Falchetta, G., & Hammad, A. T. (2025). Tracking green space along streets of world cities. Environmental Research: Infrastructure and Sustainability. https://doi.org/10.1088/2634-4505/add9c4
To replicate the analysis:
- Download input data from Zenodo: https://doi.org/10.5281/zenodo.15624204
- Optional data extraction steps (processed output data are already available in the Zenodo repository):
- Adjust your working directory
- Run [lines 4-11] of workflow/sourcer.R
- Run the Javascript scripts written by the string_generator_training.R and string_generator_prediction.R files in Google Earth Engine (https://code.earthengine.google.com) and complete the export to Drive tasks to generate the output .csv files
- Run workflow/sourcer.R [lines 15-46] to train the ML model and make predictions (including figures and tables replication)
The analysis was implemented in the following environment:
- RStudio 2023.03.0
- R version 4.2.3 (2023-03-15 ucrt)
- Platform: x86_64-w64-mingw32/x64 (64-bit)
- Running under: Windows 10 x64 (build 22631)
The file "gvi_358cities_2016_2023_yearly_falchetta_hammad.csv" (found in the Zenodo repository) contains output data, reporting sampling-point level data on the yearly (2016-2023) values of the Green View Index for the 190 cities covered in the paper AND an additional number of world cities (for a total of 358 cities). The "README_gvi_358cities_2016_2023_yearly_falchetta_hammad.txt" file contains a dictionary of each column name and units.