Extraction of urban impervious surfaces from an IKONOS image

被引：153

作者：

Lu, Dengsheng ^{[1
]}

Weng, Qihao ^{[2
]}

机构：

[1] Indiana Univ, Anthropol Ctr Training & Res Global Environm Chan, Bloomington, IN 47405 USA

[2] Indiana State Univ, Ctr Urban & Environm Change, Dept Geog Geol & Anthropol, Terre Haute, IN 47809 USA

来源：

INTERNATIONAL JOURNAL OF REMOTE SENSING | 2009年 / 30卷 / 05期

基金：

美国国家科学基金会;

关键词：

LAND-COVER CHANGE; VEGETATION ABUNDANCE; SYNERGISTIC USE; SOIL MODEL; CLASSIFICATION; AREA; URBANIZATION; ACCURACY; ANATOMY; QUALITY;

D O I：

10.1080/01431160802508985

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

Impervious surface has been recognised as an important indicator in urban environmental assessment. However, accurate extraction of impervious surface information in urban areas is a challenge because of the complexity of impervious materials. This paper explores different approaches for impervious surface extraction with IKONOS imagery in Indianapolis, U.S.A., by using decision tree classifier (DTC) and linear spectral mixture analysis (LSMA). This research indicates that DTC is an effective approach for extraction of different impervious surface classes, including high-, medium- and low-reflectivity impervious surfaces and that LSMA-based approach can provide quantitative measure of imperviousness. A critical step is to separate dark impervious objects/features from shadows cast by tall buildings and tree canopy and from water.

引用

页码：1297 / 1311

页数：15

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