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山区可见光-近红外遥感影像浓密植被暗像元自动识别方法研究
Alternative TitleAutomatic Detection of the DDV Pixels from VIS-NIR Images in Typical Mountainous Areas
赵志强1,2; 李爱农1; 边金虎1,2; 郭文静1,2; 刘倩楠1,2; 赵伟1,2; 黄成全3
Corresponding Author李爱农
2015
Source Publication遥感技术与应用
ISSN1004-0323
Volume30Issue:1Pages:58-67
Other Abstract 暗目标法是目前气溶胶光学厚度遥感反演中应用最为广泛的方法,浓密植被暗像元的识别是暗目标法的基础。针对可见光—近红外影像缺少中红外波段难以有效识别浓密植被暗像元的问题,引入红波段直方图阈值法识别山区可见光—近红外影像的浓密植被暗像元。该方法利用浓密森林像元在可见光波段反射率低的特点,通过搜索红波段直方图的最小峰值自动识别浓密植被暗像元。试验中选取Landsat TM影像前4个波段利用红波段直方图阈值法识别可见光—近红外影像的浓密植被暗像元,并与在中红外波段影像和可见光—近红外影像中广泛应用的两种暗像元识别方法进行对比分析,探讨红波段直方图阈值法的有效性,最后将该方法应用于环境减灾卫星(HJ-1)CCD影像的暗像元识别和气溶胶反演。实验结果表明:红波段直方图阈值法明显优于常用的可见光—近红外影像暗像元识别方法,识别精度接近传统的中红外波段影像识别方法,相似度指数小于2和小于3的暗像元分别为83.12%和93.48%。该方法为山区可见光—近红外影像浓密植被暗像元自动识别提供了一种新的适用方法,识别结果能够满足暗目标法反演气溶胶光学厚度的要求。 
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Dark Dense Vegetation(DDV)method is most widely used for retrieving the atmospheric aerosol optical thickness from remote sensing images in recent years,in which automatically detecting the dark dense vegetation pixels is the primary basis.However,it is quite difficult to detect DDV pixels for the visible and near-infrared(VIS-NIR)images without the mid-infrared band.A new method was named red band histogram threshold method that was proposed in this paper to automatically detect the DDV pixels from VIS-NIR images at typical mountainous areas.Using the low reflectance of forest pixels in visible bands, the method searched for the first peak of red band reflectance histogram,and detected the DDV pixels by threshold value defined by the first peak.Results of the proposed method were presented for omlyLandsat- 5Thematic Mapper(TM)imagery using only the first four bands.The performance of the method was compared with mid-infrared threshold method and multiple thresholds method,which were widely used in the imagery with mid-infrared band and VIS-NIR imagery respectively.Then the proposed method in this paper was applied to HJ satellite CCD imagery to detect DDV pixels and retrieve aerosol optical thickness. Results show that the proposed method evidently is better than the multiple threshilds method,and its accuracy is very close to the Mid-infrared threshold method.The proportion of DDV pixels whose similarity index is less than 2 and less than 3 were 83.12% and 93.48% respectively.It is a new robust method applicable for automatic detection of DDV pixels for VIS-NIR images at typical mountainous areas,and meets the need for the DDV method to retrieve aerosol optical thickness.

Keyword山区 浓密植被暗像元 红波段直方图阈值法 可见光—近红外影像 暗目标法
Subject AreaTp751
DOI:10.11873/j.issn.1004-0323.2015.1.0058
Indexed ByCSCD ; 北大中文核心
Language中文
CSCD IDCSCD:5399975
Funding Organization中国科学院和四川省“百人计划”项目 ; 国家自然科学基金项目(41271433) ; 中国科学院战略性先导科技专项(XDA05050105) ; 知识创新工程方向项目(KZCX2-YW-QN313)共同资助
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/17717
Collection数字山地与遥感应用中心
Affiliation1.中国科学院、水利部成都山地灾害与环境研究所
2.中国科学院大学
3.Department of Geography,University of Maryland,College Park,MD 20742,USA
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
赵志强,李爱农,边金虎,等. 山区可见光-近红外遥感影像浓密植被暗像元自动识别方法研究[J]. 遥感技术与应用,2015,30(1):58-67.
APA 赵志强.,李爱农.,边金虎.,郭文静.,刘倩楠.,...&黄成全.(2015).山区可见光-近红外遥感影像浓密植被暗像元自动识别方法研究.遥感技术与应用,30(1),58-67.
MLA 赵志强,et al."山区可见光-近红外遥感影像浓密植被暗像元自动识别方法研究".遥感技术与应用 30.1(2015):58-67.
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