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dc.contributor.advisorOlsen, Richard C.
dc.contributor.advisorMetcalf, Jeremy P.
dc.contributor.authorDavis, Andrew S.
dc.date.accessioned2018-08-24T22:35:08Z
dc.date.available2018-08-24T22:35:08Z
dc.date.issued2018-06
dc.identifier.urihttp://hdl.handle.net/10945/59646
dc.descriptionApproved for public release. distribution is unlimiteden_US
dc.description.abstractThe aim of this study was to analyze discrete and waveform data to improve existing Terrain Classification (TERCAT) capabilities. Light Detection and Ranging (LiDAR) data were collected over the Point Lobos State Park, which contains various buildings, vegetation, and man-made surfaces. Data were used from two separate airborne LiDAR systems, Optech Titan and Airborne Hydrography AB (AHAB) Chiroptera II. Classic standard point cloud analysis techniques were used with the discrete data. Waveform data were analyzed following a gridding or rasterization process to enable visualization and processing. Analysis approaches used were ENVI classification tools such as Support Vector Machines (SVM), Spectral Angle Mapper (SAM), Maximum Likelihood, and K-means to classify returns. Through the use of this analog to hyperspectral data analysis to classify vegetation and terrain, the results are that, by using the Support Vector Machines with full waveform data, we can successfully improve low vegetation classifiers by 40%, and differentiate tree types (Pine/Cypress) at 40–60% accuracy.en_US
dc.description.urihttp://archive.org/details/forestryidentifi1094559646
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleFORESTRY IDENTIFICATION WITH LIDAR WAVEFORM AND POINT CLOUDSen_US
dc.typeThesisen_US
dc.contributor.departmentSpace Systems Academic Group (SP)
dc.subject.authorLiDARen_US
dc.subject.authorfull waveform LiDARen_US
dc.subject.authorremote sensingen_US
dc.subject.authorterrain classificationen_US
dc.subject.authorlaser altimetryen_US
dc.subject.authorSupport Vector Machinesen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Space Systems Operationsen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineSpace Systems Operationsen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.identifier.thesisid29758


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