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Analyzing the impact of climate change on agriculture using big data

About the Authors

Н. Л. Красюкова
Финансовый университет при Правительстве Российской Федерации
Russian Federation


Т. Х. Фарманов
Ташкентский государственный аграрный университет
Uzbekistan


References

1. Easterling W., Apps M. Assessing the Consequences of Climate Change for Food and Forest Resources: A View from the IPCC // Climatic Change. 2005; 70: 165–189.

2. Olesen J.E., Bindi M. Consequences of climate change for European agricultural productivity, land use and policy // European Journal of Agronomy. 2002; 16(4): 239–262.

3. Ewert F. et al. Crop modelling for integrated assessment of risk to food production from climate change // Environmental Modelling & Software. 2015; 72: 287–303.

4. Feng P. et al. Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia // Agricultural Systems. 2019; 173: 303–316.

5. Hoffman A.L. et al. Simulating the Effects of Climate Change on Rice Production in the Philippines Using Neural Networks and Bayesian Models // Global Environmental Change. 2021; 69: 102322.

6. Kadiyala M.D.M. et al. A Bayesian Framework to Assess Uncertainties in the Impacts of Climate Change on Yield and Adaptation Strategies in Rice // Scientific Reports. 2021; 11: 8932.

7. Peng B. et al. Dynamic Bayesian Network-Based Probabilistic Climate Model Ensemble Averaging for Seamless Crop Yield Prediction // Journal of Agricultural and Food Engineering. 2021; 1(1): 11.


Review

For citations:


Красюкова Н.Л., Фарманов Т.Х. Analyzing the impact of climate change on agriculture using big data. Agrarian science. 2024;(6):30-32. (In Russ.)

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ISSN 2686-701X (Online)
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