GIS: Temporal Database Issues, Spatio-Temporal Database, Dynamic

Chapter Contents (Back)
Systems. GIS. Temporal Data. Dynamic Data.
See also GIS for Transportation, Roads.

Bernard, L.[Lars], Schmidt, B.[Benno], Streit, U.[Ulrich], Uhlenkueken, C.[Christoph],
Managing, Modeling, and Visualizing High-dimensional Spatio-temporal Data in an Integrated System,
GeoInfo(2), No. 1, March 1998, pp. 59-77.
DOI Link BibRef 9803

Chomicki, J.[Jan], Revesz, P.Z.[Peter Z.],
Constraint-Based Interoperability of Spatiotemporal Databases,
GeoInfo(3), No. 3, September 1999, pp. 211-243.
DOI Link BibRef 9909

Tryfona, N.[Nectaria], Jensen, C.S.[Christian S.],
Conceptual Data Modeling for Spatiotemporal Applications,
GeoInfo(3), No. 3, September 1999, pp. 245-268.
DOI Link BibRef 9909

Erwig, M.[Martin], Guting, R.H.[Ralf Hartmut], Schneider, M.[Markus], Vazirgiannis, M.[Michalis],
Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases,
GeoInfo(3), No. 3, September 1999, pp. 269-296.
DOI Link BibRef 9909

Sakr, M.A.[Mahmoud Attia], Güting, R.H.[Ralf Hartmut],
Spatiotemporal pattern queries,
GeoInfo(15), No. 3, July 2011, pp. 497-540.
WWW Link. 1106

Sakr, M.A.[Mahmoud Attia], Güting, R.H.[Ralf Hartmut],
Group spatiotemporal pattern queries,
GeoInfo(18), No. 4, 2014, pp. 699-746.
WWW Link. 1410

Zhang, W.[Wei], Hunter, G.J.[Gary J.],
Temporal Interpolation of Spatially Dynamic Object,
GeoInfo(4), No. 4, December 2000, pp. 403-418.
DOI Link 0101

Chen, J.[Jun], Jiang, J.[Jie],
An Event-Based Approach to Spatio-Temporal Data Modeling in Land Subdivision Systems,
GeoInfo(4), No. 4, December 2000, pp. 387-402.
DOI Link 0101

Roddick, J.F.[John F.], Grandi, F.[Fabio], Mandreoli, F.[Federica], Scalas, M.R.[Maria Rita],
Beyond Schema Versioning: A Flexible Model for Spatio-Temporal Schema Selection,
GeoInfo(5), No. 1, March 2001, pp. 33-50.
DOI Link 0105

Peuquet, D.J.[Donna J.],
Making Space for Time: Issues in Space-Time Data Representation,
GeoInfo(5), No. 1, March 2001, pp. 11-32.
DOI Link 0105

Spery, L.[Laurent], Claramunt, C.[Christophe], Libourel, T.[Therese],
A Spatio-Temporal Model for the Manipulation of Lineage Metadata,
GeoInfo(5), No. 1, March 2001, pp. 51-70.
DOI Link 0105

Grumbach, S.[Stephane], Rigaux, P.[Philippe], Segoufin, L.[Luc],
Spatio-Temporal Data Handling with Constraints,
GeoInfo(5), No. 1, March 2001, pp. 95-115.
DOI Link 0105

Brinkhoff, T.[Thomas],
A Framework for Generating Network-Based Moving Objects,
GeoInfo(6), No. 2, June 2002, pp. 153-180.
DOI Link For spatio-temporal database analysis. 0205

Tzouramanis, T.[Theodoros], Vassilakopoulos, M.[Michael], Manolopoulos, Y.[Yannis],
On the Generation of Time-Evolving Regional Data,
GeoInfo(6), No. 3, September 2002, pp. 207-231.
DOI Link 0208

Frihida, A.[Ali], Marceau, D.J.[Danielle J.], Thériault, M.[Marius],
Development of a Temporal Extension to Query Travel Behavior Time Paths Using an Object-Oriented GIS,
GeoInfo(8), No. 3, September 2004, pp. 211-235.
DOI Link 0409

