面向对象的三亚珊瑚礁底质信息提取

Object-oriented extraction of Sanya coral reef sediment information

珊瑚礁对于海洋生态环境研究具有重要意义,通过分析珊瑚礁底栖物质的分布及健康状况,可以对珊瑚礁生态环境进行评估。本文提出了一种基于面向对象的图像分类方法,通过试验确定不同地貌的最优分割尺度,其中陆地和深海的最优分割尺度为150,各类底栖物质的最优分割尺度为30。以Sentinel-2A卫星遥感影像为例,提取海南三亚珊瑚礁自然保护区的珊瑚礁底栖物质,并使用混淆矩阵对提取结果进行精度评估。结果表明,底栖物质提取总体分类精度为87.91%,Kappa系数为0.83。面向对象分类方法可有效结合珊瑚礁底栖物质的纹理特征和光谱特征,并充分利用遥感影像不同波段的组合特性,可为三亚珊瑚礁保护管理提供方法支撑。

Coral reefs are of great significance to the study of marine ecological environment.The ecological environment of coral reefs can be evaluated by analyzing the distribution and health status of benthic materials.In this paper,an object-based image classification method is used to determine the optimal segmentation scale of different landforms through experiments.Among them,the optimal segmentation scale of terrestrial and deep-sea is 150,and the optimal segmentation scale of various benthic substances is 30.Furthermore,Sentinel-2 A satellite remote sensing images are used to extract benthic materials from coral reefs in Sanya Coral Reef Nature Reserve,Hainan province,and confusion matrix is used to evaluate the accuracy of extraction results.The results show that the overall classification accuracy of benthic material extraction is 87.91%,and the Kappa coefficient is 0.83.The object-oriented classification method can effectively combine the texture characteristics and spectral characteristics of benthic material of coral reef and make full use of the combination characteristics of different bands of remote sensing image,and the extraction results can provide methodological support for reef protection and management in Sanya.