全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于LiDAR和航空影像的地震灾害倒塌建筑物信息提取

DOI: 10.6046/gtzyyg.2011.03.14, PP. 77-81

Keywords: 地震灾害,倒塌建筑物,信息提取,LiDAR,面向对象的图像分析(OBIA),SVM,航空影像

Full-Text   Cite this paper   Add to My Lib

Abstract:

地震灾害损失评估是震后展开救灾工作的重要环节。快速、准确地获取震后损毁建筑物信息能够为灾区减灾、救灾工作提供有效的支持。高分辨率航空遥感是灾害监测的重要技术手段,但其信息自动提取的精度受到一定的限制。近年来新出现的LiDAR技术能够提供地面目标的高程信息,可应用于复杂环境下倒塌建筑物信息的提取。研究中采用航空遥感数据和LiDAR数据,基于面向对象的图像分析(Object-BasedImageAnalysis,OBIA)与SVM技术相结合的方法对2010年1月12日海地地震中倒塌建筑物信息进行了提取,提取总体精度达到86.1%。

References

[1]  郭华东,鹿琳琳,马建文,等.一种改进的地震灾害倒塌房屋遥感信息自动识别方法
[2]  [J] 科学通报,2009,54(17):2581-2585.
[3]  Kaya S,Curran P J,Llewellyn G.Post-earthquake Building Collapse:A Comparison of Government Statistics and Estimates Derived from SPOT HRVIR Data
[4]  [J] Int J Remote Sens,2005,26(3):2731-2740.
[5]  Sakamoto M,Takasago Y,Uto K,et al.Automatic Detection of Damaged Area of Iran Earthquake by High-resolution Satellite Imagery
[6]  [C] //Proceedings of IGARSS’04.Alaska,2004:1418-1421.
[7]  Turker M,San B T.Detection of Collapsed Buildings Caused by the 1999 Izmit,Turkey Earthquake Through Digital Analysis of Post-event Aerial Photographs
[8]  [J] Int J Remote Sens,2004,25(21):4701-4714.
[9]  Turker M,Cetinkaya B.Automatic Detection of Earthquake- damaged Buildings Using DEMs Created from Pre- and Post-earthquake Stereo Aerial Photographs
[10]  [J] Int J Remote Sens,2005,26(4):823-832.
[11]  Gamba P,Dell’Acqua F,Trianni G.Rapid Damage Detection in the Bam Area Using Multitemporal SAR and Exploiting Ancillary Data
[12]  [J] IEEE Transactions on Geoscience & Remote Sensing,2007,45(6):1582-1589.
[13]  Alexander B,Christian H,Goepfert J,et al.Aspects of Generating Precise Digital Terrain Models in the Wadden Sea from Lidar-water Classification and Structure Line Extraction
[14]  [J] ISPRS Journal of Photogrammetry & Remote Sensing,2008,63(5):510-528.
[15]  Axelsson P.DEM Generation from Laser Scanner Data Using Adaptive TIN Models
[16]  [J] International Archives of Photogrammetry and Remote Sensing,2000,33(1):110-117.
[17]  Baatz M,Sch?pe A.Multiresolution Segmentation—an Optimization Approach for High Quality Multi-scale Image Segmentation
[18]  [C] //Strobl J,Blaschke T,Griesebner G.Angewandte Geographische Informations-Verarbeitung XII.Karlsruhe:Wichmann Verlag,2000:12-23.
[19]  Haralick R M,Shanmugan K,Dinstein I.Textural Features for Image Classification
[20]  [J] IEEE Transactions on Systems,Man,and Cybernetics,1973,3(6):610-621.
[21]  于海洋,甘甫平,武法东,等.VHSR图像基于分割对象分类器性能评价
[22]  [J] 国土资源遥感,2008(2):30-34.
[23]  Foody G M,Mathur A.Toward Intelligent Training of Supervised Image Classifications:Directing Training Data Acquisition for SVM Classification
[24]  [J] Remote Sensing of Environment,2004,93(1/2):107-117.
[25]  Vapnik V.The Nature of Statistical Learning Theory
[26]  [M] New York:Springer-Verlag,1995.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133