Guo, B.[Bo], Kurt, C.E.[Carl E.],
Towards Temporal Dynamic Segmentation,
GeoInfo(8), No. 3, September 2004, pp. 265-283.
DOI Link 0409
Temporal data (e.g. traffic) in GIS. BibRef

Marchand, P.[Pierre], Brisebois, A.[Alexandre], Bédard, Y.[Yvan], Edwards, G.[Geoffrey],
Implementation and evaluation of a hypercube-based method for spatiotemporal exploration and analysis,
PandRS(59), No. 1-2, August 2004, pp. 6-20.
Elsevier DOI 0411

Isenegger, D.[Daniel], Price, B.[Bronwyn], Wu, Y.[Yi], Fischlin, A.[Andreas], Frei, U.[Urs], Weibel, R.[Robert], Allgöwera, B.[Britta],
IPODLAS: A software architecture for coupling temporal simulation systems, VR, and GIS,
PandRS(60), No. 1, December 2005, pp. 34-47.
WWW Link. 0602

Mouza, C.[Cédric], Rigaux, P.[Philippe],
Mobility Patterns,
GeoInfo(9), No. 4, December 2005, pp. 297-319.
Springer DOI 0602
Data structure to track mobile objects and report on position. BibRef

Choi, J.M.[Jin-Mu], Seong, J.C.[Jeong Chang], Kim, B.[Bora], Usery, E.L.[E. Lynn],
Innovations in Individual Feature History Management: The Significance of Feature-based Temporal Model,
GeoInfo(12), No. 1, March 2008, pp. 1-20.
Springer DOI 0802

Botea, V.[Viorica], Mallett, D.[Daniel], Nascimento, M.A.[Mario A.], Sander, J.[Jörg],
PIST: An Efficient and Practical Indexing Technique for Historical Spatio-Temporal Point Data,
GeoInfo(12), No. 2, June 2008, pp. xx-yy.
Springer DOI 0804

Ding, H.[Hui], Trajcevski, G.[Goce], Scheuermann, P.[Peter],
Efficient Maintenance of Continuous Queries for Trajectories,
GeoInfo(12), No. 3, September 2008, pp. xx-yy.
Springer DOI 0804

Fu, L.[Lei], Soh, L.K.[Leen-Kiat], Samal, A.[Ashok],
Techniques for Computing Fitness of Use (FoU) for Time Series Datasets with Applications in the Geospatial Domain,
GeoInfo(12), No. 1, March 2008, pp. 91-115.
Springer DOI 0802

Chen, J.[Jidong], Meng, X.F.[Xiao-Feng],
Update-efficient indexing of moving objects in road networks,
GeoInfo(13), No. 4, December 2009, pp. xx-yy.
Springer DOI 0909

Anderson, S.[Scot], Revesz, P.[Peter],
Efficient MaxCount and threshold operators of moving objects,
GeoInfo(13), No. 4, December 2009, pp. xx-yy.
Springer DOI 0909

Sagar, B.S.D.[B.S. Daya],
Visualization of Spatiotemporal Behavior of Discrete Maps via Generation of Recursive Median Elements,
PAMI(32), No. 2, February 2010, pp. 378-384.
And: Erratum: PAMI(36), No. 3, March 2014, pp. web-web.
Merging data in GIS to display seamless results (maps). BibRef

Gao, Y.J.[Yun-Jun], Zheng, B.H.[Bai-Hua], Chen, G.C.[Gen-Cai], Li, Q.[Qing],
Algorithms for constrained k-nearest neighbor queries over moving object trajectories,
GeoInfo(14), No. 2, April 2010, pp. xx-yy.
Springer DOI 1003

Huang, Y.K.[Yuan-Ko], Lee, C.A.[Chi-Ang],
Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity,
GeoInfo(14), No. 2, April 2010, pp. xx-yy.
Springer DOI 1003

Winter, S.[Stephan], Yin, Z.C.[Zhang-Cai],
The elements of probabilistic time geography,
GeoInfo(15), No. 3, July 2011, pp. 417-434.
WWW Link. 1106

Coetzee, S.[Serena],
Reference model for a data grid approach to address data in a dynamic SDI,
GeoInfo(16), No. 1, January 2012, pp. 111-129.
WWW Link. 1201
Spatial Data Infrastructure. BibRef

