Efficient agricultural land management increasingly requires the integration of operational, environmental, and spatial factors influencing field performance.This study presented an updated nationwide classification of agricultural land parcels in the Czech Republic according to their suitability for shape optimisation.The classification was based on a multi-criteria analysis (MCA) integrating ten criteria describing terrain morphology, parcel geometry, accessibility constraints, and soil susceptibility to machinery-induced compaction.The analysis was applied to 301 558 arable land parcel identification system (LPIS) agricultural parcels covering 2.49 million hectares.The resulting suitability index classified parcels into four categories representing increasing levels of spatial complexity and optimisation potential.The results revealed a strong relationship between parcel suitability classes and terrain conditions.Classes III and IV, representing the parcels with high optimisation potential, accounted for 39.3% of the national arable land area and were most frequently associated with larger parcels and topographically heterogeneous landscapes.The resulting nationwide map layer provides a decision-support tool for the identification of the agricultural parcels requiring shape optimisation or spatial reconfiguration.
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Lang et al. (2026) studied this question.
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