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Classification of agricultural land consolidation types based on soil security to improve limiting factors adapted to local soil conditions

Bibliographic Data

ID21648321
AuthorsRui Zhao (0000-0001-6445-3461, School of Land Science and Technology China University of Geosciences (Beijing) Beijing PR China), Xiaodan Zhang (0000-0003-3579-953X, Zhongcheng Think Tank (Urbanization Research Institute) Beijing City University Beijing PR China), Jose Luis Gabriel (0000-0002-5508-4120, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA, CSIC) Madrid Spain), José Antonio Rodríguez Martín (0000-0002-9158-9564, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA, CSIC) Madrid Spain), Kening Wu (0000-0001-7995-1666, School of Land Science and Technology China University of Geosciences (Beijing) Beijing PR China, corresponding author)
Year2023
Volume34
Issue11
Pages3098-3113
Publication date2023-07-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.4669
OpenAlexW4322503662
LanguageEN
Citations received1
References cited70

Agricultural land consolidation (ALC) is an effective tool to ensure national food security. The current ALC is a government‐led systematic behavior with regional characteristics, most ALC types are classified according to difficulty without considering the safety of soil systems, resulting in randomness in the site selection of projects. Given the soil complexity, ensuring soil security (SS) is a prerequisite for efficiently completing ALC. ALC that gives full play to the soil's functional advantages is an effective means of securing SS. The main goal of this study is to establish a new set of technical processes for classifying the types of ALC from the perspective of SS, including the agricultural SS evaluation system and the identification method of land‐improvable limiting factors. We used a generalized mean model to evaluate and analyze SS in multiple dimensions and identified 11 combinations of limiting factors in Wen County through the k‐means clustering method. The combination of the limiting factor clustering area with the SS spatial distribution patterns guided five ALC types. When compared using the spatial pattern comparison method, the new ALC guideline avoids the singularity of ALC types, selects the field patch as the evaluation and decision‐making unit, and improves the accuracy of land management measures. The results indicate that incorporating SS into ALC policy planning and decision‐making can provide complex and multifaceted knowledge of factors affecting SS, and potential solutions to make agricultural soils safer, enabling higher quality and sustainability of agricultural land use

Agricultural engineering · Agricultural land · Civil engineering · Cluster analysis · Environmental economics · Environmental resource management · Land use · Machine learning · Soil biodiversity · Soil fertility · Soil functions · Soil Quality · Soil water · Computer Science · Engineering · Environmental Science · Land Rights and Reforms · Land Use and Ecosystem Services · Soil erosion and sediment transport · Soil Science

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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