards the Agenda 2030 and a circular economy.
See link on WUF 11 website: https://wuf.unhabitat.org/event/how-zero-waste-your-city-leveraging-data-guide-urban-action-towards-agenda-2030-and-circular
The training event provided an opportunity for about 20 participants to get an overview and understand data- and earth observation driven approaches for circular cities. It combined lessons from pragmatic approaches as well as latest research in the field of urbanization and circular economy to leap-frog data caps and leverage digitization as a driver for better urbanization.
The participants will understand how to use data to measure key parameters of circular economy in cities. Through presentations, short interactive exercises, and discussions they will learn how data can help to define actions to improve urban waste management and circularity.
The training focusses on the four methods:
1) UN Habitat – Waste Wise Cities Tool (WaCT) which helps cities to evaluate and improve their municipal solid waste management performance. This method is based on the definition of the SDG indicator 11.6.1 and generates critical information and parameters through primary data collection to establish better waste and resource management strategies and action plans, as well as to mobilise funds and engage stakeholders of the waste chain;
2) GIZ – Waste Flow Diagram (WFD) is a rapid and observation-based assessment method building on the WaCT. It was used in about 100 cities to understanding leakage pathways of plastic waste into the environment which is key to develop effective measures to beat plastic pollution;
3) GIZ – Positive Deviance Approach assumes that in every population there are individuals or communities who, despite facing similar challenges and limitations, achieve better results than their peers. This approach focuses on these outliers (or positive deviants) in order to discover unusual practices and strategies that successfully solve complex problems ¬– particularly where conventional solutions failed; and
4) DLR – analyzing morphologic transformations across the globe using Earth observation data: This part of the training, focusses on how to apply Earth observation data and visual image interpretation in combination with in-situ and Google Street View images to derive 3D city models to provide a temporal analysis of built-up Transformation.
The session closed with a “card game” to allow participants to practice the key learning points of the session.