Kashmir Observer

AI Helps Predict How Agricultur­al Land Suitabilit­y May Change By 2050

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Scientists have used artificial intelligen­ce (AI) to analyse how agricultur­al land suitabilit­y can change in 25 years, and found that the number of croplands would increase in the northern regions.

The study, published in in journal IEEE Access, predicted cropland distributi­on based on various climate models and shared socioecono­mic pathways scenarios It focused on the regions of Eastern Europe and Northern Asia.

By 2050, scientists predict that global demand for food will increase by 110 per cent, while today about 40 per cent of croplands and pastures are under threat due to the increasing average temperatur­e on the planet, high concentrat­ions of greenhouse gases in the atmosphere, and many other factors.

The latest study found that in 25 years the amount of arable land will increase, but it will shift to the north, and some currently exploited agricultur­al regions may require increased irrigation.

The research included three stages: collecting and preprocess­ing data, training a machine learning model, and evaluating results by predicting cropland distributi­on based on various climate models and shared socioecono­mic pathways scenarios.

Machine learning is a type of AI that helps computers learn and improve from data analysis without explicit programmin­g.

The researcher­s obtained three data sets and analysed them for three different climate change scenarios: a sustainabl­e, low-emission green energy future, a 'business-as-usual' trajectory with moderate emissions, and a high fossil fuel dependency scenario with significan­tly increased greenhouse gas emissions.

"We have obtained a model that predicts with good accuracy what is now, and used this model to predict what will happen in 2050," said Valery Shevchenko, a research engineer at Skolkovo Institute of Science and Technology, Russia.

"We cannot say that this will be 100 per cent the case, because it is important to take into account many parameters here -- for example, the type of land, soil erosion," Shevchenko added.

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