Impacts of Cropland Utilization Patterns on the Sustainable Use Efficiency of Cropland Based on the Human–Land Perspective

Confronted with China&rsquo:s burgeoning population and finite arable land resources, the enhancement of sustainable arable land efficiency is of paramount importance. This study, grounded in the United Nations Sustainable Development Goals (SDGs), introduces a robust framework for assessing sustainable arable land use. Utilizing the Sustainable Utilization of Arable Land (SUA) indicator system, the DGA&ndash:Super-SBM model, the Malmquist&ndash:Luenberger production index, and the TO&ndash:Fisher&ndash:OSM algorithm, we evaluated the efficiency of sustainable utilization of arable land (ESUA) in 52 prefecture-level cities within China&rsquo:s major grain-producing regions of the Yellow and Huaihai Seas. We analyzed the cropland utilization patterns from 2010 to 2020, examining the influence of these patterns on sustainable utilization efficiency. Our findings indicate that between 2010 and 2020, the arable land usage in these regions exhibited minimal transformation, primarily shifting towards construction land and conversely from grassland and water systems. Notably, the ESUA of arable land demonstrated an upward trend, characterized by pronounced spatial clustering, enduring high efficiency in the northern regions, and a significant surge in the southern sectors. The declining ESUA (D-ESUA) trend was general but increased in half of the cities. The change in the center of gravity of ESUA correlated with the north&ndash:south movement of the proportion of cultivated land area, the turn-in rate, and the turn-out rate, yet moved in the opposite direction to that of cultivated land density and yield per unit area. Variables such as the replanting index, cropland density, yield per unit area, and cropland turn-in rate significantly affected ESUA. These findings offer a scientific basis and decision-making support for optimizing the utilization pattern of arable land and achieving a rational allocation of arable land resources.