Spatial-temporal variability: characterisation of a beach system using high resolution radar data

Frontiers in Marine Science

Marine Science

James Murphy¹  Daniel Arribas-Bel¹  Cai Bird²  Andy Plater³ 

[1] Geographic Data Science Lab, University of Liverpool, Liverpool, United Kingdom;R&D Department, CoastSense Ltd., Queens Dock Business Centre, Liverpool, United Kingdom;School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom;

关键词: beach characterization;    radar;    remote sensing;    spatio - temporal analysis;    beach variability;    machine learning;   

DOI  :  10.3389/fmars.2023.1142077

 received in 2023-01-11, accepted in 2023-07-05,  发布年份 2023

来源: Frontiers

【 摘 要 】

Intertidal areas experience a series of complex dynamic processes that affect beach morphology. Many of these processes are difficult to monitor, particularly due to the limited availability of high-resolution data. This study utilises high resolution radar-derived DEMs obtained through the temporal waterline method high resolution to perform a spatio-temporal analysis of beach morphology over the macrotidal nearshore of Rossall Beach, UK. Beach elevation changes are characterized, providing new insights into the morphological processes from fortnightly to seasonal time scales. The results of this analysis draw focus to the short-term variations in beach morphology and their contributions to long-term change. Observation of spatio-temporal variation displayed an intertidal system in a seasonal steady state equilibrium, somewhat dominated by elevation changes within the spring and summer months. Furthermore, the upper-intertidal zone displays evidence of continuing accretion. Though the analysis within this study is mostly explorative, it shows the potential of radar data for autonomous monitoring and spatio-temporal characterization of the coast. This enables coastal managers and stakeholders to build a long-term picture of the coastline, reducing vulnerability to coastal hazards and building resilience.

【 授权许可】

Unknown   
Copyright © 2023 Murphy, Plater, Bird and Arribas-Bel