Paper
6 August 2007 A spatial cluster method for prime farmland selection
Xinqi Zheng, Weining Xiang, Jinwei Dong, Buqing Zhong
Author Affiliations +
Abstract
In China, the protection of prime farmland is a national policy of eminent importance. From an analytical perspective, its central mission, designating qualified cultivated land as prime farmland, is a comprehensive multi-attribute ranking problem. The paper first analyzed the shortcomings of the existent methods, and then proposed a spatial clustering method for prime farmland designation. The main processes were as follows: (1) Building of index system of prime farmland delimiting; (2) Evaluation of index weights according to expert knowledge; (3) Partition of study area on account of the accuracy. Data of elliptical regions that was preprocessed was put into model of spatial clustering. (4) The land parcels in same cluster is combined into larger units, ranking the result units by holistic productivity level, and selecting the super units which meet the requirement of prime farmland, finally modulating the result according to the correlated policy. The final result can be acquired. Take Jiyang County, Shandong, as a study area, the research showed that the model of selecting cultivated land into prime farmland by GA-K means spatial clustering can effectively solve the existing problems. The prime farmlands were obviously more concentrative, the isolated land parcel fragments were removed effectively, and spatial gathering level was enhanced remarkably. All that makes it a scientifically sound and practically feasible tool to protect and manage prime farmland, and monitor the prime farmland, and realize the aim of scientific and scale management.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xinqi Zheng, Weining Xiang, Jinwei Dong, and Buqing Zhong "A spatial cluster method for prime farmland selection", Proc. SPIE 6754, Geoinformatics 2007: Geospatial Information Technology and Applications, 67543J (6 August 2007); https://doi.org/10.1117/12.765573
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KEYWORDS
Agriculture

Data modeling

Soil science

Roads

Data mining

Modulation

Data acquisition

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