Deriving Tidal Flat Topography Using ICESat‐2 Laser Altimetry and Sentinel‐2 Imagery

Abstract

Acquiring accurate and timely datasets on tidal flat topography is fundamental for studies, management, and policy‐making in coastal zones. In this study, we report a fusion method of freely accessed and global‐scale Sentinel‐2 (imagery) and Ice,Cloud, and Land Elevation Satellite‐2 (ICESat‐2) (laser altimetry) datasets for deriving tidal flat topography. The basic idea is to construct a model on characterizing the specific relationship between the elevations of the tidal flat (from ICESat‐2 data) and corresponding inundation frequencies (from Sentinel‐2 time‐series). The proposed method was validated for the largest tidal flat on the Chinese continental shelf with a root mean square error of 0.23 m. We highlight that this method solely relies on satellite data and does not require any in‐situ data because ICESat‐2 provides dense and accurate along‐track points as valuable prior elevation information, which enhance the ability to obtain tidal flat topography in many coastal regions even in the absence of local in‐situ data.

Geomorphological Evolution in the Tidal Flat of a Macro-Tidal Muddy Estuary, Hangzhou Bay, China, over the Past 30 Years

“…Tidal flat bathymetry is a key parameter for coastal disaster management. Obtaining accurate bathymetry has received continuous attention [6][7][8]. Field observation is conducted to obtain the bathymetry data using a 3D (three-dimensional) terrain laser scanner or unmanned aerial vehicle scanning during spring low slack water when the tidal flat is non-submerged.…”

“…Field observation is conducted to obtain the bathymetry data using a 3D (three-dimensional) terrain laser scanner or unmanned aerial vehicle scanning during spring low slack water when the tidal flat is non-submerged. In recent years, the calculation of shallow water Sentinel-2 bathymetry based on remote sensing data has been developed using ICESat-2 Photon-Counting Lidar combined with classical wave theory [9], or ICESat-2 Laser Altimetry combined with Sentinel-2 Imagery [8]. Hsu et al [7] provided a semi-empirical scheme for bathymetric mapping in shallow water using ICESat-2 and Sentinel-2.…”

“…However, detailed information on tidal flats and their annual variations is largely unknown [34][35][36]. Rapidly measuring the detailed topography of tidal flats is important for coastal management and safety, and clearly knowing the evolution of tidal flats supports the planning of coastal zones [8]. This study uses the southern tidal flat in the HZB as an example to investigate the characteristics of tidal flat geomorphology (area, altimetry, and tidal creek) using field data and remote sensing data.…”

Estimating coastal slope of sandy beach from ICESat-2: a case study in Texas

“…Exceeding 40% of the global population lives in areas within 200 km to the coastline (Jouffray et al 2020), and 70% of the industrial capital is located within the coastal zone 100 km from the coastline (Zong et al 2021). Under the double pressure of climate change driven sea level rise and disturbance of human activities, accurate geographical information is urgently required for sustainable management in coastal zones (He and Silliman 2019, Kulp and Strauss 2019, Xu et al 2022a.…”

A Low-Cost Approach for Lake Volume Estimation on the Tibetan Plateau: Coupling the Lake Hypsometric Curve and Bottom Elevation

“…To overcome the disadvantage of the traditional survey, some researchers attempted to derive the bathymetric map using remote sensing technologies (Getirana et al, 2018;Li et al, 2019bLi et al, , 2020. Both the optical images and satellite altimetry were used to derive the underwater topography of inland or coastal waterbodies (Armon et al, 2020;Xu et al, 2022), yet being restricted in deep or turbid water conditions (Saylam et al, 2017;Bandini et al, 2018). Some spatial prediction and modeling methods were gradually proposed to overcome such difficulties mentioned above by predicting underwater bathymetry using exposed lake-surrounding terrains (Hollister et al, 2011;Heathcote et al, 2015;Cael et al, 2017;Getirana et al, 2018).…”