語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
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 /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Spatial data handling in big data eraedited by Chenghu Zhou ... [et al.].
其他題名:
select papers from the 17th IGU Spatial Data Handling Symposium 2016 /
其他作者:
Zhou, Chenghu.
團體作者:
出版者:
Singapore :Springer Singapore :2017.
面頁冊數:
xiii, 237 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Geographic information systems
電子資源:
http://dx.doi.org/10.1007/978-981-10-4424-3
ISBN:
9789811044243$q(electronic bk.)
Spatial data handling in big data eraselect papers from the 17th IGU Spatial Data Handling Symposium 2016 /
Spatial data handling in big data era
select papers from the 17th IGU Spatial Data Handling Symposium 2016 /[electronic resource] :edited by Chenghu Zhou ... [et al.]. - Singapore :Springer Singapore :2017. - xiii, 237 p. :ill., digital ;24 cm. - Advances in geographic information science,1867-2434. - Advances in geographic information science..
Big geographical data storage and search -- Data-intensive geospatial computing and data mining -- Visualization of big geographical data -- Multi-scale spatial data representations, data structures and algorithms -- Space-time modelling and analysi -- Geological applications of Big Data and multi-criteria decision analysis.
This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.
ISBN: 9789811044243$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)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000143865
電子館藏
1圖書
電子書
EB G70.212 I61 2017
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-981-10-4424-3
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入