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Performance evaluation of three DEM‐based fluvial terrace mapping methods
Author(s) -
Hopkins Austin J,
Snyder Noah P
Publication year - 2016
Publication title -
earth surface processes and landforms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 127
eISSN - 1096-9837
pISSN - 0197-9337
DOI - 10.1002/esp.3922
Subject(s) - terrace (agriculture) , digital elevation model , watershed , geology , river terraces , fluvial , lidar , remote sensing , geomorphology , hydrology (agriculture) , geography , structural basin , archaeology , computer science , geotechnical engineering , machine learning
The availability of high‐resolution digital elevation models (DEMs) derived from airborne light detection and ranging (LiDAR) surveys has spurred the development of several methods to identify and map fluvial terraces. The post‐glacial landscape of the Sheepscot River watershed, Maine, where land‐use change has produced fill terraces upstream of historic dam sites, was selected to implement a comparison between terrace mapping methodologies. At four study sites within the watershed, terraces were manually mapped on LiDAR‐DEM‐derived hillshade images to facilitate the comparison among fully and semi‐automated DEM‐based procedures, including: (1) spatial relationships between interpreted terraces and surrounding natural topography, (2) feature classification algorithms, and (3) the TerEx terrace mapping toolbox. Each method was evaluated based on its accuracy and ease of implementation. The four study sites have varying longitudinal slope (0.0008–0.006 m/m), channel width (< 5–30 m), surrounding landscape relief (20–80 m), type and density of surrounding land use, and mapped surficial geologic units. All methods generally overestimate terrace areas (average predicted area 210% of manually defined area) with the most accurate results achieved within confined river valleys surrounded by the steep hillslopes. Accuracy generally decreases for study sites surrounded by low‐relief landscapes (predicted areas ranged 4–953% of manual delineations). We conclude with the advantages and drawbacks of each method tested and make recommendations for the scenarios where the use of each method is most appropriate. Copyright © 2016 John Wiley & Sons, Ltd.