TerraSAR-X/SPOT-5 Fused Images for Supervised Land Cover Classification

Author

Burini, A. ; Putignano, C. ; Del Frate, F. ; Licciardi, G. ; Pratola, C. ; Schiavon, G. ; Solimini, D.

Author_Institution

GEO-K s.r.l., Rome

Volume

5

fYear

2008

fDate

7-11 July 2008

Abstract

This paper reports the study of supervised neural network algorithm for classification purposes. SPOT 5 and TerraSAR-X dataset are analyzed. Classification results are critically discussed and compared to ground truth map and unsupervised neural classification of the same area. The aim is to demonstrate the capability of neural networks in managing heterogeneous dataset and the accuracy improvement obtained by the use of the textural object based layers fused with the optical and radar data.

Keywords

geophysical signal processing; geophysical techniques; image classification; image fusion; image texture; neural nets; remote sensing; SPOT-5; TerraSAR-X; ground truth map; image fusion; supervised land cover classification; supervised neural network; textural object based layers; unsupervised neural classification; Algorithm design and analysis; Classification algorithms; Data analysis; Laser radar; Neural networks; Optical computing; Optical sensors; Radar imaging; Shape; Testing; Data Fusion; Neural Network; TerraSAR-X;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4780106

Filename

4780106