Automatic Analysis and Mining of Remote Sensing Big Data

doi:10.13485/j.cnki.11-2089.2014.0187

Abstract

Abstract: With the diversification of the imaging methods and the growing categories, quantity, and observation frequency of remote sensing data, the ability of land-cover observation has reached an unprecedented level, which means a new era of big data in remote sensing is coming. However, the existing methods and processing techniques cannot fulfill the need of the big data application in remote sensing. Thus, to develop the automatic analysis and mining theory and techniques for remote sensing big data is among the most advanced international research areas. This paper investigates and analyses the domestic and overseas research status and progress around this field and points out its key problems and developing trends.

Key words: remote sensing big data, representation, retrieval, understanding, data mining

CLC Number:

P237

LI Deren, ZHANG Liangpei, XIA Guisong. Automatic Analysis and Mining of Remote Sensing Big Data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12): 1211-1216.

References

[1] ADSHEAD A. Data Set to Grow 10-fold by 2020 as Internet of Things Takes off [EB/OL]. [2014-04-09]. http://www.computerweekly.com/news/2240217788/data-set-to-grow-10-fold-by-2020-as-internet-of-things-takes-off.
[2] MAYER S V, CUKIER K.Big Data:a Revolution That Will Transform How We Live, Work, and Think [M]. Translated by ZHOU Tao. Hangzhou: Zhejiang People's Publishing House, 2012. (MAYER S V, CUKIER K.大数据时代:生活,工作与思维的大变革 [M].周涛, 译. 杭州:浙江人民出版社,2012.)
[3] ZIKOPOULOS P, EATON C, DEROOS D, et al. Understanding of Big Data [M]. New York:Mc Graw Hill, 2012.
[4] DAVID G.Big Data [J]. Nature, 2008, 455(7209): 1-136.
[5] WOUTER L,JOHN W.Dealing with Big Data [J]. Science, 2011, 331(6018): 639-806.
[6] White House Office of Science and Technology Policy. Big Data is a Big Deal[EB/OL]. [2012-03-29].http://www.whitehouse.gov/blog/2012/03/29/big-data-big-deal.
[7] White House Executive Office of the President. Big Data across the Federal Government [EB/OL].[2012-03-29].http://www.whitehouse.gov/sites/default/files/microsites/ ostp/big_data_fact_sheet.pdf.
[8] WANG Weihang. The British Provides Huge Sum of Money for Developing Big Data Technologies to Promote Economic Growth [EB/OL]. [2013-05-31]. http://www.e-gov.org.cn/xinxihua/news003/201305/141545.html. (王苇航.英国斥巨资发展大数据技术以期推动经济增长[EB/OL]. [2013-05-31].http://www.e-gov.org.cn/xinxihua/news003/201305/141545.html.)
[9] LI Guojie, CHENG Xueqi. Research Status and Scientific Thinking of Big Data [J]. Bulletin of Chinese Academy of Sciences, 2012, 27(6): 647-657. (李国杰,程学旗.大数据研究:未来科技及经济社会发展的重大战略领域—大数据的研究现状与科学思考[J]. 中国科学院院刊,2012,27(6): 647-657.)
[10] LI Deren, TONG Qingxi, LI Rongxing, et al. Some Frontier Problems of High Resolution Earth Observation [J]. Scientia Sinica Terrae, 2012, 42(6): 805-813. (李德仁, 童庆禧, 李荣兴,等. 高分辨率对地观测的若干前沿科学问题[J]. 中国科学: 地球科学, 2012, 42(6): 805-813.)
[11] QUARTULLI M, OLAIZOLA I G. A Review of EO Image Information Mining[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013 (75):11-28.
[12] XIN Fangfang, JIAO Licheng, WANG Guiting. Change Detection in Multitemporal Remote Sensing Images Based on Dynamic Fuzzy Fisher Classifier and Non Local Mean Weighted Method [J]. Acta Geodaetica et Cartographica Sinica, 2012,41(4):584-590.(辛芳芳,焦李成,王桂婷. 非局部均值加权的动态模糊Fisher分类器的遥感图像变化检测[J].测绘学报,2012,41(4):584-590.)
[13] LI Hui,XIAO Pengfeng, FENG Xuezhi, et al. Multi-scale Edge Detection in Multispectral Remotely Sensed Imagery Based Vector[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(1): 100-107. (李晖,肖鹏峰,冯学智,等.基于向量场模型的多光谱遥感图像多尺度边缘检测[J].测绘学报,2012,41(1):100-107.)
[14] ZHANG Nan.Content-based Remote Sensing Image Retrieval [D].Changsha:National University of Defense Technology, 2008. (张男.基于内容的光学遥感图像检索关键技术研究[D].长沙:国防科学技术大学, 2008.)
[15] YUAN Deyang, NIE Juan, DENG Lei, et al. Design and Implementation of Metadata-based Multi-source Remote Sensing Image Database Integration Technology [J]. Science of Surveying and Mapping, 2012, 37(3): 151-155. (袁德阳,聂娟,邓磊,等. 基于元数据的多源遥感影像数据库集成技术研究与实现 [J]. 测绘科学, 2012, 37(3): 151-155.)
[16] DATCU M, DASCHIEL H, PELIZZARI A, et al. Information Mining in Remote Sensing Image Archives: System Concepts [J].IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(12): 2923-2936.
[17] KOPERSKI A, TUSK C, MARCHISIO G, et al. Learning Bayesian Classifiers for Scene Classification with a Visual Grammar [J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(3): 581-589.
[18] PORWAY J, WANG Q, ZHU S C.A Hierarchical and Contextual Model for Aerial Image Parsing [J]. International Journal of Computer Vision, 2010, 88(2): 254-283.
[19] LIENOU M L, MAITRE H, DATCU M.Semantic Annotation of Satellite Images Using Latent Dirichlet Allocation [J]. IEEE Geoscience and Remote Sensing Letters, 2010, 7(1): 28-32.
[20] YUE P, WEI Y,DI L, et al. Sharing Geospatial Provenance in a Service-oriented Environment [J]. Computers, Environment and Urban Systems, 2011, 35(2): 333-343.
[21] CHEN N. Geoproessing Workflow Driven Wildfire Hot Pixel Detection under Sensor Web Environment [J]. Computers & Geosciences, 2010, 36: 362-372.
[22] LI Deren, YAO Yuan, SHAO Zhenfeng. Big Data in Smart City[J].Geomatics and Information Science of Wuhan University, 2014, 39(6): 631-640. (李德仁,姚远,邵振峰. 智慧城市中的大数据[J].武汉大学报:信息科学版, 2014, 39(6): 631-640.)
[23] HAN J, KAMBER M, PEI J.Data Mining: Concepts and Techniques [M]. San Francisco:Morgan Kaufmann Publishers, 2006.
[24] LI Deren, WANG Shuliang, LI Deyi. Spatial Data Mining Theories and Applications [M].Beijing: Science Press, 2013. (李德仁,王树良,李德毅. 空间数据挖掘理论与应用 [M].北京:科学出版社,2013.)
[25] LI Xi.Luminous Remote Sensing Cultural Perspectives Observation to the Earth [EB/OL]. [2014-05-30]. http://ccnucity.ccnu.edu.cn/ShowDetail.aspx?id=5593 (李熙. 夜光遥感:以人文视角观测地球[EB/OL]. [2014-05-30]. http://ccnucity.ccnu.edu.cn/ShowDetail.aspx?id=5593)