融合面向对象与缨帽变换的湿地覆被类别遥感提取方法

被引:21
作者
罗开盛 [1 ,2 ]
陶福禄 [1 ]
机构
[1] 中国科学院地理科学与资源研究所陆地表层格局与模拟院重点实验室
[2] 中国科学院大学
关键词
遥感; 分类; 湿地; 面向对象; HJ-CCD影像; 缨帽变换;
D O I
暂无
中图分类号
P237 [测绘遥感技术];
学科分类号
1404 ;
摘要
为了有效提取湿地覆被类别遥感信息,该文基于国产环境星影像(HJ-CCD)和Landsat7遥感影像(ETM)提出了一种融合面向对象技术和缨帽变换的提取湿地覆被信息的方法,并对东洞庭湖区的湿地进行提取。遥感提取结果的总体精度90.02%,Kappa系数0.88,高于传统的分类方法分类的量化结果;获得的结果没有"椒盐现象"且比较紧致。试验结果表明融合面向对象和缨帽变换的方法能够有效的提取湿地覆被类别,精度高,效果好。研究结果为有效地利用遥感手段提取湿地覆被信息提供参考。
引用
收藏
页码:198 / 203
页数:6
相关论文
共 20 条
[1]  
Evaluation of a rule-based compositing technique for Landsat-5 TM and Landsat-7 ETM+ images.[J].W. Lück;A. van Niekerk.International Journal of Applied Earth Observatio.2016,
[2]  
Global coastal wetland change under sea-level rise and related stresses: The DIVA Wetland Change Model.[J].Thomas Spencer;Mark Schuerch;Robert J. Nicholls;Jochen Hinkel;Daniel Lincke;A.T. Vafeidis;Ruth Reef;Loraine McFadden;Sally Brown.Global and Planetary Change.2016,
[3]  
Object-oriented semantic labelling of spectral–spatial LiDAR point cloud for urban land cover classification and buildings detection.[J].Anandakumar M. Ramiya;Rama Rao Nidamanuri;Ramakrishnan Krishnan.Geocarto International.2016, 2
[4]   Predicting climate change effects on wetland ecosystem services using species distribution modeling and plant functional traits [J].
Helen Moor ;
Kristoffer Hylander ;
Jon Norberg .
AMBIO, 2015, 44 :113-126
[5]  
Multi-temporal Sub-pixel Landsat ETM+ Classification of Isolated Wetlands in Cuyahoga County; Ohio; USA.[J].Robert C. Frohn;Ellen D’Amico;Charles Lane;Brad Autrey;Justicia Rhodus;Hongxing Liu.Wetlands: The Journal of the Society of Wetland Scientists.2012, 2
[6]  
Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing.[J].R.J. Zomer;A. Trabucco;S.L. Ustin.Journal of Environmental Management.2008, 7
[7]  
Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data.[J].Charlotte MacAlister;Manithaphone Mahaxay.Journal of Environmental Management.2008, 7
[8]  
Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data.[J].Chris Wright;Alisa Gallant.Remote Sensing of Environment.2006, 4
[9]  
遥感应用分析原理与方法.[M].赵英时等编著;.科学出版社.2003,
[10]   基于HJ-CCD数据和决策树法的干旱半干旱灌区土地利用分类 [J].
于文婧 ;
刘晓娜 ;
孙丹峰 ;
姜宛贝 ;
曲葳 .
农业工程学报, 2016, 32 (02) :212-219