A multi-window texture classification and object-oriented feature extraction method with airborne LiDAR products

Author

Zhu, Xiaokun ; Toutin, Thierry

Author_Institution

Beijing Inst. of Surveying & Mapping, Beijing, China

fYear

2011

fDate

24-29 July 2011

Firstpage

3370

Lastpage

3373

Abstract

High accurate airborne Light Detection and Range (LiDAR) is widely accepted as one kind of survey data sources. However, with the LiDAR products including Digital Elevation Model (DEM), Digital Surface Model (DSM) and intensity image, land use classifications and feature extractions were generally combined with optical images including satellite images or aerial photos using relative segmentations and feature extraction algorithms. In this paper, a multi-window texture classification and object- oriented feature extraction method is proposed using only airborne LiDAR products. Based on the experimental analysis and accuracy statistics, it is an efficient attempt in land cover classification with airborne LiDAR products.

Keywords

feature extraction; geophysical image processing; image classification; image texture; object detection; optical radar; remote sensing; DEM; DSM; accuracy statistics; aerial photos; airborne LIDAR products; digital elevation model; digital surface model; high accurate airborne light detection and range; intensity image; multiwindow texture classification; object-oriented feature extraction method; optical images; relative segmentations; satellite images; Accuracy; Buildings; Data mining; Feature extraction; Laser radar; Vegetation mapping; Wires; Image Classification; Image Texture Analysis; Land Surface; LiDAR; Object Oriented Methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International

Conference_Location

Vancouver, BC

ISSN

2153-6996

Print_ISBN

978-1-4577-1003-2

Type

conf

DOI

10.1109/IGARSS.2011.6049941

Filename

6049941