國立高雄大學圖資館 |

Language: English

Back

Spatial data handling in big data er...

(1998 :)

Spatial data handling in big data eraselect papers from the 17th IGU Spatial Data Handling Symposium 2016 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Spatial data handling in big data eraedited by Chenghu Zhou ... [et al.].
Reminder of title:	select papers from the 17th IGU Spatial Data Handling Symposium 2016 /
other author:	Zhou, Chenghu.
corporate name:
Published:	Singapore :Springer Singapore :2017.
Description:	xiii, 237 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Geographic information systems
Online resource:	http://dx.doi.org/10.1007/978-981-10-4424-3
ISBN:	9789811044243$q(electronic bk.)

Spatial data handling in big data eraselect papers from the 17th IGU Spatial Data Handling Symposium 2016 /
Spatial data handling in big data eraselect papers from the 17th IGU Spatial Data Handling Symposium 2016 /[electronic resource] :edited by Chenghu Zhou ... [et al.]. - Singapore :Springer Singapore :2017. - xiii, 237 p. :ill., digital ;24 cm. - Advances in geographic information science,1867-2434. - Advances in geographic information science..

Big geographical data storage and search -- Data-intensive geospatial computing and data mining -- Visualization of big geographical data -- Multi-scale spatial data representations, data structures and algorithms -- Space-time modelling and analysi -- Geological applications of Big Data and multi-criteria decision analysis.

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.

ISBN: 9789811044243$q(electronic bk.)

Standard No.: 10.1007/978-981-10-4424-3doiSubjects--Topical Terms:

281515
Geographic information systems

LC Class. No.: G70.212

Dewey Class. No.: 910.285

Spatial data handling in big data eraselect papers from the 17th IGU Spatial Data Handling Symposium 2016 /
LDR:02378nmm a2200337 a 4500 001 515102
003 DE-He213
005 20170504090909.0
006 m d
007 cr nn 008maaau
008 180126s2017 si s 0 eng d
020 $a 9789811044243$q(electronic bk.)
020 $a 9789811044236$q(paper)
024 7 $a 10.1007/978-981-10-4424-3 $2 doi
035 $a 978-981-10-4424-3
040 $a GP $c GP
041 0 $a eng
050 4 $a G70.212
072 7 $a RGW $2 bicssc
072 7 $a SCI030000 $2 bisacsh
072 7 $a TEC036000 $2 bisacsh
082 0 4 $a 910.285 $2 23
090 $a G70.212 $b .I61 2016
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Spatial data handling in big data era $h [electronic resource] : $b select papers from the 17th IGU Spatial Data Handling Symposium 2016 / $c edited by Chenghu Zhou ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2017.
300 $a xiii, 237 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in geographic information science, $x 1867-2434
505 0 $a Big geographical data storage and search -- Data-intensive geospatial computing and data mining -- Visualization of big geographical data -- Multi-scale spatial data representations, data structures and algorithms -- Space-time modelling and analysi -- Geological applications of Big Data and multi-criteria decision analysis.
520 $a This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.
650 0 $a Geographic information systems $3 281515
650 1 4 $a Geography. $3 174760
650 2 4 $a Geographical Information Systems/Cartography. $3 273999
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Data Storage Representation. $3 277024
650 2 4 $a Earth Sciences, general. $3 338609
700 1 $a Zhou, Chenghu. $3 785374
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Advances in geographic information science. $3 559673
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-4424-3
950 $a Earth and Environmental Science (Springer-11646)