Skip to main content
U.S. flag

An official website of the United States government

The development of a GIS methodology to identify oxbows and former stream meanders from LiDAR-derived digital elevation models

December 21, 2018

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.

Citation Information

Publication Year 2019
Title The development of a GIS methodology to identify oxbows and former stream meanders from LiDAR-derived digital elevation models
DOI 10.3390/rs11010012
Authors Courtney L. Zambory, Harvest Ellis, Clay Pierce, Kevin J. Roe, Michael J. Weber, Keith E. Schilling, Nathan C. Young
Publication Type Article
Publication Subtype Journal Article
Series Title Remote Sensing
Series Number
Index ID 70227885
Record Source USGS Publications Warehouse
USGS Organization Coop Res Unit Leetown

Related Content