Input data for the OnStove Nepal model "AAchieving Nepal's clean cooking ambitions: an open source and geospatial cost–benefit analysis"
Contributors
Description
This repository includes input data to run the OnStove Nepal model presented in the paper "Achieving Nepal's clean cooking ambitions: an open source and geospatial cost–benefit analysis" DOI: https://doi.org/10.1016/S2542-5196(24)00209-2.
The code and automated workflow to run the model can be found in the Github repository https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove-Nepal. All result files and figures can be downloaded from the permanent repository https://doi.org/10.5281/zenodo.10643983.
The "GIS_input_data/" directory includes all the geospatial datasets needed to run the model. Each dataset folder contains a Source.md file describing the dataset, source, attribution, and license. To run the model extract the data inside your "1. Data" folder in your project.
The "Scenario_inputs/" directory includes the CSV files with the input socio- and techno-economic data for the different scenarios. Sources for the socio- and techno-economic data can be found in the supplementary material of the related publication in the link https://doi.org/10.1016/S2542-5196(24)00209-2. To run the model extract the scenario data inside your "2. Scenario inputs" folder in your project.
Files
GIS_input_data.zip
Additional details
Related works
- Is supplement to
- Journal article: 10.2139/ssrn.4726269 (DOI)
Software
- Repository URL
- https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove-Nepal
- Programming language
- Python , Jupyter Notebook
- Development Status
- Active
References
- Ramirez, Camilo and Khavari, Babak and Oberholzer, Alicia and Ghimire, Bhoj Raj and Mishra, Bhogendra and Sinclair-Lecaros, Santiago and Mentis, Dimitris and Gurung, Anobha and Khatiwada, Dilip and Nerini, Francesco Fuso, Achieving Nepal's Clean Cooking Ambitions: An Open Source Spatially Explicit Approach. Available at SSRN: https://ssrn.com/abstract=4726269 or http://dx.doi.org/10.2139/ssrn.4726269