harveststat-africa

HarvestStat-Africa: Open Access Harmonized Subnational Crop Statistics

https://github.com/harveststat/harveststat-africa

Science Score: 36.0%

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  • CITATION.cff file
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    Found 8 DOI reference(s) in README
  • Academic publication links
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    1 of 2 committers (50.0%) from academic institutions
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    Low similarity (11.2%) to scientific vocabulary
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Repository

HarvestStat-Africa: Open Access Harmonized Subnational Crop Statistics

Basic Info
  • Host: GitHub
  • Owner: HarvestStat
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 1.68 GB
Statistics
  • Stars: 24
  • Watchers: 3
  • Forks: 9
  • Open Issues: 12
  • Releases: 3
Created about 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

HarvestStat-Africa: Open-Access Harmonized Subnational Crop Statistics

GitHub GitHub last commit GitHub issues GitHub pull requests <!-- GitHub forks GitHub stars -->

Overview

The HarvestStat-Africa is a repository that contains cleaned and harmonized subnational global crop production data for Africa from various sources, including the Famine Early Warning Systems Network (FEWS NET) of the United States Agency for International Development (USAID) and the Food and Agriculture Organization (FAO).

This repository provides access to a comprehensive crop dataset that allows researchers, policymakers, and stakeholders to explore trends and patterns from the subnational to the global level, enabling better-informed decisions related to food security, trade, and development.

Data sources

The data in this repository is compiled from various sources, including: - Famine Early Warning Systems Network (FEWS NET) of the United States Agency for International Development (USAID). This is the primary source of information - FEWS NET Data Warehouse (FDW) - Food and Agriculture Organization (FAO) - FAOSTAT - National agricultural agencies

Repository structure

This repository is organized as follows: - data/: stores raw and intermediate crop statistics generated during internal processing. - docs/: contains documentation related to the data. - notebook/: includes Jupyter notebook and Python files for processing crop data for each country. - public/: holds the semi-final & final processed datasets in CSV, Parquet, and GeoPackage formats, ready for public use.

Setting up the environment

To set up the environment using environment.yml, follow these steps:

  1. Clone the repository: bash git clone https://github.com/HarvestStat/HarvestStat-Africa.git cd HarvestStat-Africa

  2. Create the conda environment: bash conda env create -f environment.yml

  3. Activate the environment: bash conda activate hvstat

  4. Start your preferred development environment (e.g., Jupyter Notebook, VSCode):

Current data status

HarvetStat currently contains subnational crop statistics for 33 countries. <!-- (see current data status per country):
--> - Admin-1 level: Angola, Burundi, Central African Republic, Chad, DRC, Ghana, Kenya, Lesotho, Liberia, Mali, Mauritania, Mozambique, Nigeria, South Africa, South Sudan, Sudan, Tanzania, Zimbabwe - Admin-2 level: Benin, Burkina Faso, Cameroon, Ethiopia, Guinea, Madagascar, Malawi, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Togo, Uganda, Zambia

drawing

Data access

The data in this repository is available in the public folder in CSV and GeoPackage formats.

To access the data, download the files from the public folder. - hvstatafricadata{version}.csv: The final processed crop statistics dataset. - hvstatafricaboundary{version}.gpkg: Boundary data for subnational administrative units.

The version of the dataset is specified in the filename. The current version is v1.0.

The official release version is available on Dryad - HarvestStat Africa.

Data structure

The dataset contains the following columns:

| Column Name | Description | | ----------------------- | --------------------------------------------------------------- | | fnid | FEWS NET's unique geographic unit identifier | | country | Name of the country | | country_code | ISO 3166-1 alpha-2 country code | | admin_1 | Name of the first-level administrative unit | | admin_2 | Name of the second-level administrative unit (if applicable) | | product | Name of the crop product | | season_name | Name of the growing season | | planting_year | Year when planting begins | | planting_month | Month when planting begins | | harvest_year | Year when harvesting ends | | harvest_month | Month when harvesting ends | | crop_production_system| Type of crop production system (e.g., irrigated, rainfed, etc.) | | qc_flag | Quality control flag (0 = no flag, 1 = outlier, 2 = low variance)| | area | Cropped area (hectares; ha) | | production | Crop quantity produced (metric tonnes; mt) | | yield | Crop yield (metric tonnes per hectare; mt/ha) |

For details, please see the paper in the Citation section.

Citation

The data in this repository is available for free and unrestricted use. Users are encouraged to cite the following:

D. Lee, W. Anderson, X. Chen, F. Davenport, S. Shukla, R. Sahajpale, M. Budde, J. Rowland, J. Verdin, L. You, M. Ahouangbenoni, K. Davis, E. Kebede, S. Ehrmannk, C. Justice, and C. Meyer. (2024), HarvestStat Africa Harmonized Subnational Crop Statistics for Sub-Saharan Africa. EarthArXiv, https://doi.org/10.31223/X5M123.

BibTeX
@article{lee_eaxv2024,
  author       = {Lee, Donghoon and
                  Anderson, Weston and
                  Chen, Xuan and
                  Davenport, Frank and
                  Shukla, Shraddhanand and
                  Sahajpal, Ritvik and
                  Budde, Michael and
                  Rowland, James and
                  Verdin, Jim and
                  You, Liangzhi and
                  Ahouangbenon, Matthieu and
                  Davis, Kyle Frankel and
                  Kebede, Endalkachew and
                  Ehrmann, Steffen and
                  Justice, Christina and
                  Meyer, Carsten},
  title        = {{HarvestStat Africa  Harmonized Subnational Crop Statistics for Sub-Saharan Africa}},
  year         = {2024},
  journal      = {EarthArXiv},
  note         = {Preprint},
  doi          = {10.31223/X5M123},
  url          = {https://doi.org/10.31223/X5M123}
}

How to contribute

Contributions to this repository are welcome, including new data sources or improvements to the existing data. To contribute, please create a pull request with a clear description of the changes proposed.

Contact

License

The data in this repository is licensed under the MIT License.

Owner

  • Name: HarvestStat
  • Login: HarvestStat
  • Kind: organization

GitHub Events

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  • Issues event: 4
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Last Year
  • Create event: 3
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  • Issues event: 4
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  • Issue comment event: 4
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  • Pull request review event: 4
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Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 293
  • Total Committers: 2
  • Avg Commits per committer: 146.5
  • Development Distribution Score (DDS): 0.338
Past Year
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gnodnooh g****h@g****m 194
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Committer Domains (Top 20 + Academic)
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Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 5
  • Total pull requests: 21
  • Average time to close issues: 13 days
  • Average time to close pull requests: about 16 hours
  • Total issue authors: 3
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  • Average comments per issue: 0.2
  • Average comments per pull request: 0.29
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Past Year
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  • Pull requests: 21
  • Average time to close issues: 13 days
  • Average time to close pull requests: about 16 hours
  • Issue authors: 3
  • Pull request authors: 3
  • Average comments per issue: 0.2
  • Average comments per pull request: 0.29
  • Merged pull requests: 16
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
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  • Mastro1 (3)
  • gnodnooh (1)
  • Hornbydd (1)
Pull Request Authors
  • gnodnooh (11)
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Dependencies

environment.yml conda
  • fiona
  • gdal
  • geopandas
  • ipykernel
  • ipywidgets
  • matplotlib
  • netcdf4
  • numpy 1.23.5.*
  • openpyxl
  • pandas 1.4.4.*
  • papermill
  • pyshp
  • pytables
  • python 3.10.10.*
  • python-docx
  • python-kaleido
  • rasterio
  • rtree
  • scipy
  • seaborn
  • shapely
  • statsmodels
  • xlrd