Beyond general thresholds: A soil-based, data-driven identification of marginal agricultural lands

Marginal agricultural lands, characterised by limited productivity and constrained suitability for conventional farming, represent a growing challenge for sustainable land management and agricultural planning. While several review studies have proposed generalised threshold values to identify marginal conditions, these broad definitions often fail to capture regional heterogeneity. Consequently, robust delineation requires approaches that derive thresholds directly from the characteristics of the study area, combining data-driven analysis with decision-relevant thresholds. In this study, we developed a geospatial framework to delineate marginal croplands across Hungary using high-resolution (100 m) spatial data. Soil properties, topographic variables, and climatic indicators were analysed at the pixel level. Marginality was assessed without relying on a single dependent variable, instead applying multiple threshold-based approaches to identify unfavourable conditions across individual variables. Thresholds were derived using complementary data-driven methods, including univariate unsupervised techniques such as Gaussian Mixture Models, one-dimensional clustering, and percentile-based classification. In parallel, expert-based threshold definitions were applied using distribution-based rescaling with predefined class boundaries. Each variable was evaluated independently to derive marginality scores, which were subsequently analysed by thematic categories (soil and environmental) and combined into an integrated marginality assessment. The results show consistent spatial patterns of agricultural marginality across Hungary, driven mainly by soil-related limitations, topographic constraints, and climate. Spatial agreement among different threshold-based classifications identifies areas of stable marginality, whereas disagreement delineates transitional zones influenced by methodological choices. The framework allows systematic comparison of threshold-based delineations of marginal agricultural lands.