基于Sentinel-2影像多特征组合的红树林分布信息提取研究  

Study on the Extraction of Mangrove Distribution Information Based on Multi-Feature Combination of Sentinel-2 Images

作　　者：孙玉超 董迪[1,2] 高晴 艾彬 SUN Yuchao;DONG Di;GAO Qing;AI Bin(Technology Innovation Center for South China Sea Remote Sensing,Surveying and Mapping Collaborative Application,Ministry of Natural Resources,Guangzhou 510300,China;South China Sea Institute of Planning and Environmental Research,State Oceanic Administration,Guangzhou 510300,China;School of Marine Sciences,Sun Yat-sen University,Zhuhai 519082,China)

机构地区：[1]自然资源部南海遥感测绘协同应用技术创新中心,广东广州510300 [2]国家海洋局南海规划与环境研究院,广东广州510300 [3]中山大学海洋科学学院,广东珠海519082

出　　处：《海洋技术学报》2025年第1期21-32,共12页Journal of Ocean Technology

基　　金：自然资源部南海局科技发展基金资助项目(230103);国家自然科学基金面上项目(42071261)。

摘　　要：本文以广西北仑河口国家级自然保护区核心区——珍珠湾范围内的红树林为例,通过提取Sentinel-2影像的水体指数、植被指数、红边特征、纹理特征和空间邻域特征,以及先进星载热发射和反射辐射仪全球数字高程模型(Advanced Spaceborne Thermal Emission and Reflec-tion Radiometer Global Digital Elevation Model,ASTER GDEM)数据的地形特征,分别采用特征相关性分析及特征重要性排序进行多特征组合初选和优选,最后采用面向对象的支持向量机分类方法进行红树林分布信息提取和分析。实验结果表明:Sentinel-2影像原始波段进行红树林分布信息提取生产者精度较高,但用户精度比较低;增加红边特征、纹理特征、空间邻域特征及地形特征后,用户精度均有明显提升;通过对各类型特征做相关性分析,可以在减少数据冗余的同时提升红树林分布信息提取精度,而通过对各类型特征做重要性排序,可以定量分析各类型特征对红树林分布信息提取的贡献,更大程度上减少数据冗余的同时达到更好的红树林提取结果。本文研究成果对使用Sentinel-2影像多特征开展红树林分布信息提取具有参考意义。This study takes the mangrove forests within the Pearl Bay area of the Beilun River Estuary National Nature Reserve in Guangxi as an example.It utilizes Sentinel-2 imagery to extract water indices,vegetation indices,red-edge features,texture features,and spatial neighborhood features,in addition to topographic features derived from ASTER GDEM data.The study employs feature correlation analysis for initial multi-feature combination selection,followed by feature importance ranking for optimized multi-feature combination selection.Finally,an object-oriented Support Vector Machine classification method is utilized to extract mangrove distribution information.The experimental results indicate that the use of original bands from Sentinel-2 imagery yields high producer爷s accuracy for mangrove distribution information extraction,but relatively low user爷s accuracy.However,after incorporating red-edge features,texture features,spatial neigh-borhood features,and topographic features,there is a significant improvement in user爷s accuracy.By conducting correlation analysis on various types of features,data redundancy can be reduced while simultaneously enhancing the accuracy of mangrove extraction.Furthermore,by ranking the importance of different types of features,we can quantitatively analyze the contribution of each type to mangrove extraction.This allows for the selection of more accurate feature combinations,leading to better mangrove extraction results with reduced data redundancy.The findings of this research are of significant reference value for the use of Sentinel-2 imagery and multiple features in mangrove extraction.

关 键 词：红树林 Sentinel-2 支持向量机 特征优选 特征组合 

分 类 号：P237[天文地球—摄影测量与遥感]