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Classifier Fusion of Hyperspectral and Lidar Remote Sensing Data For Improvement of Land Cover Classification

Bigdeli, Behnaz and Samadzadegan, Farhad and Reinartz, Peter (2013) Classifier Fusion of Hyperspectral and Lidar Remote Sensing Data For Improvement of Land Cover Classification. In: ISPRS International Conference on Sensors and Models in Photogrammetry and Remote Sensing, XL-1/W, pp. 97-102. ISPRS Archives. SMPR 2013, 05.-08. Okt. 2013, Tehran, Iran. ISBN doi:10.5194/isprsarchives-XL-1-W3-97-2013

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Official URL: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W3/

Abstract

The interest in the joint use of remote sensing data from multiple sensors has been remarkably increased for classification applications. This is because a combined use is supposed to improve the results of classification tasks compared to single-data use. This paper addressed using of combination of hyperspectral and Light Detection And Ranging (LIDAR) data in classification field. This paper presents a new method based on the definition of a Multiple Classifier System on Hyperspectral and LIDAR data. In the first step, the proposed method applied some feature extraction strategies on LIDAR data to produce more information in this data set. After that in second step, Support Vector Machine (SVM) applied as a supervised classification strategy on LIDAR data and hyperspectal data separately. In third and final step of proposed method, a classifier fusion method used to fuse the classification results on hypersepctral and LIDAR data. For comparative purposes, results of classifier fusion compared to the results of single SVM classifiers on Hyperspectral and LIDAR data. Finally, the results obtained by the proposed classifier fusion system approach leads to higher classification accuracies compared to the single classifiers on hyperspectral and LIDAR data.

Item URL in elib:https://elib.dlr.de/86433/
Document Type:Conference or Workshop Item (Speech)
Title:Classifier Fusion of Hyperspectral and Lidar Remote Sensing Data For Improvement of Land Cover Classification
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bigdeli, Behnazbigdeli (at) ut.ac.irUNSPECIFIED
Samadzadegan, Farhadfarhad.samadzadegan (at) dlr.deUNSPECIFIED
Reinartz, PeterPeter.Reinartz (at) dlr.deUNSPECIFIED
Date:October 2013
Journal or Publication Title:ISPRS International Conference on Sensors and Models in Photogrammetry and Remote Sensing
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:XL-1/W
Page Range:pp. 97-102
Editors:
EditorsEmail
Arefi, Hosseinhossein.arefi@dlr.de
Sharifi, M.Universtity of Tehran
Reinartz, Peterpeter.reinartz@dlr.de
Delawar, M.University of Tehran
Publisher:ISPRS Archives
Series Name:International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISBN:doi:10.5194/isprsarchives-XL-1-W3-97-2013
Status:Published
Keywords:Hyperspectral data, LIDAR data, Classification, Classifier fusion
Event Title:SMPR 2013
Event Location:Tehran, Iran
Event Type:international Conference
Event Dates:05.-08. Okt. 2013
Organizer:University of Tehran
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Reinartz, Prof. Dr.. Peter
Deposited On:09 Dec 2013 07:50
Last Modified:31 Jul 2019 19:43

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