红外与毫米波学报2025，Vol.44Issue(2)：203-210,8.DOI:10.11972/j.issn.1001-9014.2025.02.008
基于时序Sentinel-2影像和近红外潮滩指数的海岸带潮滩提取方法
Tidal flats extraction in the coastal zone based on time-series Sentinel-2 imagery and near-infrared tidal flats indices
摘要
Abstract
When extracting coastal zone tidal flats using remote sensing transient images,the influence of tides greatly limits the accuracy of tidal flat spatial distribution extraction.With the purpose of weakening the influence of tides,a method of extracting coastal zone tidal flats by combining time-series Sentinel-2 images and tidal flat index was pro-posed.First,based on the Sentinel-2 time-series image data,we used the quantize synthesis method to generate high-and low-tide images,and then analyzed the spectral reluctance characteristics of different land classes on the high-and low-tide images.ANIR-band tidal flat extraction index that excludes the interference of the tidal transient was construct-ed.Secondly,the image spectral information and the tidal flat extraction index were input into a machine learning algo-rithm to realize fast and efficient extraction of the tidal flat.In addition,the study discussed the separability of the tidal flats index and the generalizability of the methodology.The results show that the tidal flat's extraction index constructed in this research had a good separability for tidal flats,the overall accuracy of tidal flats extraction was 93.02％,the Kap-pa coefficient was 0.86,and the proposed method had good applicability to remote sensing images containing near-in-frared bands.This method can realize automatic and rapid tidal flat extraction,and provide data support for the sustain-able management and protection of coastal zone resources.关键词
湿地遥感/海岸带潮滩指数/定量分析法/近红外波段/Sentinel-2影像Key words
wetland remote sensing/coastal zone tidal flats index/quantitative analysis method/near-infrared band/Sentinel-2 imagery分类
测绘与仪器引用本文复制引用
周汝佳,夏清,郑琼,朱丽红,李建华,李斌,宋佳..基于时序Sentinel-2影像和近红外潮滩指数的海岸带潮滩提取方法[J].红外与毫米波学报,2025,44(2):203-210,8.基金项目
国家自然科学基金(42101356) （42101356）
长沙理工大学公路地质灾变预警空间信息技术湖南省工程实验室开放基金资助项目(KFJ210601) （KFJ210601）
湖南省教育厅科学研究项目(23B0327) （23B0327）
湖南省教育厅优秀青年项目(24B0331)Supported by the National Natural Science Foundation of China(42101356),Open Fund of Engineering Laboratory of Spatial In-formation Technology of Highway Geological Disaster Early Warning in Hunan Province(Changsha University of Science&Technology)(KFJ210601),the Scientific Research Foundation of Hunan Education Department(23B0327),the Youth Project of the Hunan Provincial Depart-ment of Education(24B0331) （24B0331）
