测绘通报 ›› 2022, Vol. 0 ›› Issue (9): 63-67.doi: 10.13474/j.cnki.11-2246.2022.0265

• 学术研究 • 上一篇    下一篇

面向对象的三亚珊瑚礁底质信息提取

吴虹蓉1,2, 朱岚巍1,3, 施冬2   

  1. 1. 海南空天信息研究院海南省地球观测重点实验室, 海南 三亚 572029;
    2. 长江大学地球科学学院, 湖北 武汉 430000;
    3. 中国科学院空天信息创新研究院数字地球重点实验室, 北京 100094
  • 收稿日期:2022-05-17 发布日期:2022-09-30
  • 通讯作者: 朱岚巍。E-mail:zhulw@aircas.ac.cn
  • 作者简介:吴虹蓉(1996—),女,硕士生,研究方向为珊瑚礁遥感监测。E-mail:hrwsxll@163.com
  • 基金资助:
    海南省重点研发计划(ZDYF2020030);海南省重大科技计划(ZDKJ2019006);广东省海洋遥感重点实验室开放课题(2017B030301005-LORS1904)

Object-oriented extraction of Sanya coral reef sediment information

WU Hongrong1,2, ZHU Lanwei1,3, SHI Dong2   

  1. 1. Hainan Key Laboratory of Earth Observation, Hainan Aerospace Information Research Institute, Sanya 572029, China;
    2. School of Earth Sciences, Yangtze University, Wuhan 430000, China;
    3. Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
  • Received:2022-05-17 Published:2022-09-30

摘要: 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。

关键词: 珊瑚礁, 面向对象, 分类体系, 遥感影像, 精度评估

Abstract: 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-2A 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.

Key words: coral reef, object orientation, classification system, remote sensing images, accuracy evaluation

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