Can We Use Machine Learning for Agricultural Land Suitability Assessment?

It is vital for farmers to know if their land suitable the crops that they plan grow. An increasing number of studies have used machine learning models based on use data as an efficient means mapping suitability. This approach relies assumption grow in best-suited areas, but no systematically tested this assumption. We aimed test specialty Denmark. First, we mapped suitability 41 using learning. Then, compared predicted suitabilities with mechanistic model ECOCROP (Ecological Crop Requirements). The results showed there was little agreement between and ECOCROP. Therefore, argue methods represent different phenomena, which label socioeconomic ecological suitability, respectively. In most cases, predicts ambiguity term can lead misinterpretation. highlight need awareness distinction a way forward agricultural assessment.