土地利用

基于MODIS 数据的长江三角洲地区土地覆盖分类

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  • 1. 南京信息工程大学遥感学院中美合作遥感中心, 南京210044;
    2. 北京市气象局气候中心, 北京100089
徐永明(1980-), 男, 硕士, 助理工程师, 主要从事资源环境遥感、全球变化方面的研究。 E-mail: xym30@263.net

收稿日期: 2006-11-17

  修回日期: 2007-01-17

  网络出版日期: 2007-06-25

基金资助

国家自然科学基金重点项目(40333027); 国家自然科学基金项目(60674074); 南京信息工程大学科研基金项 目(Y653)

Land Cover Classification of the Yangtze River Delta Using MODIS Data

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  • 1. Sino-America Cooperative Remote Sensing Center, School of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing 210044, China;
    2. Climate Center, Beijing Meteorological Bureau, Beijing 100089, China

Received date: 2006-11-17

  Revised date: 2007-01-17

  Online published: 2007-06-25

Supported by

National Natural Science Foundation of China, No.40333027; No.60674074; Scientific Research Foundation of Nanjing University of Information Science and Technology, No.Y653

摘要

长江三角洲地区是我国经济最发达的地区之一, 人类活动对自然环境产生了很大影响。为了研究该地区人类活动与生态环境的相互作用, 利用250 m 分辨率MODIS 数据进行土地 覆盖制图研究, 采用的主要数据为增强型植被指数EVI 数据、反射率数据和DEM 数据。通过基于时间序列的滤波方法消除EVI 的噪声, 通过PCA 变换压缩数据量, 并计算均质度来表征空间维的纹理信息, 构造了一个综合性的分类数据矩阵, 依据高分辨率影像选取了训练区, 采用最大似然法进行分类, 并采用缓冲区分析技术进行分类修正, 得到长江三角洲地区的土地覆盖分类结果。利用高分辨率影像解译信息对分类结果进行了精度评价, 并将分类结果与 MODIS 土地覆盖产品进行了对比, 精度分析表明分类结果很好的反映了研究区的土地覆盖信息, 显示了本研究分类方法与技术处理在实践中的可行性及250 m 分辨率EVI 时间序列数据在区域尺度土地覆盖分类方面的优势与潜力。

本文引用格式

徐永明, 刘勇洪, 魏鸣, 吕晶晶 . 基于MODIS 数据的长江三角洲地区土地覆盖分类[J]. 地理学报, 2007 , 62(6) : 640 -648 . DOI: 10.11821/xb200706009

Abstract

The Yangtze River Delta is one of the most economically developed regions in China. During the last decade, this area experienced rapid urban expansion, and accordingly, masses of cropland have been converted into human buildings. To analyze the influence of landscape change, it is important to provide up-to-date land cover information of this area. This paper describes the development of land cover map of the Yangtze River Delta using 250 m MODIS data, and the main satellite data used in this study were MODIS EVI data, MODIS reflectance data and DEM. A filter method based on time series was applied to eliminate EVI noise, and a PCA analysis was performed to reduce the volume of data. Besides, homogeneity was calculated to present spatial texture information. Therefore, a compositive classification matrix was generated. Considering the natural and artificial conditions of the Yangtze River Delta, a classification scheme was defined. ROIs (Region of Interest) were selected from Landsat ETM+ images by human interpretation consulting the 1: 1,000,000 Vegetation Atlas of China. Then the land cover map was generated using MLC method. After correction by buffering analysis, we got the final land cover classification of the Yangtze River Delta. The classification accuracy was assessed using fine-resolution Landsat images, with an overall accuracy of 95.98% . In addition, our classification result was compared with the MODIS-IGBP land cover production and showed better accuracy. The good result indicated the good behavior of the classification method and technical processing used in our research, and also suggested the advantage of 250 m MODIS data in regional land cover mapping.

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