Stream Network Delineation from High-Resolution Digital Elevation Models.

dc.contributor.advisorHelena Mitasova, Committee Memberen_US
dc.contributor.advisorJames D. Gregory, Committee Chairen_US
dc.contributor.advisorStacy A. C. Nelson, Committee Co-Chairen_US
dc.contributor.advisorMontserrat Fuentes, Committee Memberen_US
dc.contributor.authorColson, Thomas Paytonen_US
dc.date.accessioned2010-04-02T18:53:53Z
dc.date.available2010-04-02T18:53:53Z
dc.date.issued2006-12-08en_US
dc.degree.disciplineForestryen_US
dc.degree.leveldissertationen_US
dc.degree.namePhDen_US
dc.description.abstractEffective environmental management requires an accurate inventory of the resources to be managed. Decision makers often lack the technical expertise necessary to understand the limitations of environmental data. The State of North Carolina is re-surveying elevations using Light Detection and Ranging to re-delineate floodplains. These data allow analysts to predict flood inundation extents of design storms in order to better manage flood-prone terrain. Conversely, many environmental management functions in North Carolina, such as calculating stream length for hydrologic modeling and riparian buffer protection, rely upon outdated paper maps such as the USGS topographic map series for the determination of the location of stream "blue lines". These cartographic products are inadequate for use in headwater stream mapping when compared to field observations yet no better data source has been found to achieve the accuracy needed for local site planning. This research evaluated the horizontal accuracy and completeness of currently available stream maps compared to stream networks derived from DEMs obtained from the USGS, the North Carolina Floodplain Mapping Program, and interpolated from LiDAR bare-earth elevation points. A unique system combining software and hardware was developed to map headwater catchments with global positioning systems and was used to perform field data collection at nine catchments distributed across four physiographic regions. A method of determining the horizontal accuracy of stream lines shown on maps was developed and used to show that stream networks delineated using high-resolution, interpolated DEMs are more accurately positioned than those on previously published maps or stream networks delineated from currently available DEMs.en_US
dc.identifier.otheretd-10302006-122024en_US
dc.identifier.urihttp://www.lib.ncsu.edu/resolver/1840.16/4432
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectterrain analysisen_US
dc.subjectheadwater streamsen_US
dc.subjectstream mappingen_US
dc.subjectdigital elevation modelen_US
dc.titleStream Network Delineation from High-Resolution Digital Elevation Models.en_US

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