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Agricultural suitability assessment should distinguish between “socioeconomic suitability” and “ecological suitability”, study shows.

Published on
July 16, 2021

Researchers of Soil Geography and Landscape co-authored a paper testing the added value of machine learning for land suitability assessments, allowing the integration of both environmental and socioeconomic processes for assessing the suitability of agricultural land. The authors found that socioeconomic factors, for example distance to cities, play a role at the farmers’ decisions which crops to grow, and should therefore be considered beside purely soil- and climate driven assessment of agricultural land use suitability.

More information: Machine learning creates ways to better assess the suitability of agricultural land

The paper: Can We Use Machine Learning for Agricultural Land Suitability Assessment?