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‎404.html‎

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‎About/index.html‎

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<p>PyAEZ package consists of six main AEZ modules and one additional utility module stated as below:</p>
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<p>Module 1: Climate regime - calculation of agro-climatic indicators for evaluation of climatic suitability of crops.</p>
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<p><strong>Module 1: Climate regime</strong> - calculation of agro-climatic indicators for evaluation of climatic suitability of crops.</p>
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<p><strong>Module 2: Crop simulation</strong> - simulate an optimal crop cycle for the highest attainable yield.</p>
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<h1 id="acknowledgements">Acknowledgements<a class="headerlink" href="#acknowledgements" title="Permanent link">&para;</a></h1>
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<p>The free and open source package Python Agro-Ecological Zoning (PyAEZ) was developed to address country-specific spatial information needs on future agricultural production. The finalization of this publication was led by Dr. Manzul Kumar Hazarika, Dr. Kittiphon Boonma and Swun Wunna Htet are the main authors for this publication with technical advice and contribution from Prof. Rajendra P. Shrestha.</p>
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<p>The authors acknowledge the contribution from the Asian Institute of Technology - Geoinformatics Center and the Food and Agriculture Organization of the United Nations (FAO) through the Geospatial Unit and the Regional Office for Asia and the Pacific (FAO-RAP). The PyAEZ development received financial support under a regional initiative on “Capacity building for Agro-Ecological Zone (AEZ) mapping and modelling to project climate suitability of crops and land uses” in collaboration with the FAO-RAP and the “Strengthening agro-climatic monitoring and information systems to improve adaptation to climate change and food security in Lao PDR (GCP /LAO/021/LDF)” project. The code development received contribution from Lakmal Nawarathnage, Thaileng Thol, Gianluca Franceschini, Shraddha Sharma, Dr. Kavinda Gunasekara, Dr. Kittiphon Boonma, Swun Wunna Htet and Dwijendra Das.</p>
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<p>This achievement would have not been made possible without the continuous technical contribution and advice from Günther Fischer from the International Institute for Applied Systems Analysis (IIASA) and Freddy Nachtergaele. The authors are also grateful for the financial and management support from FAO, especially Beau Damon, Monica Petri, Federica Chiozza, Joyce Ahimbisibwe, Dario Spiller, Rutendo Mukaratirwa and Matieu Henry.</p>
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<p>The free and open source package Python Agro-Ecological Zoning (PyAEZ) was developed to address country-specific spatial information needs on future agricultural production. The finalization of this web-based PyAEZ documentation was done by Swun Wunna Htet, Senior Research Associate of GIC-AIT.</p>
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<p>The authors acknowledge the contribution from the Asian Institute of Technology - Geoinformatics Center (GIC-AIT) and the Food and Agriculture Organization of the United Nations (FAO) through the Geospatial Unit and the Regional Office for Asia and the Pacific (FAO-RAP). The PyAEZ development received financial support under a regional initiative on “Capacity building for Agro-Ecological Zone (AEZ) mapping and modelling to project climate suitability of crops and land uses” in collaboration with the FAO-RAP and the “Strengthening agro-climatic monitoring and information systems to improve adaptation to climate change and food security in Lao PDR (GCP /LAO/021/LDF)” project. The code development received contribution from Lakmal Nawarathnage, Thaileng Thol, Gianluca Franceschini, Shraddha Sharma, Dr. Kavinda Gunasekara, Dr. Kittiphon Boonma, Swun Wunna Htet and Dwijendra Das.</p>
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<p>This achievement would have not been made possible without the continuous technical contribution and advice from Günther Fischer from the International Institute for Applied Systems Analysis (IIASA) and Freddy Nachtergaele. The authors are also grateful for the financial, management and technical support from FAO, especially Beau Damon, Monica Petri, Federica Chiozza, Joyce Ahimbisibwe, Dario Spiller, Rutendo Mukaratirwa, Filippo Sarvia and Matieu Henry.</p>
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<p>Numpy: <a href="https://numpy.org/install/">click-here</a></p>
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<p>GDAL : <a href="https://anaconda.org/conda-forge/gdal">click-here</a></p>
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<p>SciPy : <a href="https://scipy.org/install">click-here</a></p>
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<p>Numba : <a href="https://numba.readthedocs.io/en/stable/user/installing.html">click-here</a></p>
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<p>ECMWF : <a href="https://www.ecmwf.int/en/forecasts/datasets">click-here</a></p>
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<p>While most of the parameterizations can be referred to GAEZv4 Appendix (Source: https://s3.eu-west-1.amazonaws.com/data.gaezdev.aws.fao.org/documentation/GAEZ4_Appendices.xlsx), some requires additional references apart from GAEZ context. The crop parameters can also be user-defined, or experimental, i.e., some parameters can be estimated from laboratory experiments, as FAO scientists initiated in the early 1900's.</p>
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<p>While most of the parameterizations can be referred to <a href="https://s3.eu-west-1.amazonaws.com/data.gaezdev.aws.fao.org/documentation/GAEZ4_Appendices.xlsx">GAEZv4 Appendix</a>, some requires additional references apart from GAEZ context. The crop parameters can also be user-defined, or experimental, i.e., some parameters can be estimated from laboratory experiments, as FAO scientists initiated in the early 1900's.</p>
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