An integrated approach of remote sensing and geospatial analysis for modeling and predicting the impacts of climate change on food security
January 19, 2023 | Scientific Reports |
Introduction: Climate change threatens agriculture, infrastructure, and local communities. Monitoring and predicting climate impacts on food security is essential, requiring advanced technologies like remote sensing and machine learning. Yet, integrated approaches remain scarce, especially in assessing frost impacts. An Iranian research team formed by University of Tabriz, Isfahan University of Technology, Bu-Ali Sina University team up with researchers based in Italy and US to analyze climate effects on food security in the Lake Urmia Basin.
Key findings: Through remote sensing and advanced modeling techniques, the research assesses changes in agricultural lands (AL) and frost-affected areas over the past two decades. Results indicate a decrease in AL and an increase in frost-affected areas, threatening food production. Analyses of various environmental variables reveal correlations between factors like temperature, precipitation, and soil quality with food security. Moreover, predictive modeling suggests worsening food security conditions in the future. The study highlights the urgency of addressing climate-induced challenges in the Lake Urmia Basin to safeguard food production and mitigate potential environmental crises.
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Fig. | An overview of the presents study methodology.
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