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...
-  2018 

光学遥感影像变化检测研究的回顾与展望
State-of-the-Art Remotely Sensed Images-Based Change Detection Methods

DOI: 10.13203/j.whugis20180419

Keywords: 变化检测,可靠性,光学遥感影像,回顾与展望,
change detection
,reliability,optical remote sensing images,review

Full-Text   Cite this paper   Add to My Lib

Abstract:

地理实体或现象的变化数据是自然资源管理、灾害监测、生态环境保护和可持续发展等的重要科学分析依据。光学遥感影像变化检测是遥感科学与技术的重要研究领域,40年来,国内外学者针对遥感影像变化检测做了大量研究工作,取得了一系列成果。力图从变化检测关键问题、方法与技术、面临的挑战以及应用领域等多个角度对光学遥感影像变化检测研究进行系统的回顾,分析变化检测技术的研究现状,并且提出未来有待进一步解决的研究问题

References

[1]  Singh A. Review Article Digital Change Detection Techniques Using Remotely-Sensed Data[J]. International Journal of Remote Sensing, 1989, 10(6):989-1003, doi:10.1080/01431168908903939
[2]  Weismiller R, Kristoff S, Scholz D, et al.Change Detection in Coastal Zone Environments[J]. Photogrammetric Engineering and Remote Sensing, 1977,43(12):1533-1539
[3]  Zhou L, Cao G, Li Y, et al. Change Detection Based on Conditional Random Field with Region Connection Constraints in High-Resolution Remote Sensing Images[J]. IEEE J Sel Top Appl Earth Obs Remote Sens,2016, doi:10.1109/JSTARS.2016.2514610
[4]  Ghosh S, Bruzzone L, Patra S, et al.A Context-Sensitive Technique for Unsupervised Change Detection Based on Hopfield-Type Neural Networks[J]. IEEE Transactions on Geoscience and Remote Sensing,2007, 45:778-789, doi:10.1109/TGRS.2006.888861
[5]  Zhang P, Lv Z, Shi W.Object-Based Spatial Feature for Classification of very High Resolution Remote Sensing Images[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(6):1572-1576
[6]  Li Liang,Wang Lei,Sun Xiaopeng,et al. Remote Sensing Change Detection Method Based on Object-Oriented Change Vector Analysis[J].Remote Sen-sing Information, 2017, 32(6):71-77(李亮,王蕾,孙晓鹏,等.面向对象变化向量分析的遥感影像变化检测[J].遥感信息, 2017, 32(6):71-77)
[7]  Huang F, Chen L, Yin K,et al. Object Oriented Change Detection and Damage Assessment Using High Resolution Remote Sensing Images, Tangjiao Landslide, Three Gorges Reservoir, China[J]. Environmental Earth Sciences, 2018, 77:183
[8]  Bhatt A, Ghosh S K, Kumar A. Spectral Indices Based Object Oriented Classification for Change Detection Using Satellite Data[J]. Int J Syst Assur Eng Manag, 2018, 9(1):33-42
[9]  Menz G. From Change Detection to Change Modelling[C]. International Workshop on Change Detection, Wuhan, China, 2013
[10]  Zhang P,Lv Z,Shi W. Local Spectrum-Trend Similarity Approach for Detecting Land-Cover Change by Using SPOT-5 Satellite Images[J]. IEEE Geoscience and Remote Sensing Letters,2014, 11(4):738-742
[11]  Ban Y,Yousif O.Change Detection Techniques:A Review[M]//Multitemporal Remote Sensing. Stockholm:Springer, 2016
[12]  Ma Jianwen,Tian Guoliang,Wang Changyao,et al.Review of the Development of Remote Sensing Change Detection Technology[J].Advance in Earth Sciences, 2004,19(2):192-196(马建文, 田国良, 王长耀,等.遥感变化检测技术发展综述[J].地球科学进展, 2004,19(2):192-196)
[13]  Cho S, Haralick R,Yi S.Improvement of Kittler and Illingworth's Minimum Error Thresholding[J]. Pattern Recogn, 1989,22(5):609-617
[14]  Bruzzone L,Prieto D F.Automatic Analysis of the Difference Image for Unsupervised Change Detection[J]. IEEE Transactions on Geoscience and Remote Sensing,2000,38(3):1171-1182
[15]  Yuan F, Sawaya K E, Loeffelholz B C, et al. Land Cover Classification and Change Analysis of the Twin Cities (Minnesota) Metropolitan Area by Multitemporal Landsat Remote Sensing[J]. Remote Sensing of Environment, 2005, 98(2):317-328
[16]  Wu K, Du Q, Wang Y,et al.Supervised Sub-Pixel Mapping for Change Detection from Remotely Sensed Images with Different Resolutions[J]. Remote Sensing, 2017, 9:284, doi:10.3390/rs9030284
[17]  Xu Y, Lin L,Meng D. Learning-Based Sub-Pixel Change Detection Using Coarse Resolution Satellite Imagery[J]. Remote Sensing, 2017, 9:709; doi:10.3390/rs9070709
[18]  Sun Tiantian,Deng Wenbin,Ma Lin.Urban Land Use Change Detection Based on Object-Oriented Classification[J]. Geospatial Information,2018, 16(9):95-98(孙天天,邓文彬,马琳.基于面向对象分类的城市土地利用变化检测[J].地理空间信息,2018, 16(9):95-98)
[19]  Lyu H, Lu H, Mou L.Learning a Transferable Change Rule from a Recurrent Neural Network for Land Cover Change Detection[J]. Remote Sensing, 2016, 8:506, doi:10.3390/rs8060506
[20]  Cao G, Wang B, Xavier H C, et al.A New Diffe-rence Image Creation Method Based on Deep Neural Networks for Change Detection in Remote Sensing Images[J]. International Journal of Remote Sen-sing, 2017, 38(23):7161-7175
[21]  Hao M, Shi W, Zhang H, et al.Unsupervised Change Detection with Expectation-Maximization-Based Level Set[J]. IEEE Geoscience and Remote Sensing Letters,2014, 11(1):210-214
[22]  Hao M, Shi W,Deng K, et al.Superpixel-Based Active Contour Model for Unsupervised Change Detection from Satellite Images[J].International Journal of Remote Sensing,2016, 37(18):4276-4295
[23]  Im J, Jensen J R. A Change Detection Model Based on Neighborhood Correlation Image Analysis and Decision Tree Classification[J]. Remote Sensing of Environment, 2005, 99:326-340
[24]  Zhang P,Shi W, Wong M S, et al.A Reliability-Based Multi-algorithm Fusion Technique in Detecting Changes in Land Cover[J]. Remote Sensing,2013, 5(3):1134-1151

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133