TY - JOUR

T1 - Mapping three-dimensional morphological characteristics of tidal salt-marsh channels using UAV structure-from-motion photogrammetry

AU - Chen, Chunpeng

AU - Zhang, Ce

AU - Schwarz, Christian

AU - Tian, Bo

AU - Jiang, Wenhao

AU - Wu, Wenting

AU - Garg, Rahul

AU - Garg, Pradeep

AU - Aleksandr, Chusov

AU - Mikhail, Shilin

AU - Zhou, Yunxuan

N1 - This is the author’s version of a work that was accepted for publication in Geomorphology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Geomorphology, 407, 2022 DOI: 10.1016/j.geomorph.2022.108235

PY - 2022/6/15

Y1 - 2022/6/15

N2 - Tidal channels (TCs) are geomorphological features of coastal and tidal landscapes. They provide a pathway for the exchange of material and energy between marshes and adjacent water bodies and thereby control the hydrodynamic, morphological, and ecological processes on marsh platforms. Due to difficulties in terms of accessibility, limitations on the duration of exposure during low-water stages, and variations in morphology over time, rapid and accurate mapping of such intertidal morphological features at a high frequency is extremely challenging. Here, we present an efficient method integrated unmanned aerial vehicles (UAVs) structure-from-motion (SfM) photogrammetry, and spatial morphological fitting and delineation for accurately quantifying channel three-dimensional (3D) morphological features in terms width, depth, width-to-depth ratio, and cross-sectional area. We also relate these measured proxies to salt marsh species distributions. A two-step thresholding approach combining elevation and slope is developed in order to determinate TC boundaries from salt marsh and tidal flat area, and a Gaussian fit is used to estimate water-bearing channel depth and cross-sectional area. Salt marsh species are identified from fine-resolution multispectral satellite data and a field training dataset using a Random Forest classifier. Our results indicate that (1) UAV-based SfM photogrammetry can achieve centimeter-level accuracy in mapping the topography of TCs, with a root mean square error (RMSE) of 5.7 cm — mainly from the strong reflection of light from smooth TC water surfaces and the presence of water-bearing layers; (2) the morphological features of TCs, ranging from tidal flats to salt marsh areas, demonstrate a similar tendency, which increases at first and then decreases. The maximum depth and cross-sectional area of TCs is in sparse salt-marsh area, up to 4 m and 150 m2, respectively; and (3) TC morphology has a major impact on the distribution of salt marsh plants and such effects vary across different plant species. These results greatly contribute deep understanding of feedbacks between TCs and salt marsh plant species distribution and have significant implications for developing ecological and morphological salt marsh restoration guidelines.

AB - Tidal channels (TCs) are geomorphological features of coastal and tidal landscapes. They provide a pathway for the exchange of material and energy between marshes and adjacent water bodies and thereby control the hydrodynamic, morphological, and ecological processes on marsh platforms. Due to difficulties in terms of accessibility, limitations on the duration of exposure during low-water stages, and variations in morphology over time, rapid and accurate mapping of such intertidal morphological features at a high frequency is extremely challenging. Here, we present an efficient method integrated unmanned aerial vehicles (UAVs) structure-from-motion (SfM) photogrammetry, and spatial morphological fitting and delineation for accurately quantifying channel three-dimensional (3D) morphological features in terms width, depth, width-to-depth ratio, and cross-sectional area. We also relate these measured proxies to salt marsh species distributions. A two-step thresholding approach combining elevation and slope is developed in order to determinate TC boundaries from salt marsh and tidal flat area, and a Gaussian fit is used to estimate water-bearing channel depth and cross-sectional area. Salt marsh species are identified from fine-resolution multispectral satellite data and a field training dataset using a Random Forest classifier. Our results indicate that (1) UAV-based SfM photogrammetry can achieve centimeter-level accuracy in mapping the topography of TCs, with a root mean square error (RMSE) of 5.7 cm — mainly from the strong reflection of light from smooth TC water surfaces and the presence of water-bearing layers; (2) the morphological features of TCs, ranging from tidal flats to salt marsh areas, demonstrate a similar tendency, which increases at first and then decreases. The maximum depth and cross-sectional area of TCs is in sparse salt-marsh area, up to 4 m and 150 m2, respectively; and (3) TC morphology has a major impact on the distribution of salt marsh plants and such effects vary across different plant species. These results greatly contribute deep understanding of feedbacks between TCs and salt marsh plant species distribution and have significant implications for developing ecological and morphological salt marsh restoration guidelines.

KW - Structure-from-motion (SfM) photogrammetry

KW - Tidal channels

KW - Morphological features

KW - Salt marsh

KW - Unmanned aerial vehicles (UAVs)

U2 - 10.1016/j.geomorph.2022.108235

DO - 10.1016/j.geomorph.2022.108235

M3 - Journal article

VL - 407

SP - 1

EP - 13

JO - Geomorphology

JF - Geomorphology

SN - 0169-555X

M1 - 108235

ER -