Share Email Print

Proceedings Paper

Application of LiDAR’s multiple attributes for wetland classification
Author(s): Qiong Ding; Shengyue Ji; Wu Chen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Wetlands have received intensive interdisciplinary attention as a unique ecosystem and valuable resources. As a new technology, the airborne LiDAR system has been applied in wetland research these years. However, most of the studies used only one or two LiDAR observations to extract either terrain or vegetation in wetlands. This research aims at integrating LiDAR’s multiple attributes (DSM, DTM, off-ground features, Slop map, multiple pulse returns, and normalized intensity) to improve mapping and classification of wetlands based on a multi-level object-oriented classification method. By using this method, we are able to classify the Yellow River Delta wetland into eight classes with overall classification accuracy of 92.5%

Paper Details

Date Published: 2 March 2016
PDF: 6 pages
Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 990110 (2 March 2016); doi: 10.1117/12.2234678
Show Author Affiliations
Qiong Ding, Guangdong Univ. of Technology (China)
Shengyue Ji, China Univ. of Petroleum (China)
Wu Chen, Hong Kong Polytechnic Univ. (China)

Published in SPIE Proceedings Vol. 9901:
2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015)
Cheng Wang; Rongrong Ji; Chenglu Wen, Editor(s)

© SPIE. Terms of Use
Back to Top