Published January 25, 2023
| Version 1
Dataset
Open
Input data - Wasteaware Cities Benchmark Indicators - WABI 2023 - Global data analytics
Authors/Creators
- 1. University of Leeds
- 2. Imperial College London
- 3. Resources and Waste Advisory Group Ltd.
Description
This is the input dataset for the research publication "Socio-economic development drives solid waste management performance in cities: A global analysis using machine learning". It features
- Metadata info used by R codes
- Full data set for the WABI, used by the R codes
- Data required for plotting the map in Figure 1
The independent variables data set refers to specific indicators of the WABI methodology (https://www.sciencedirect.com/science/article/pii/S0956053X14004905) which generates solid waste management and resource recovery profiles for cities. It is applied here for 40 cities around the world. The data set contains also values for a series of explanatory variables, which are measures of the level of socioeconomic development at country level.
Notes
Files
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