Software and applications of spatial data mining

Most big data are spatially referenced, and spatial data mining (SDM) is the key to the value of big data. In this paper, SDM are overviewed in the aspects of software and application. First, spatial data are summarized on their rapid growth, distinct characteristics, and implicit values. Second, the principles of SDM are briefed with the descriptive definition, fundamental attributes, discovery mechanism, and usable methods. Third, SDM software is presented in the context of software components, developing methodology, typical software for geographical information system (GIS) data and remote sensing (RS) images, and software trend. Fourth, SDM applications are outlined on GIS data, RS image, and spatiotemporal video data. The final is the concluding remarks and perspectives. WIREs Data Mining Knowl Discov 2016, 6:84–114. doi: 10.1002/widm.1180

[1]  Doheon Lee,et al.  A Taxonomy of Dirty Data , 2004, Data Mining and Knowledge Discovery.

[2]  Theodore Johnson,et al.  Exploratory Data Mining and Data Cleaning , 2003 .

[3]  K.J. Cios,et al.  From the guest editor medical data mining and knowledge discovery , 2000, IEEE Engineering in Medicine and Biology Magazine.

[4]  H. Kriegel,et al.  Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support , 2000, Data Mining and Knowledge Discovery.

[5]  Eric Gossett,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2015 .

[6]  Viktor Mayer-Schnberger,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2013 .

[7]  Michael F. Goodchild,et al.  Defining a Digital Earth System , 2008, Trans. GIS.

[8]  Ranga Raju Vatsavai,et al.  Spatiotemporal data mining in the era of big spatial data: algorithms and applications , 2012, BigSpatial '12.

[9]  Armin Gruen Reality-based generation of virtual environments for digital earth , 2008, Int. J. Digit. Earth.

[10]  Huadong Guo,et al.  Digital Earth 2020: towards the vision for the next decade , 2012, Int. J. Digit. Earth.

[11]  Salvatore J. Stolfo,et al.  Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem , 1998, Data Mining and Knowledge Discovery.

[12]  B. Clinton Executive Order 12906: Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure , 1994 .

[13]  Steven K. Feiner,et al.  Spatial computing , 2015, Commun. ACM.

[14]  Deren Li,et al.  Can night-time light images play a role in evaluating the Syrian Crisis? , 2014 .

[15]  Shuliang Wang,et al.  Brightness of Nighttime Lights as a Proxy for Freight Traffic: A Case Study of China , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[16]  Shuliang Wang,et al.  Data Mining and Knowledge Discovery , 2005, Mathematical Principles of the Internet.

[17]  Michael Mitzenmacher,et al.  Detecting Novel Associations in Large Data Sets , 2011, Science.

[18]  Li Deren Theories and Technologies of Spatial Data Mining and Knowledge Discovery , 2002 .

[19]  Huadong Guo,et al.  Next-generation Digital Earth , 2012, Proceedings of the National Academy of Sciences.

[20]  Monika Sester,et al.  Knowledge acquisition for the automatic interpretation of spatial data , 2000, Int. J. Geogr. Inf. Sci..

[21]  J. Manyika Big data: The next frontier for innovation, competition, and productivity , 2011 .

[22]  S. R,et al.  Data Mining with Big Data , 2017, 2017 11th International Conference on Intelligent Systems and Control (ISCO).

[23]  Yuan Yao,et al.  From digital Earth to smart Earth , 2014 .

[24]  Albert-Laszló Barabási,et al.  Bursts : the hidden patterns behind everything we do, from your e-mail to bloody crusades , 2011 .

[25]  Shuliang Wang,et al.  Spatial data mining under Smart Earth , 2011, 2011 IEEE International Conference on Granular Computing.

[26]  Xiaoling Chen,et al.  Satellite-Observed Nighttime Light Variation as Evidence for Global Armed Conflicts , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[27]  Xi Li,et al.  Detecting Zimbabwe's Decadal Economic Decline Using Nighttime Light Imagery , 2013, Remote. Sens..

[28]  Deren Li,et al.  The new era for geo-information , 2009, Science in China Series F: Information Sciences.

[29]  Shashi Shekhar,et al.  Encyclopedia of GIS , 2007, Encyclopedia of GIS.

[30]  Mark Gahegan,et al.  Geospatial Data Mining and Knowledge Discovery , 2000 .

[31]  Nigel Thrift,et al.  International Encyclopaedia of Human Geography , 2009 .

[32]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[33]  Deyi Li,et al.  Spatial Data Cleaning , 2015 .

[34]  Jian Peng,et al.  Intercalibration of DMSP-OLS night-time light data by the invariant region method , 2013 .

[35]  Alex A. Freitas,et al.  A survey of hierarchical classification across different application domains , 2010, Data Mining and Knowledge Discovery.

[36]  Shuliang Wang,et al.  Spatial Data Mining: A Perspective of Big Data , 2014, Int. J. Data Warehous. Min..

[37]  Ah Chung Tsoi,et al.  Face recognition: a convolutional neural-network approach , 1997, IEEE Trans. Neural Networks.

[38]  Albert-László Barabási,et al.  Bursts: The Hidden Pattern Behind Everything We Do , 2010 .

[39]  Noel A Cressie,et al.  Statistics for Spatial Data, Revised Edition. , 1994 .

[40]  F. Burstein,et al.  Handbook on Decision Support Systems 1 , 2008 .

[41]  Jiawei Han,et al.  Efficient Polygon Amalgamation Methods for Spatial OLAP and Spatial Data Mining , 1999, SSD.

[42]  Deyi Li,et al.  Spatial Data Mining: Theory and Application , 2016 .

[43]  Jiawei Han,et al.  Geographic Data Mining and Knowledge Discovery , 2001 .

[44]  Ian Davidson,et al.  Visual Data Mining: Techniques and Tools for Data Visualization and Mining , 2002 .

[45]  Din J. Wasem,et al.  Mining of Massive Datasets , 2014 .

[46]  A. Gore The digital earth : Understanding our planet in the 21st century , 1998 .

[47]  Naizhuo Zhao,et al.  Mapping spatio-temporal changes of Chinese electric power consumption using night-time imagery , 2012 .

[48]  Shuliang Wang,et al.  Data Field for Hierarchical Clustering , 2011, Int. J. Data Warehous. Min..

[49]  Robert Haining,et al.  Spatial Data Analysis: Theory and Practice , 2003 .

[50]  Deyi Li,et al.  Artificial Intelligence with Uncertainty , 2004, CIT.

[51]  Jiawei Han,et al.  A progressive refinement approach to spatial data mining , 1999 .

[52]  Xinyue Ye,et al.  Knowledge Discovery in Spatial Data , 2009 .