Spatial Big Data Science Classification Techniques for Earth Observation Imagery /

Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristi...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Jiang, Zhe (Συγγραφέας), Shekhar, Shashi (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03241nam a22004815i 4500
001 978-3-319-60195-3
003 DE-He213
005 20170714103724.0
007 cr nn 008mamaa
008 170714s2017 gw | s |||| 0|eng d
020 |a 9783319601953  |9 978-3-319-60195-3 
024 7 |a 10.1007/978-3-319-60195-3  |2 doi 
040 |d GrThAP 
050 4 |a QA76.9.D343 
072 7 |a UNF  |2 bicssc 
072 7 |a UYQE  |2 bicssc 
072 7 |a COM021030  |2 bisacsh 
082 0 4 |a 006.312  |2 23 
100 1 |a Jiang, Zhe.  |e author. 
245 1 0 |a Spatial Big Data Science  |h [electronic resource] :  |b Classification Techniques for Earth Observation Imagery /  |c by Zhe Jiang, Shashi Shekhar. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2017. 
300 |a XV, 131 p. 37 illus., 27 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a Part I Overview of Spatial Big Data Analytics -- 1 Spatial Big -- 2 Spatial and Spatiotemporal Big Data science -- Part II Classification of Earth Observation Imagery Big Data -- 3 Overview of Earth Imagery Classification -- 4 Spatial Information Gain Based Spatial Decision Tree -- 5 Focal-Test-Based Spatial Decision Tree -- 6 Spatial Ensemble Learning -- Part III Future Research Needs -- 7 Future Research Needs -- References. 
520 |a Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book. This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference. 
650 0 |a Computer science. 
650 0 |a Physical geography. 
650 0 |a Data mining. 
650 0 |a Remote sensing. 
650 1 4 |a Computer Science. 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Remote Sensing/Photogrammetry. 
650 2 4 |a Earth System Sciences. 
700 1 |a Shekhar, Shashi.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319601946 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-60195-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)