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遥感技术与应用  2018, Vol. 33 Issue (2): 360-369    DOI: 10.11873/j.issn.1004-0323.2018.2.0360
遥感应用     
基于资源三号影像的红树林物种分类研究
李想1,刘凯1,朱远辉1,蒙琳1,2,于晨曦3,曹晶晶1
(1.中山大学地理科学与规划学院 广东省城市化与地理环境空间模拟重点实验室 综合地理信息研究中心,广东 广州  510275;
2.广西师范学院国土资源与测绘学院,广西 南宁  530001;
3.中山大学环境科学与工程学院,广东 广州  510275)
Study on Mangrove Species Classification based on ZY-3 Image
Li Xiang1,Liu Kai1,Zhu Yuanhui1,Meng Lin1,2,Yu Chenxi3,Cao Jingjing1
(1.School of Geography and Planning,Sun Yat\|sen University,Guangdong Key Laboratory for Urbanization and Geo-Simulation,Center of Integrated Geographic Information Analysis,Guangzhou 510275,China;2.School of Land Resources and Surveying,Guangxi Teachers Education University,Nanning 530001,China;3.School of Environment Science and Engineering,Sun Yat\|sen University,Guangzhou 510275,China)
 全文: PDF(10830 KB)  
摘要:
选取北部湾的东部地区(广东省和广西壮族自治区交界处)为研究区,探索利用资源三号卫星影像,建立大范围红树林遥感信息提取和精细分类模式。首先根据地物波谱特征提取水陆边线,并建立缓冲区生成红树林生长适宜区;再通过基于面向对象的阈值分类方法提取红树林植被信息;最后采用基于像元的最近邻、贝叶斯和随机森林方法对红树林进行树种级分类。结果表明:采用结合阈值法的面向对象遥感分类可以对整景资源三号卫星影像准确提取水陆边线并有效提取红树林分布区,采用基于像元的随机森林法对红树林树种级分类可以得到较好的分类效果(总体分类精度82.84%),优于最近邻法和贝叶斯法。基于混合方法的红树林提取与树种分类模式适用于大范围的红树林分类与制图,同时也证实了资源三号卫星数据应用于海岸带红树林研究的有效性。
关键词: 资源三号红树林提取遥感分类北部湾    
Abstract: A hybrid mangrove forest extraction and species classification model for large coastal region was proposed using a ZY-3 (ZiYuan-3) image in the eastern part of Beibu Gulf (located at the junction of Guangdong and Guangxi).Firstly,the coastline was extracted according to the spectral features of ZY-3 image.Secondly,the buffer zone along with the coastline was generated as the suitable area of mangrove distribution.Mangrove forests and non-mangrove areas were then further classified using threshold method based on object-based image classification in these areas.Finally,Mangrove forests were classified at specie level using three pixel-based supervised classification methods,k-Nearest Neighbor,Bayes,and Random Forest.The classification results and accuracies were also compared and discussed.The results indicated that object-based threshold method can extract the coastline accurately and map the mangrove forests effectively.The pixel-based random forest classifier can obtain satisfactory results (the overall accuracy of 82.24%) of mangrove species classification than the other classifiers.In summary,the hybrid mode proposed in this paper is suitable for mangrove forests mapping and species classification in a large region.It is also validated the feasibility application of ZY-3 image in coastal mangrove research.
Key words: ZY-3    Mangrove extraction    Remote sensing classification    Beibu Gulf
收稿日期: 2017-04-06 出版日期: 2018-05-15
:  TP79  
基金资助: 广东省自然科学基金项目(2016A030313261),广州市科技计划项目(201510010081),国家自然科学基金项目(41001291)和广西高校科学技术研究项目(KY2015YB185)。
作者简介: 李想(1993-),女,江苏泰州人,硕士研究生,主要从事资源环境遥感研究。Email: lix57@mail2.sysu.edu.cn。
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引用本文:

李想,刘凯,朱远辉,蒙琳,于晨曦,曹晶晶. 基于资源三号影像的红树林物种分类研究[J]. 遥感技术与应用, 2018, 33(2): 360-369.

Li Xiang,Liu Kai,Zhu Yuanhui,Meng Lin,Yu Chenxi,Cao Jingjing. Study on Mangrove Species Classification based on ZY-3 Image. Remote Sensing Technology and Application, 2018, 33(2): 360-369.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2018.2.0360        http://www.rsta.ac.cn/CN/Y2018/V33/I2/360

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