西沙群岛精细植被分布的遥感制图及动态变化  

Mapping and dynamic changes of refined vegetation distribution in Xisha Islands

作　　者：孙晓慧 史建康[3] 李新武 吴文瑾 梁雷 宫晨 无 SUN Xiaohui;SHI Jiankang;LI Xinwu;WU Wenjin;LIANG Lei;GONG Chen;无(Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China;Ecological Environment Monitoring Center,Hainan Provincial,Haikou 571126,China;Hainan Institute,Institute of Aerospace Information Research,Chinese Academy of Sciences,Sanya 572029,China;Key Laboratory of Earth Observation,Hainan Province,Sanya 572029,China)

机构地区：[1]中国科学院空天信息创新研究院,北京100094 [2]中国科学院大学,北京100049 [3]海南省环境科学研究院,海口570026 [4]中国科学院空天信息创新研究院海南研究院,三亚572029 [5]海南省地球观测重点实验室,三亚572029

出　　处：《遥感学报》2021年第7期1473-1488,共16页NATIONAL REMOTE SENSING BULLETIN

基　　金：海南省重点研发计划(编号:ZDYF2018171);海南省重点研发计划(编号:ZDYF2019005);中国科学院国际合作局对外合作重点项目(编号:131X11KYSB20160061)。

摘　　要：西沙群岛是南海群岛中岛屿最多、面积最大的群岛,自然环境独特、植物区系特殊、岛上植被一直都是植物学家及地理学家重点关注的问题。本文基于光谱分类,于决策层融合支持向量机与光谱信息散度两类分类器进行西沙群岛典型岛屿植被类型识别,形成典型植被分布图。建立西沙群岛典型植被光谱库,分析西沙群岛典型植被实测光谱与其一阶导数的特性,并基于典型岛屿不同时期的植被分布图进行变化分析。结果表明:(1)采用光谱分类的生产精度及用户精度在西沙群岛主要岛屿的平均值为83.49%、85.54%,Kappa系数为0.8728。(2)2002年—2018年,各典型岛屿主要受到人类活动影响,整体上植被种类及植被面积增加,草海桐形成单优植被群落。(3)经相关性分析,各典型岛屿植被种类数量与本岛面积基本成正相关关系,且面积越大,植被种类随时间增加速度越快;相邻岛屿之间的距离与两岛植被相似性呈正相关,两岛距离越近,植被种类相似性越高。The Paracel Islands is the largest island with the largest number of islands in the South China Sea Islands.They have a unique natural environment and particular natural flora.The vegetation on the islands has always been a key concern of botanists and geographers.In order to quickly obtain the continuous distribution and long-term dynamic changes of vegetation in a large area of the island,the study integrated multi-source high resolution remote sensing data and measured GPS sampling data,spectral data and other auxiliary information.The vegetation types of typical islands in Paracel Islands were identified based on spectral classification,which fusing Support Vector Machine(SVM)and Spectral Information Divergence(SID)two classifiers on decision-making level and generating the typical vegetation distribution maps.A typical vegetation spectrum library of the Paracel Islands was also established using to analyze the characteristics of the measured spectrum and its first derivative of the typical vegetation in the Paracel Islands,enriching the basic information of vegetation in Paracel Islands.The study compared the classification method of SVM+SID and the general Spectral Angle Mapper(SAM)method,then further obtained the accuracy assessment results of each island.Based on the vegetation distribution maps of typical islands in different periods after the accuracy assessment,the statistical change of the area occupied by each vegetation and the correlation analysis of the vegetation diversity of different islands were conducted.The results demonstrating that:(1)The average production accuracy and user accuracy of the spectral classification method(combining SVM and SID classifiers on decision-making level)were 83.49%and 85.54%and Kappa coefficient was 0.8728 of the most whole islands in Paracel Islands.Therefore,the study achieved good performances in identifying different vegetation types on typical islands.(2)From 2002 to 2018,the vegetation types and its areas increased and tended to be stable.Scaevola was prone

关 键 词：西沙群岛 光谱分类 植被识别与变化 草海桐 植被种类数量 

分 类 号：Q948[生物学—植物学] TP751[自动化与计算机技术—检测技术与自动化装置]