Exploiting Spectral and Spatial Information in Hyperspectral Urban Data With High Resolution

被引：194

作者：

Dell'Acqua, F. ^{[1
]}

Gamba, P. ^{[1
]}

Ferrari, A. ^{[1
]}

Palmason, J. A. ^{[2
]}

Benediktsson, J. A. ^{[2
]}

Arnason, K. ^{[2
]}

机构：

[1] Univ Pavia, Dept Elect, I-27100 Pavia, Italy

[2] Univ Iceland, IS-107 Reykjavik, Iceland

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2004年 / 1卷 / 04期

关键词：

Hyperspectral imaging; morphology; multiclassification; urban remote sensing;

D O I：

10.1109/LGRS.2004.837009

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Very high resolution hyperspectral data should be very useful to provide detailed maps of urban land cover. In order to provide such maps, both accurate and precise classification tools need, however, to be developed. In this letter, new methods for classification of hyperspectral remote sensing data are investigated, with the primary focus on multiple classifications and spatial analysis to improve mapping accuracy in urban areas. In particular, we compare spatial reclassification and mathematical morphology approaches. We show results for classification of DAIS data over the town of Pavia, in northern Italy. Classification maps of two test areas are given, and the overall and individual class accuracies are analyzed with respect to the parameters of the proposed classification procedures.

引用

页码：322 / 326

页数：5

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