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时间:2020-03-26
《面向对象的高分辨率影像采煤塌陷地提取.pdf》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、ComputerEngineeringandApplications计算机工程与应用2011,47(23)239面向对象的高分辨率影像采煤塌陷地提取李晓霞“2,汪云甲“2LIXiaoxia“2,WANGYUniia“21.中国矿业大学环境与测绘学院,江苏徐州2210082.江苏省资源环境信息工程重点实验室,江苏徐州2210081.SchoolofEnvironmentScience&SpatialInformatics。ChinaUniversityofMiningandTechnology,Xuzhou,Jiangsu221008,China2.JiangsuK
2、eyLaboratoryofResourcesandEnvironmentalEngineering,Xuzhou,Jiangsu221008,ChinaLIXiaoxla。WANGYunjla.Coalminesubsidenceareaextractionfromhigh-resolutionremotesensingimagerybasedonobject-orientedclassificationmethod.ComputerEngineeringandApplications,2011.47(23):239-241.Abstract:Coalminea
3、ctivitieshavecausedaseriesofgeologicalandenvironmentalproblems,suchasgroundsurfacesubsid-ence,eta1.ComparedwithconventionalmonitoringtechniquesaslevelingandGPS,theremotesensingtechniquecandynami-callymonitortheminesubsidencewithwidercoverageandhigherefficiency.Theobject-orientedclassi
4、ficationmethod,whichcallmakeboreruseofthetextureandgeometryshapeinformationoftheremotesensingimagery,ismoreandmoreuti-lizedinhighresolutionimageclassification.Basedonthecharacteristicsofminesubsidencearea,howtorecognizetheminesubsidenceareafromremotesensingimageryisstudied,andtheautom
5、aticextractionrulesforobject-orientedclassificationmethodareproposed.ThePansanmineofHuainanMiningGroupinAnhuiprovince,China,isselectedasanexperimentalar-ea,theSPOT5imagesareusedtoextractminesubsidenceareawiththeproposedmethod,alloftheimagesareprocessedusingERDASIMAGINE9.2,ENVl4.7andEN
6、Vl4.4ZOOM.2.3226km2minesubsidenceareaareextracted,comparedwithfieldsurveydata,theresdtisveryconvincing.Keywords:object-oriented;high-resolutionremotesensingdata;subsidedland;informationex仃actionrules摘要:煤炭开采引起了塌陷等一系列的地质环境问题,与常规监测方法相比,遥感技术可以实现大范围、高效率、周期性的动态监测.在遥感影像分类方法中,面向对象的遥感影像分类方法能更好
7、地利用高分辨率遥感影像中丰富的纹理和几何结构信息。针对煤炭开采导致的地表塌陷地的特点,在归纳整理遥感影像中塌陷地判识准则的基础上,重点探讨了面向对象的遥感影像分类方法中塌陷地的自动提取规则.综合利用ERDASIMAGINE9.2、ENVl4.7和ENVl4.4ZOOM进行数据处理,以安徽省淮南矿务集团潘三矿区为实验区,用该方法利用SPOT5影像进行了塌陷地信息提取实验,结果证明,面向对象分类方法能有效地从高分辨率遥感影像中自动提取塌陷地相关信息。关键词:面向对象:高分辨率遥感数据;塌陷地;信息提取规则DOI:10.3778/j.issn.1002.8331.201
8、1.23.
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