期刊导航

论文摘要

基于ArcGIS和熵值法的四川省各市州耕地利用集约度时空差异研究

The Research of the Cities’ Temp-Spatial Disparity of Arable Land Use Intensity in Sichuan Province Based on Entropy and ArcGIS

作者:赵曦(武汉大学资源与环境科学学院);陈静(武汉大学资源与环境科学学院)

Author:ZHAO Xi(School of Resource and Environmental Sciences, Wuhan University);CHEN Jing(School of Resource and Environmental Sciences, Wuhan University)

收稿日期:2017-04-28          年卷(期)页码:2018,55(3):625-631

期刊名称:四川大学学报: 自然科学版

Journal Name:Journal of Sichuan University (Natural Science Edition)

关键字:耕地利用集约度, 熵值法, 标准差椭圆, 四川省各市州

Key words:arable land use intensity, the entropy method, standard deviational ellipse, cities in Sichuan Province

基金项目:国家自然科学基金(41501444)

中文摘要

本文基于熵值法和四川省复杂多样的地形,构建了包括“投入强度”、“利用强度”、“产出强度”和“可持续状况”这四个准则层,共12个指标的评价体系,以五年为一个跨度,计算出四川省各市州2006~2016年这十年的耕地利用集约度.运用标准差椭圆法,基于ArcGIS10.2软件,直观地展示了这三个时间截面上耕地利用集约度的空间分布差异和变化状况.研究结果显示:(1)四川省耕地利用集约度较高的市州位于中部偏东,其范围与成都平原基本吻合,中心位于资阳市的西北部并逐渐向东南移动,最大偏移距离为48 km;(2)2006~2011年,东北——西南轴上的市州耕地利用集约度普遍高于东南——西北方向上的市州,但逐渐放缓;2016年的标准差椭圆在各方向的差异进一步缩小.(3)四川省各市州的耕地利用集约度在三个时间截面的标准差分别为3.286,2.474和1.961,区域之间的集约利用程度趋于平衡.

英文摘要

Based on the Entropy method and the complicated landform in Sichuan Province, an evaluation system containing four criteria layers and nine indexes was established in this paper, the four criteria layers are input intensity, utilization intensity, output intensity and sustainability intensity. The arable land use intensities in the year 2006 2016 has been calculated every five years. The SDE was utilized to reveal the spatial disparities among cities and their changes with ArcGIS10.2. The research suggested that: (1) The arable land use intensities are higher in those cities located in the middle and east of Sichuan Province, mainly on the Chengdu Plain, and the centers of the three SDEs are all in the north western Ziyang City, and moved 48 km to southeast for most. (2) Between the year 2006 and 2011, the values of intensity in northeast southwestern cities had been higher than those in the other directions, and the disparities had decreased slightly all the way to 2016. (3) The standard deviations in 2006, 2011 and 2016 are 3.286, 2.474 and 1.961 respectively, which suggested a more balanced intensive arable land use between regions in Sichuan Province.

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