中国地理科学(英文版) ›› 2009, Vol. 19 ›› Issue (3): 283-290.doi: 10.1007/s11769-009-0283-x

• 论文 • 上一篇    

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

YUE Wenze   

  1. Department of Land Management, Zhejiang University, Hangzhou 310029, China
  • 收稿日期:2008-12-22 修回日期:2009-05-04 出版日期:2009-09-20 发布日期:2009-11-28
  • 通讯作者: YUE Wenze.E-mail:wzyue@zju.edu.cn E-mail:wzyue@zju.edu.cn
  • 基金资助:

    Under the auspices of National Natural Science Foundation of China (No.40701177)

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

YUE Wenze   

  1. Department of Land Management, Zhejiang University, Hangzhou 310029, China
  • Received:2008-12-22 Revised:2009-05-04 Online:2009-09-20 Published:2009-11-28
  • Supported by:

    Under the auspices of National Natural Science Foundation of China (No.40701177)

摘要:

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

关键词: vegetation-impervious surface-soil model, spectral mixture analysis, impervious surface, Shanghai

Abstract:

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

Key words: vegetation-impervious surface-soil model, spectral mixture analysis, impervious surface, Shanghai