Journal article
The Development of a GIS Methodology to Identify Oxbows and Former Stream Meanders from LiDAR-Derived Digital Elevation Models
Remote sensing (Basel, Switzerland), Vol.11(1), p.12
01/01/2019
DOI: 10.3390/rs11010012
Abstract
Anthropogenic development of floodplains and alteration to natural hydrological regimes have resulted in extensive loss of off-channel habitat. Interest has grown in restoring these habitats as an effective conservation strategy for numerous aquatic species. This study developed a process to reproducibly identify areas of former stream meanders to assist future off-channel restoration site selections. Three watersheds in Iowa and Minnesota where off-channel restorations are currently being conducted to aid the conservation of the Topeka Shiner (Notropis topeka) were selected as the study area. Floodplain depressions were identified with LiDAR-derived digital elevation models, and their morphologic and topographic characteristics were described. Classification tree models were developed to distinguish relic streams and oxbows from other landscape features. All models demonstrated a strong ability to distinguish between target and non-target features with area under the receiver operator curve (AUC) values 0.82 and correct classification rates 0.88. Solidity, concavity, and mean height above channel metrics were among the first splits in all trees. To compensate for the noise associated with the final model designation, features were ranked by their conditional probability. The results of this study will provide conservation managers with an improved process to identify candidate restoration sites.
Details
- Title: Subtitle
- The Development of a GIS Methodology to Identify Oxbows and Former Stream Meanders from LiDAR-Derived Digital Elevation Models
- Creators
- Courtney L. Zambory - Iowa State UniversityHarvest Ellis - Univ Iowa, Iowa Flood Ctr, Iowa City, IA 52242 USAClay L. Pierce - Iowa State UniversityKevin J. Roe - Iowa State UniversityMichael J. Weber - Iowa State UniversityKeith E. Schilling - Iowa Geol Survey, Iowa City, IA 52242 USANathan C. Young - Univ Iowa, Iowa Flood Ctr, Iowa City, IA 52242 USA
- Resource Type
- Journal article
- Publication Details
- Remote sensing (Basel, Switzerland), Vol.11(1), p.12
- DOI
- 10.3390/rs11010012
- ISSN
- 2072-4292
- eISSN
- 2072-4292
- Publisher
- Mdpi
- Number of pages
- 16
- Grant note
- F15AP01039 / U.S. Fish and Wildlife Service's State Wildlife Grant Competitive Program
- Language
- English
- Date published
- 01/01/2019
- Academic Unit
- Civil and Environmental Engineering; Earth and Environmental Sciences; IIHR--Hydroscience and Engineering
- Record Identifier
- 9984383297702771
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