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Proceedings Paper

Comparison analysis of agricultural land gradation evaluation based on different weight making methods
Author(s): Xiaobin Jin; Honghui Zhang; Yinkang Zhou
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Paper Abstract

Agricultural land gradation links land classification and land appraisal. It indicates the difference in agricultural productivity resulted from differences in land's natural characteristics and/or the effectiveness and efficiency of agricultural production at present and in the future. Technically, agricultural land is graded based on the sum of weighted indices and further classified by equal-distance, or axis, or sum frequency curve. It is critical to define the system of weights in this process. In practice, a single or mixed weight system has been widely applied in agricultural land gradation. However, few studies put efforts in comparing outcomes in applying different systems of weights for a specific area. This research applied several popular systems of weights, such as AHP, factor analysis, grey relation analysis, entropy method, and etc., in gradating agricultural land in Jintan, Jiangsu province. Outcomes resulted from different systems of weights were compared. The result did illustrate the obvious differences among these outcomes, which in turn stood for differences among systems of weights. Considering biases inherent in different systems of weights, a system of combined weights is highly recommended for the general practice in agricultural land gradation.

Paper Details

Date Published: 3 November 2008
PDF: 9 pages
Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 71450O (3 November 2008); doi: 10.1117/12.813001
Show Author Affiliations
Xiaobin Jin, Nanjing Univ. (China)
Honghui Zhang, Central South Univ. (China)
Changsha Urban Planning Information Service Ctr. (China)
Yinkang Zhou, Nanjing Univ. (China)


Published in SPIE Proceedings Vol. 7145:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Yong Lao, Editor(s)

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