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Study on the Erosion and Deposition Changes of Tidal Flat in Jiangsu Province Using ICESat-2 and Sentinel-2 Data

Authors :
Kaizheng Wang
Huan Li
Nan Zhang
Jiabao Zhang
Xiaoyan Zhang
Zheng Gong
Source :
Remote Sensing, Vol 15, Iss 14, p 3598 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The ecological dynamics of tidal flats are subject to continuous transformations attributed to the interplay of the tidal erosion and sedimentation processes. Accordingly, the realization of a dynamic monitoring system for tidal flats holds significant importance in facilitating the judicious utilization and safeguarding of tidal flats resources. In this study, an integrated methodology was implemented to monitor and assess the tidal flats in Jiangsu province. Specifically, a collection of five multispectral images from the Sentinel-2 satellite was acquired, coupled with data derived from the ICESat-2 satellite. Through the application of advanced techniques, including convolutional neural networks and machine learning algorithms, a comprehensive combined model for inverting tidal flats topography was developed. The accuracy disparity between various model combinations was meticulously evaluated, thereby enabling the acquisition of detailed topography information encompassing the entirety of Jiangsuā€™s tidal flats for the year 2021. Comparative analysis against measured topographic data demonstrated that the overall accuracy of the combined model inversion surpassed 80%. Additionally, this study conducted an extensive investigation into the temporal evolution of tidal flats in Jiangsu by integrating data from 2008 to 2021, focusing particularly on the measured topography from 2008. Consequently, the study successfully delineated the various types of tidal flats present in Jiangsu and elucidated their corresponding evolutionary trends.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.83b49466cef3422aaefabadfe7874fde
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15143598