浙江农业学报 ›› 2016, Vol. 28 ›› Issue (12): 2116-2122.DOI: 10.3969/j.issn.1004-1524.2016.12.22

• 食品科学 • 上一篇    下一篇

果品产量统计数据空间离散化研究——以北京平谷区为例

刘玉1, 范文洋2, 郜允兵1,*, 唐林楠1   

  1. 1.国家农业信息化工程技术研究中心,北京 100097;
    2.北京舜土规划顾问有限公司,北京 100070
  • 收稿日期:2016-04-05 出版日期:2016-12-15 发布日期:2017-01-05
  • 通讯作者: 郜允兵,E-mail:Gaoyb@nercita.org.cn
  • 作者简介:刘玉(1982—),男,河北无极人,博士,副研究员,主要从事土地利用、区域农业与农村发展研究。E-mail: Liuyu@nercita.org.cn
  • 基金资助:
    国家自然科学基金项目(41201173, 41301093)

A method of spatial discretization of statistical fruit production: A case study of Pinggu District in Beijing

LIU Yu1, FAN Wen-yang2, GAO Yun-bing1,*, TANG Lin-nan1   

  1. 1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China;
    2. Beijing SINOSUNTOP Planning Consultation Co., Ltd, Beijing 100070, China
  • Received:2016-04-05 Online:2016-12-15 Published:2017-01-05

摘要: 果品产量是衡量区域农产品生产功能的重要指标。果品产量的空间离散化,有助于揭示区域内部要素的空间差异性和获取微观尺度的果品产量数据。该研究依据地形起伏度和土地利用分区将平谷区划分为平原区、浅山区和深山区,并分别建立离散化模型进行修正,将村果品产量离散到500 m×500 m格网下的果园图斑上。结果表明:(1)村果品模拟产量与果品实际产量的相关性系数由总体样本建模的0.585提高到分区建模的0.690,表明分区建模是一种有效的方法。(2)各区影响因素与产量的关系存在差异。平原区果园面积对果品产量呈现线性影响;浅山区和深山区果园面积对果品产量的影响较为剧烈,呈幂指数关系,并且增加海拔高度和坡度2个变量后模型的拟合效果均有改善。(3)在自然环境、社会经济等综合影响下,平谷区果品产量呈现地带性分布。其中,产量较高的区域集中分布于地形相对平缓、自然本底较好、农民劳作便利的浅山带;而平原区和深山区分别受政策限制和地形限制,果品产量相对较低。

关键词: 果品产量, 土地利用, 空间离散化, 平谷区

Abstract: Spatial discretization of fruit production was of great help to deeply learn the spatial diversity in small scaled districts, and provide guidance for those areas lacking fruit statistical data to develop the spatial discretization method. Based on Pinggu's overall plan of land use and surface rolling, this study built discretization model for plain, hill and mountain's areas, respectively, and then selected appropriate correction method to discrete the fruit output from village to 500 m×500 m's grid size. The results were shown as follows: (1) Compared with the simulation results of overall samples, the correlation between predicted output and actual fruit output increased from 0.585 to 0.690, which meant the partition modeling was an effective method. (2) There were differences in the relationship between the influence factors and fruit output. The orchard area in plain area had a linear effect on fruit output. Differently, the orchard area in shallow mountain area and deep mountain area had an exponential effect on fruit output, and the fitting effect improved significantly after increasing the elevation and slope variables. (3) In 2012, influenced by natural geographical factors, fruit production presented an obvious zonal distribution. The villages with higher output mainly lay in the shallow hills with relatively flat terrain, good natural background and convenient working environment for farmers. Instead, limited by policy or terrain, the fruit output in the plain and deep mountains was relatively low.

Key words: fruit production, land use, space discretization, Pinggu District

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