Análisis de imágenes aéreas clasificadas temáticamente con datos multiespectrales y LIDAR
(Analysis of thematic classified aerial images trough multispectral and LIDAR data)
Agueda Arquero Hidalgo (firstname.lastname@example.org), Estibaliz Martinez Izquierdo (email@example.com)
Universidad Politecnica de Madrid
This paper appears in: Revista IEEE América Latina
Publication Date: March 2011
Volume: 9, Issue: 1
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.
image classification, aerial photography, LIDAR (Light Detection And Ranging), hydraulic modeling
Documents that cite this
This function is not implemented yet.
[PDF Full-Text (2196)]