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Optimizing arable land suitability evaluation using improved suitability functions in the Anning River Basin. | LitMetric

Optimizing arable land suitability evaluation using improved suitability functions in the Anning River Basin.

Sci Rep

State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, 610059, China.

Published: November 2024

Conducting arable land suitability evaluation (ALSE) is essential for identifying agricultural development opportunities and ensuring sustainable production and food security. Traditional ALSE methods, relying on suitability proportion functions, often encounter constraints due to land use structures. Therefore, it is necessary to develop new function methods to avoid the constraints imposed by land use structures, thus making ALSE more convenient. This study aims to propose a novel set of rules for constructing proportion functions, aiming to enhance the applicability of suitability functions in arable land suitability evaluation. The study findings reveal that: (1) In the Anning River Basin, the highly Suitable, Moderately Suitable, and Marginally Suitable current arable land (CAL) respectively account for 45.3%, 29.8%, and 18.9% of the arable land (AL). The proportion of areas deemed Temporarily Unsuitable and Permanently Unsuitable is only 6%. The distribution of suitability levels for the potential arable land (PAL) is relatively uniform, with a proportion of suitable areas reaching 66.1%, indicating substantial development potential. (2) The agricultural production conditions in the arid and warm river valley area of the Anning River Basin are exceptional. Highly Suitable CAL and Highly Suitable PAL cover 93.14% and 82.97% of this region, respectively, making it a focal point for regional agricultural development. (3) The spatial distribution patterns of ALSE results based on the original function and the improved function are essentially consistent. However, there are significant differences among the suitability levels. The correlation analysis results indicate that the evaluation results based on the improved function are closer to reality. This study enhanced the accuracy of ALSE results based on the suitability function. It provided a new approach for evaluating the suitability of AL and offers a beneficial reference for regional arable land resource utilization and sustainable agricultural development.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11582588PMC
http://dx.doi.org/10.1038/s41598-024-80302-8DOI Listing

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