Analysis of Thematic Classified Aerial Images Trough Multispectral and LIDAR Data


Autoria(s): Arquero Hidalgo, Águeda; Martínez Izquierdo, María Estíbaliz
Data(s)

2011

Resumo

The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

Formato

application/pdf

Identificador

http://oa.upm.es/11218/

Idioma(s)

eng

Publicador

Facultad de Informática (UPM)

Relação

http://oa.upm.es/11218/1/INVE_MEM_2011_90994.pdf

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5876413&tag=1

info:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2011.5876413

Direitos

http://creativecommons.org/licenses/by-nc-nd/3.0/es/

info:eu-repo/semantics/openAccess

Fonte

IEEE Latin America Transactions, ISSN 1548-0992, 2011, Vol. 9, No. 1

Palavras-Chave #Informática
Tipo

info:eu-repo/semantics/article

Artículo

PeerReviewed