| 注册
首页|期刊导航|广西科学|耦合SAM与地学知识的红树林-盐沼生态交错带无人机精细制图与碳储量估算

耦合SAM与地学知识的红树林-盐沼生态交错带无人机精细制图与碳储量估算

董迪 黄华梅 高晴 李小维 雷学铁 魏征 孙玉超 邹智垒 李亢

广西科学2026,Vol.33Issue(2):233-242,10.
广西科学2026,Vol.33Issue(2):233-242,10.DOI:10.13656/j.cnki.gxkx.20260603.003

耦合SAM与地学知识的红树林-盐沼生态交错带无人机精细制图与碳储量估算

Fine-scale Mapping of Unmanned Aerial Vehicle and Carbon Stock Estimation in Mangrove-Salt Marsh Ecotones by Coupling SAM and Geoscientific Knowledge

董迪 1黄华梅 2高晴 2李小维 3雷学铁 3魏征 2孙玉超 2邹智垒 2李亢2

作者信息

  • 1. 自然资源部海洋环境探测技术与应用重点实验室,广东 广州 510300||自然资源部南海发展研究院(自然资源部南海遥感技术应用中心),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. 自然资源部南海发展研究院(自然资源部南海遥感技术应用中心),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
  • 3. 自然资源部北海海洋中心,广西北海 536000
  • 折叠

摘要

Abstract

To address the challenges faced by conventional classification methods in balancing"salt and pepper noise"suppression and complex boundary extraction for fine-scale mapping of mangrove-salt marsh ecotones,this study proposes a mapping framework by coupling the Segment Anything Model(SAM)with geoscientif-ic knowledge.The Yifengxi Wetland Park in Shantou,Guangdong was selected as the study area.A multi-scale hierarchical constraint strategy was utilized.First,the object-oriented random forest classification was a-dopted to the resampled unmanned aerial vehicle Digital Orthophoto Map(DOM,2 m spatial resolution)to obtain a coastal vegetation mask,serving as a macro-scale geospatial background constraint.Subsequently,this mask was applied as a regional constraint for the SAM model to perform zero-shot segmentation on the resampled unmanned aerial vehicle DOM(20 cm spatial resolution),and fine-scale object patches were ex-tracted.Finally,spectral and textural features were coupled to achieve precise identification of mangroves and salt marshes.The results demonstrated that the proposed method achieved the Overall Accuracy(OA)of 98.67%and Kappa coefficient of 0.98,outperforming the conventional object-oriented random forest classifi-cation,and it showed a superior capability in delineating complex boundaries.Combination of the fine-scale mapping results and the InVEST model estimated the carbon stocks of mangroves ecosystem and salt mar-shes ecosystem in the study area as 14 953.53 and 923.58 Mg C,respectively.This study proves that the fine-scale mapping of unmanned aerial vehicle by coupling SAM and geoscientific knowledge provides reliable baseline data for the refined management of blue carbon ecosystems,offering significant application value.

关键词

红树林-盐沼生态交错带/SAM/蓝碳/精细制图/地学知识

Key words

mangrove-salt marsh ecotone/SAM/blue carbon/fine-scale mapping/geoscientific knowledge

分类

天文与地球科学

引用本文复制引用

董迪,黄华梅,高晴,李小维,雷学铁,魏征,孙玉超,邹智垒,李亢..耦合SAM与地学知识的红树林-盐沼生态交错带无人机精细制图与碳储量估算[J].广西科学,2026,33(2):233-242,10.

基金项目

自然资源部南海局科技发展基金项目(230206)和广东省林业局2025年度自然资源事务专项"广东省滨海湿地资源监测和生态价值评估"资助. (230206)

广西科学

1005-9164

访问量0
|
下载量0
段落导航相关论文