• 方法模型与应用 •

### 基于矢量数据的土地利用类型分维数计算程序设计及其应用

1. 1. 湖北大学资源环境学院|武汉430062； 2. 西北师范大学地理与环境科学学院|兰州 730070
• 出版日期:2010-03-25 发布日期:2010-03-25
• 通讯作者: 王倩，主要从事GIS二次开发和图像分类算法研究。 E-mail:wangq306@163.com
• 作者简介:汪权方(1974-)|女|安徽枞阳人|博士|副教授|主要从事土地遥感研究。E-mai: wangqf@hubu.edu.cn
• 基金资助:

国家自然科学基金项目（40601003）；湖北省教育厅青年项目(Q200610002)

### Programming on Calculating Fractal Dimension of Land Use Types for 2D Vector Data

WANG Quanfang1, WANG Qian1, ZHANG Qipeng2, MEI Xin1

1. 1. Faculty of Resources and Environmental Science Hubei University, Wuhan 430062, China|
2. College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, China
• Online:2010-03-25 Published:2010-03-25

Abstract:

Nowadays the fractal dimension is often calculated on raster data, but most of existing land-use data is stored as vector data in fact. If these vector data are converted to images to calculate fractal dimension, perhaps some pixels with inaccurate grey values will be resulted from the “GRID” structure of raster data. The precision calculated on raster data is closely related to the size of pixel and grid image. In this paper, a computation program for the fractal dimension of 2D vector data based on Windows platform has been designed by using Visual C sharp. Now the program has been successfully applied to land-use data of the middle Qinling Mountains and the southeast of Hubei Province in China. The results show that the program is a convenient, reliable and precise method for the fractal dimension of 2D vector data. The land use and land cover types arranged in the descending order of their average stability indices are as follows. 1) The fractal dimensions of the middle Qinling Mountains are in the order of construction land > unutilized land> paddy field > dry upland > grassland > forestland > water area in 1990, 1995 and 2000. 2) The fractal dimensions of the southeast of Hubei Province in China are in the order of paddy field > unutilized land > construction land > dry upland > forestland > grassland > water area in 1990, 1995 and 2000. In a word, forestland, water area and grassland have poorer stability and higher possibility of changes in the two study areas.