基于边线的遥感影像道路震害快速提取方法研究
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摘要
重大地震灾害发生以后,快速准确地提取灾区的道路震害信息对于应急救援工作具有重要意义。由于地震造成的破坏非常复杂,没有固定的光谱特征变化模式,而且影像中存在大量同物异谱和同谱异物现象。因此,传统基于光谱特征的遥感影像道路震害提取方法,不仅提取精度较低,而且通用性不强,需要根据不同影像调整参数。道路边线是一种稳定的道路几何特征,其特征变化能够准确地表现道路的状态变化。基于此,本文研究了一种基于道路边线的震害信息快速提取方法。该方法利用震后遥感影像提取完好道路边线,与震前道路线分布数据进行变化检测,从而实现震害路段的提取。最后,利用汶川震区的遥感影像进行实例验证,与人工解译的结果进行比较。结果表明,该方法能够快速准确地提取道路震害信息。
Roads are the traffic lifeline for emergency rescue and disaster relief.After huge earthquakes,it is very important to rapidly extract road damages from remote sensing images for disaster emergency rescue.However,because damages caused by earthquakes is different at different places,it is very complicated to extract in a common way.Usually,spectral features are used to discriminate damaged and undamaged pixels or objects in images.Because thresholds have to be chosen by manual operation dependent on different situations,methods based on spectral features are low in accuracy and efficiency.This paper proposes an approach to rapidly extract road damages by earthquake based on sidelines.The approach extracts double sidelines of undamaged road from images acquired after earthquakes,and then compare them with vector road lines before earthquakes.The damaged segments of roads can be extracted through comparison.The performance of the method is evaluated by an experiment with QuickBird images in the disaster area of the 2008 Wenchuan earthquake.
Roads are the traffic lifeline for emergency rescue and disaster relief.After huge earthquakes,it is very important to rapidly extract road damages from remote sensing images for disaster emergency rescue.However,because damages caused by earthquakes is different at different places,it is very complicated to extract in a common way.Usually,spectral features are used to discriminate damaged and undamaged pixels or objects in images.Because thresholds have to be chosen by manual operation dependent on different situations,methods based on spectral features are low in accuracy and efficiency.This paper proposes an approach to rapidly extract road damages by earthquake based on sidelines.The approach extracts double sidelines of undamaged road from images acquired after earthquakes,and then compare them with vector road lines before earthquakes.The damaged segments of roads can be extracted through comparison.The performance of the method is evaluated by an experiment with QuickBird images in the disaster area of the 2008 Wenchuan earthquake.
引文
[1]陈世荣,马海建,范一大,等.基于高分辨率遥感影像的汶川地震道路损毁评估[J].遥感学报,2008,(6):949-955.
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[10]任玉环,刘亚岚,魏成阶,胡蕾秋.汶川地震道路震害高分辨率遥感信息提取方法探讨[J].遥感技术与应用,2009,(1):52-56+133-134.
[11]王艳萍,姜纪沂,林玲玲.高分辨率遥感影像中道路震害信息的识别方法[J].计算机工程与应用,2012,(3):173-175.
[12]Peer M,Bogdan G.Edge Detection with embedded confidence[J].IEEE Transactions on pattern a-nalysis and machine intelligence,2001,23(12):1351-1365.
[13]崔屹.图像处理与分析-数学形态学方法及应用[M].北京:科学出版社,2000.
[14]张永生,巩丹超,等.高分辨率遥感卫星应用--成像模型、处理算法及应用技术[M].北京:科学出版社,2004.
[2]马海建.面向灾害评估的高分辨率遥感影像道路损毁检测研究[D].北京大学,2009.
[3]Chini M,Pierdicca N,Emery W J.Exploiting SAR and VHR optical images to quantify damagecaused by the 2003Bam Earthquake[J].IEEE Transactions on Geoscience and Remote Sensing,2009,47(1):145-152.
[4]张景发,谢礼立,陶夏新.建筑物震害遥感图像的变化检测与震害评估[J].自然灾害学报,2002,11(2):59-64.
[5]Gong JianYa,Sui HaiGang,Sun KaiMin,et al.Object-level change detection based on full-scale im-age segmentation and its application to Wenchuan Earthquake[J].Science in China Series E:Tech-nological Sciences,2008,51(II):110-122.
[6]Pesaresi M,Gerhardinger A,HAAG F.Rapid damage assessment of built-up structures using VHRsatellite data in tsunami-affected areas[J].International Journal of Remote Sensing,2007,28:13-14.
[7]柳稼航,杨建峰,魏成阶,等.震害信息遥感获取技术历史、现状和趋势[J].自然灾害学报,2004,13(5):46-53.
[8]Mustafa T,Bulent C.Automatic detection of earthquake-damaged buildings using DEMs createdfrom pre-and post-earthquake stereo aerial photographs[J].International Journal of Remote Sens-ing,2005,26(4):823-832.
[9]陈文凯.面向震害评估的遥感应用技术研究[D].硕士学位论文,中国地震局兰州地震研究所,2007.
[10]任玉环,刘亚岚,魏成阶,胡蕾秋.汶川地震道路震害高分辨率遥感信息提取方法探讨[J].遥感技术与应用,2009,(1):52-56+133-134.
[11]王艳萍,姜纪沂,林玲玲.高分辨率遥感影像中道路震害信息的识别方法[J].计算机工程与应用,2012,(3):173-175.
[12]Peer M,Bogdan G.Edge Detection with embedded confidence[J].IEEE Transactions on pattern a-nalysis and machine intelligence,2001,23(12):1351-1365.
[13]崔屹.图像处理与分析-数学形态学方法及应用[M].北京:科学出版社,2000.
[14]张永生,巩丹超,等.高分辨率遥感卫星应用--成像模型、处理算法及应用技术[M].北京:科学出版社,2004.
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