资源科学 ›› 2016, Vol. 38 ›› Issue (1): 83-92.doi: 10.18402/resci.2016.01.09

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基于贝叶斯概率模型的鄂西北山地区耕地整治适宜性评价

胡学东1(), 王占岐1(), 邹利林2   

  1. 1. 中国地质大学(武汉)公共管理学院,武汉 430074
    2. 华侨大学公共管理学院,泉州 362021
  • 收稿日期:2015-03-13 修回日期:2015-06-18 出版日期:2016-01-25 发布日期:2016-01-25
  • 作者简介:

    作者简介:胡学东,男,湖北黄石人,博士生,主要从事土地利用规划和土地经济研究。E-mail:huxuedongcug@126.com

  • 基金资助:
    基金项目: “十二五”国家科技支撑计划课题:“用地网络化综合监管信息平台优化关键技术研究”(2013BAJ05B02)

Suitability evaluation of arable land consolidation in mountain areas of Northwestern Hubei based on Bayesian Probability Modeling

HU Xuedong1(), WANG Zhanqi1(), ZOU Lilin2   

  1. 1. School of Public Administration,China University of Geosciences(Wuhan),Wuhan 430074,China
    2. College of Public Administration,Huaqiao University,Quanzhou 362021,China
  • Received:2015-03-13 Revised:2015-06-18 Online:2016-01-25 Published:2016-01-25

摘要:

在中国耕地保护形势日益严峻的情况下,如何在山地区开展耕地整治项目布局,提高耕地整治效率,是当前开展山地区土地整治规划工作的重要内容,而耕地整治适宜性评价则是耕地整治项目布局的前提。本文以鄂西北山地区房县为研究区域,选取灌溉保证率、地形坡度、土壤质地、有效土层厚度、耕地系数、与道路距离、与城镇中心距离和田块规模指数8个评价指标,运用贝叶斯概率模型计算影响因素权重和耕地整治的后验概率,并得到研究区耕地整治的适宜性分布图,最后进行预测结果检验。结果表明:①在影响山地区耕地整治的因素中,耕地系数、灌溉保证率、地形坡度、与道路距离四个因素对耕地整治影响程度比田块规模指数、有效土层厚度、与城镇中心距离和土壤质地4个因素对耕地整治的影响程度大;②对2013年耕地整治项目布局与适宜性分布图进行对比分析,有88.81%处于适宜性整治区,说明该模型具有可行性。该文可为耕地整治适宜性评价提供方法借鉴,并为鄂西北山地区更合理科学地开展土地整治规划提供依据。

关键词: 土地利用, 耕地整治, 适宜性评价, 贝叶斯概率模型, 山地区

Abstract:

How to arrange arable land consolidation projects and improve the efficiency of arable land consolidation in mountain areas under increasingly serious arable land protection situation is an important component of land consolidation planning. And suitability evaluation of arable land consolidation is the premise of arable land consolidation projects arrangement. Taking Fang county in northwest Hubei,China as a case study,we first selected eight affecting factors, including irrigation assurance rate,terrain slope,soil texture,effective soil layer thickness,arable land coefficient,distance to road,distance to town center and field scale index, to characterize the arable land consolidation suitability. The weight values of affecting factors and posterior probability of arable land consolidation were calculated to obtain a distribution map of arable consolidation suitability by Bayesian Probability Modeling. We found that among factors affecting arable land consolidation of mountain areas,arable land coefficient,irrigation assurance rate,terrain slope and distance to road have more influence on arable land consolidation than others. A total of 88.81% of the area is distributed in suitable arable consolidation areas when comparing arable land consolidation placing in 2013 with predictions of arable consolidation suitability; this indicates the model is feasible. These data provide a reference for suitability evaluation of arable land consolidation and can contribute to the practicability of land consolidation planning in mountainous areas in China.

Key words: land use, arable land consolidation, suitability evaluation, Bayesian Probability Model, mountain area