Title :
Joint VHR - LIDAR classification framework in urban areas using a priori knowledge and post processing shape optimization
Author :
Gamba, Paolo ; Lisini, Gianni ; Tomás, Lívia ; Almeida, Cláudia ; Fonseca, Leila
Author_Institution :
Dept. of Electron., Univ. of Pavia, Pavia, Italy
Abstract :
In this paper we describe a joint methodology for exploiting multispectral and LIDAR data for the characterization of an urban area. The test site is the town of Uberlandia (Brazil). We first discuss the overall framework for 2D and 3D data fusion, and then introduce the approach investigated in this work. We then provide and discuss the mapping results obtained in our investigation. Finally, in order to increase the overall accuracy and enhance the extraction of single building/composite block shapes, a post-classification procedure is applied to the obtained map.
Keywords :
optical radar; optimisation; pattern classification; remote sensing by radar; sensor fusion; shape recognition; town and country planning; VHR-LIDAR classification framework; data fusion; multispectral data; post processing shape optimization; priori knowledge; urban areas; Buildings; Joints; Laser radar; Roads; Shape; Three dimensional displays; Urban areas;
Conference_Titel :
Urban Remote Sensing Event (JURSE), 2011 Joint
Conference_Location :
Munich
Print_ISBN :
978-1-4244-8658-8
DOI :
10.1109/JURSE.2011.5764727
