Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64885
Title: Application of LiDAR’s multiple attributes for wetland classification
Authors: Ding, Q
Ji, S
Chen, W 
Keywords: Ecosystems
LIDAR
Vegetation
Issue Date: 2016
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2015, v. 9901, 990110 How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
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% © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Description: 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), Xiamen, China, 28 April 2015
URI: http://hdl.handle.net/10397/64885
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.2234678
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