PyAEZ is a python package consisted of many algorithms related to Agro-ecalogical zoning (AEZ) framework.
Project description
PyAEZ
PyAEZ is a python package consisted of many algorithms related to Agro-ecalogical zoning (AEZ) framework. PyAEZ tries to encapsulate all complex calculations in AEZ and try to provide user friendly, and intuitive ways to input data and output results after calculations.
Installation
Now the package can be installed using pip
command as below,
pip install pyaez==2.1
Alternatively, can be installed using using conda
command as below,
conda install -c conda-forge pyaez
Introduction
PyAEZ includes 6 main modules as below. Additionally to that, UtilityCalculations module is also included in PyAEZ to perform additional related utility calculations.
- Module I: Climate Regime
- Module II: Crop Simulations
- Module III: Climate Constraints
- Module IV: Soil Constraints
- Module V: Terrain Constraints
- Module VI: Economic Suitability Analysis
- UtilityCalculations Module
Other than 6 main modules and utility module, following 3 major algorithms related to AEZ also are included in PyAEZ. Those 3 major algorithms can be utilized individually without running whole PyAEZ.
- Biomass Calculations
- Evapotranspiration Calculations
- CropWat Calculations
Dependencies
- numpy
- scipy
- gdal
- numba
Step-by-step Process
Following 6 Jupyter notebooks in the GitHub repository can be used as worked full example for PyAEZ 6 major modules.
- NB1_ClimateRegime.ipynb
- NB2_CropSimulation.ipynb
- NB3_ClimaticConstraints.ipynb
- NB4_SoilConstraints.ipynb
- NB5_TerrainConstraints.ipynb
- NB6_EconomicSuitability.ipynb
Note: NB2_CropSimulation.ipynb takes a huge amount of time due to automatic crop calendar calculations. Hence, we have rewritten core parts of PyAEZ (CropWatCalc.py, BioMassCalc.py and ETOCalc.py) with Numba compatible manner as well. Numba translates Python functions to optimized machine code at runtime, allowing calculation speeds close to C or FORTRAN.
Release Note PyAEZv2.1
The goal of this release is to improve the overall accuracy and reliability of the AEZ methodology in Module 1, 2, and 3. The key updates are as follows:
Module 1:
- Major improvements in the Length of Growing Period (LGP) calculation routine through the implementation of Numba (a Python package to speed up the calculation) and cross-checking the methodology with the Global AEZ from IIASA.
- All the climatic indicators had been thoroughly cross-checked and verified with the Global AEZ outputs.
Module 2:
- Reading crop/crop cycle parameters from excel sheet.
- Updated algorithm for TSUM screening and parameter settings.
- New thermal screening logics: permafrost screening, crop-specific rule screening.
- Updated algorithm for perennial crop simulations.
- New outputs: thermal reduction factor maps (fc1), yield reduction due to moisture deficit (fc2) and optimum starting date, for both rainfed and irrigated conditions.
Module 3:
- New look-up table setting for agro-climatic reduction factors for both rainfed and irrigated conditions.
- Updated algorithm related to agro-climatic constraints calculation.
- New outputs: Adjusted Length of Growing Period for agro-climatic constraints, agro-climatic constraint map (fc3).
Documentation
API Documentation is located in "docs" folder.
Citation
Use this bibtex to cite us.
@misc{PyAEZ(v2.1.0),
title={PyAEZ Python Package for Agro-ecological zoning (AEZ)},
author={Swun Wunna Htet, Kittiphon Boonma, Gianluca Franceschini, N. Lakmal Deshapriya, Thaileng Thol, Kavinda Gunasekara, Rajendra Shrestha, Freddy Nachtergaele, Monica Petri, Beau Damen},
year={2023},
publisher={Github},
journal={GitHub repository},
howpublished={\url{https://github.com/gicait/PyAEZ}},
}
Developed by
Geoinformatics Center of Asian Institute of Technology.
Funding
Food and Agriculture Organization of the United Nations (FAO) and FAO SAMIS (Strengthening Agro-climatic Monitoring and Information System) Project in Lao PDR.
Sample Data Source
- Abatzoglou, J.T., S.Z. Dobrowski, S.A. Parks, K.C. Hegewisch, 2018, Terraclimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015, Scientific Data,
Major AEZ References
- de Wit, C. T. (1965). Photosynthesis of leaf canopies. Agricultural Research Report No. 663. PUDOC, Wageningen, 57 .
- FAO. (1992). Cropwat: A computer program for irrigation planning and management. Land and Water Development Division, Rome, Italy, FAO Irrigation and Drainage Paper no 46 .
- FAO. (1998). Crop evapotranspiration. FAO Irrigation and Drainage Paper no.56 Rome, Italy.
- FAO. (2017). Final Report: National Agro-Economic Zoning for Major Crops in Thailand (NAEZ).
- Fischer, G., van Velthuizen, H., Shah, M., & Nachtergaele, F. (2002a). Global agroecological assessment for agriculture in the 21st century: Methodology and results. IIASA RR-02-02, IIASA, Laxenburg, Austria.
- Monteith, J. L. (1965). Evapotranspiration and the environment. In The State and Movement of Water in Living Organisms, 205-234.
- Monteith, J. L. (1981). Evapotranspiration and surface temperature. Quarterly Journal Royal Meteorological Society, 107 , 1-27.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file PyAEZ-2.2.tar.gz
.
File metadata
- Download URL: PyAEZ-2.2.tar.gz
- Upload date:
- Size: 56.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | aa796d25d5ebf91f64d018cfc56fa617dfd56347edde526df352b0cf62e88e71 |
|
MD5 | c0d501a5f8e6102e29bde9abec78ea35 |
|
BLAKE2b-256 | cc66ce851488387fa0310653921d6c5e1109773688d41cc2b5d64d9f9082dff9 |
File details
Details for the file PyAEZ-2.2-py3-none-any.whl
.
File metadata
- Download URL: PyAEZ-2.2-py3-none-any.whl
- Upload date:
- Size: 61.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9ad1b3ddf9a1fce9d92f277137bd2f847f9510de947a79c4989e9d913291d72b |
|
MD5 | 002406274666b8968d9c5b7d7bf0fe77 |
|
BLAKE2b-256 | 57a567ec53f39e98f05e81958ff082a6cc2226b99738ce0d9f2cb529eba07346 |