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国土资源遥感  2016, Vol. 28 Issue (2): 182-187    DOI: 10.6046/gtzyyg.2016.02.28
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基于决策树方法的Landsat8 OLI影像红树林信息自动提取
张雪红
南京信息工程大学地理与遥感学院, 南京 210044
Decision tree algorithm of automatically extracting mangrove forests information from Landsat 8 OLI imagery
ZHANG Xuehong
School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China
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摘要 

基于广西山口国家红树林生态自然保护区的Landsat 8 OLI 影像数据,选用广泛应用于植被液态水含量反演的归一化差值湿度指数(normalized difference moisture index,NDMI)和修正的归一化差值池塘指数(modified normalized difference pond index,MNDPI)作为分类特征,运用决策树方法进行红树林信息的自动提取。研究结果表明: 红树林独特的滨海湿地生境特点,使其光谱同时包含植被和湿地信息; MNDPI和NDMI可分别反映可见光-近红外波段反射率同短波红外波段反射光谱的反差,可成功应用于湿地植被信息的提取,能有效地将红树林同其他地物相区分; 采用Landsat8 OLI遥感数据,并结合NDMI和MNDPI分类特征构建的决策树模型可有效地提取红树林信息,其错分率和漏分率都较低,分别为5.34%和1.69%。

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关键词 苹果叶片高光谱氮(N)素含量BP神经网络    
Abstract

NDMI (normalized difference moisture index) is widely used to assess and retrieve vegetation liquid water content. In this study, decision tree method was employed to automatically extract mangrove forests information combining the NDMI and MNDPI (modified normalized difference pond index), modified according to the mangrove characteristics, with Landsat8 OLI imagery acquired at Shankou mangrove national ecosystem nature reserve in Guangxi. The research results show that mangrove forests spectra consist of vegetation and wetland characteristics due to the unique near-shore coastal habitat of mangrove forests. MNDPI and NDMI can represent the spectral contrast between shortwave infrared region and visible region, near infrared region respectively. Therefore, the two spectral indices can successfully be employed to extract wetland vegetation and effectively discriminate mangrove forests from other land cover types. The decision tree method effectively extracted mangrove forests information by combining the classification features of MNDPI and NDMI and using Landsat8 OLI remotely sensed data. The commission error and omission error of mangrove forests were 5.34% and 1.69% respectively.

Key wordsapple leaf    hyperspectral    content of nitrogen(N)    back propagation(BP)neural network
收稿日期: 2014-11-12      出版日期: 2016-04-14
ZTFLH:  TP751.1  
  TP753  
基金资助:

国家自然科学基金项目"红树林冠层高光谱探测及群落类型识别研究"(编号: 41201461)和江苏政府留学奖学金共同资助。

作者简介: 张雪红(1980- ), 男,博士,副教授,主要从事植被生态遥感方面的研究。 Email: zxhbnu@126.com。
引用本文:   
张雪红. 基于决策树方法的Landsat8 OLI影像红树林信息自动提取[J]. 国土资源遥感, 2016, 28(2): 182-187.
ZHANG Xuehong. Decision tree algorithm of automatically extracting mangrove forests information from Landsat 8 OLI imagery. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 182-187.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2016.02.28      或      http://www.gtzyyg.com/CN/Y2016/V28/I2/182

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