地理研究

地理研究 ›› 2005, Vol. 24 ›› Issue (2): 311-320.doi: 10.11821/yj2005020018

• 论文 • 上一篇    

基于谱间特征和归一化指数分析的城市建筑用地信息提取

徐涵秋   

  1. 福州大学环境与资源学院, 福建福州 350002
  • 收稿日期:2004-08-20 修回日期:2004-11-26 出版日期:2005-04-15 发布日期:2005-04-15
  • 作者简介:徐函秋(1955-).男.汉族.江苏射阳人.博士.教授.博导主要从事环境与资源遥感应用研究.己在含SCI收录的国内外刊物上发表论文数十篇.Email:fdy@public.fz.fj.cn
  • 基金资助:

    国家自然科学基金资助项目(40371107)福建省科技三项资助项目(K03011)

Fast information extraction of urban built-up land based on the analysis of spectral signature and normalized difference index

XU Han-qiu   

  1. College of Environments and Resources, Fuzhou University, Fuzhou 350002, China
  • Received:2004-08-20 Revised:2004-11-26 Online:2005-04-15 Published:2005-04-15

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261 | 36

摘要：

以福州市ETM+影像为例,研究了城市建筑用地信息快速准确提取的原理和方法。通过对归一化差异型指数构成原理的分析以及对同名异义和异名同义现象的甄别,选取了归一化差异建筑指数(NDBI)、修正归一化差异水体指数(MNDWI)和土壤调节植被指数(SAVI)来代表城市建成区的三种最主要的土地利用类型--建筑用地、水体和植被。在此基础上进一步对这三个新的指数波段进行谱间特征分析,最后利用基于规则的逻辑判别运算将城市建筑用地信息提取出来。研究表明这一方法可以使繁杂的多波段谱间分析得以简化, 是一种快速准确、未经人工干预的建筑用地信息提取方法。本文还探讨了在城市建成区的研究中采用SAVI指数替代NDVI指数的优点。

关键词: 城市建筑用地, 遥感信息提取, 光谱分析, NDBI, SAVI, MNDWI

Abstract:

This paper studies the principles and method of fast remote-sensing information extraction for urban built-up land, taking Fuzhou city as an example. With the detailed analysis and clarity of several existing normalized difference indices, the study selects three indices, Normalized Difference Built-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI) and Soil Adjusted Vegetation Index (SAVI) to represent three major urban land use/cover classes, i. e. , built-up land, water body and vegetation, respectively. The three index images are generated from a Landsat ETM + subscene of Fuzhou city and then used as three bands to compose a new image. This dramatically compresses the original eight-band ETM+ image into a three-band image, reduces band correlations and data redundancy, thus significantly simplifiying the band spectral analysisprocedures. The spectral signature analysis only needs to be performed on this three-index composite image and the signature differences among the three major urban land use/cover classes are revealed much easier than being done with multi-bands. Based on the revealed signature differences, the built-up land is finally extracted through a simple logic calculation. The result achieves a 91.3% overall accuracy. Therefore, the method is a fast and accurate one for the remote-sensing information extraction of urban land use without human interference. In addition to the above built-up land information extraction study, the paper proposes a Modified Normalized Difference Water Index (MNDWI) based on the NDWI of Mcfeeters (1996) , which uses MIR wavelength (ETM + band 5) instead of NIR wavelength to construct the index. The replacement largely enhances the contrast of the water bodies with the other land use/cover classes and reduces the spectral confusion with the other classes. Therefore, the MNDWI is more suitable for delineating features of polluted urban rivers/lakes. The advantages of using SAVI instead of NDVI in the urban study are also discussed in this paper.

Key words: urban built-up land, remote sensing information extraction, spectral signature analysis, NDBI, SAVI, MNDWI