Paper Info
Title
Exploiting spectral and spatial information in hyperspectral urban data with high resolution
Abstract
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.
Year
DOI
Venue
2004
10.1109/LGRS.2004.837009
Geoscience and Remote Sensing Letters, IEEE
Keywords
Field
DocType
image morphing,image recognition,image resolution,spectral analysis,terrain mapping,DAIS data,Pavia,high resolution hyperspectral urban data,hyperspectral remote sensing,mathematical morphology,northern Italy,spatial analysis,spatial information,spatial reclassification,spectral information,Hyperspectral imaging,morphology,multiclassification,urban remote sensing
Terrain mapping,Spatial analysis,Computer vision,Mathematical morphology,Remote sensing,Hyperspectral imaging,Dais,Artificial intelligence,Spectral analysis,Land cover,Image resolution,Mathematics
Journal
Volume
Issue
ISSN
1
4
1545-598X
Citations 
PageRank 
References 
70
5.56
11
Authors
6
Name
Order
Citations
PageRank
Fabio Dell'Acqua147857.84
P. Gamba231331.71
Ferrari, A.3705.56
J. A. Palmason4705.56
J. A. Benediktsson586083.81
K. Arnason6705.56