Potential of temporal information of high density airborne LiDAR data forinstream flow type classification

Yu Li Lin, Chi Kuei Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Instream habitat mapping is an important task for river management. Remote sensing techniques have been successfully applied to replace the conventional method of habitat mapping due to the disadvantages of conventional method like expansive, labor intensive and time-consuming. Airborne LiDAR (Light Detection And Ranging) combining standard deviation analysis has been proved to be effective for instream habitat mapping in the last research. In this research, we improved the point density of LiDAR data and collected the ground truth data with the aim of GPS for accurate positioning. New methods using temporal information of water surface to discriminate instream flow types are tested and compare to the original method. The result shows that standard deviation of average surface elevation provides the best classification accuracy, and as the LiDAR technique improved, it has a great potential to be a useful tool for instream flow type classification in the future.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Pages1030-1035
Number of pages6
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Volume2

Other

Other32nd Asian Conference on Remote Sensing 2011, ACRS 2011
CountryTaiwan
CityTapei
Period11-10-0311-10-07

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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