He, Z.W.[Zhen-Wen], Kraak, M.J.[Menno-Jan], Huisman, O.[Otto], Ma, X.G.[Xiao-Gang], Xiao, J.[Jing],
Parallel indexing technique for spatio-temporal data,
PandRS(78), No. 1, April 2013, pp. 116-128.
Elsevier DOI 1304
Spatio-temporal index; Parallel index; R-Tree; Interval BibRef

Wang, S.H.[Shao-Hua], Zhong, E.[Ershun], Li, K.[Kai], Song, G.F.[Guan-Fu], Cai, W.W.[Wen-Wen],
A Novel Dynamic Physical Storage Model for Vehicle Navigation Maps,
IJGI(5), No. 4, 2016, pp. 53.
DOI Link 1604

Breunig, M.[Martin], Kuper, P.V.[Paul V.], Butwilowski, E.[Edgar], Thomsen, A.[Andreas], Jahn, M.[Markus], Dittrich, A.[André], Al-Doori, M.[Mulhim], Golovko, D.[Darya], Menninghaus, M.[Mathias],
The story of DB4GeO: A service-based geo-database architecture to support multi-dimensional data analysis and visualization,
PandRS(117), No. 1, 2016, pp. 187-205.
Elsevier DOI 1605
Spatio-temporal data modelling BibRef

Hallot, P.[Pierre], Billen, R.[Roland],
Enhancing Spatio-Temporal Identity: States of Existence and Presence,
IJGI(5), No. 5, 2016, pp. 62.
DOI Link 1606
Express relations that do not exist at time of analysis. BibRef

Aydin, B.[Berkay], Akkineni, V.[Vijay], Angryk, R.[Rafal],
Mining spatiotemporal co-occurrence patterns in non-relational databases,
GeoInfo(20), No. 4, October 2016, pp. 801-828.
Springer DOI 1610
Subsets of feature types whose instances are frequently co-occurring both in space and time. Expensive to compute. BibRef

McKenney, M.[Mark], Frye, R.[Roger], Benchly, Z.[Zachary], Maughan, L.[Logan],
Operations to support temporal coverage aggregates over moving regions,
GeoInfo(21), No. 2, April 2017, pp. 351-364.
WWW Link. 1702

Galic, Z.[Zdravko], Meškovic, E.[Emir], Osmanovic, D.[Dario],
Distributed processing of big mobility data as spatio-temporal data streams,
GeoInfo(21), No. 2, April 2017, pp. 263-291.
WWW Link. 1702

Laefer, D.F.[Debra F.], Vo, A.V.[Anh-Vu], Bertolotto, M.[Michela],
A spatio-temporal index for aerial full waveform laser scanning data,
PandRS(138), 2018, pp. 232-251.
Elsevier DOI 1804
Aerial laser scanning, Full waveform, LiDAR, Spatial database, Spatio-temporal database, Spatial indexing, Octree, R-tree BibRef

Feng, B.[Bin], Zhu, Q.[Qing], Liu, M.W.[Ming-Wei], Li, Y.[Yun], Zhang, J.X.[Jun-Xiao], Fu, X.[Xiao], Zhou, Y.[Yan], Li, M.[Maosu], He, H.G.[Hua-Gui], Yang, W.J.[Wei-Jun],
An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Gertz, M.[Michael], Renz, M.[Matthias], Zhou, X.F.[Xiao-Fang],
Editorial: Advances in spatial and temporal databases,
GeoInfo(22), No. 4, October 2018, pp. 783-784.
WWW Link. 1811

Cho, H.J.[Hyung-Ju],
Shared Execution Approach to e-Distance Join Queries in Dynamic Road Networks,
IJGI(7), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Hong, Y.K.[You-Kyung], Choi, B.H.[Byung-Hun], Lee, K.[Keumjin], Kim, Y.[Youdan],
Dynamic Robust Sequencing and Scheduling Under Uncertainty for the Point Merge System in Terminal Airspace,
ITS(19), No. 9, September 2018, pp. 2933-2943.
Aircraft, Sequential analysis, Legged locomotion, Robustness, Heuristic algorithms, Uncertainty, Dynamic scheduling, mixed integer linear programming BibRef

Xue, C.J.[Cun-Jin], Wu, C.B.[Cheng-Bin], Liu, J.Y.[Jing-Yi], Su, F.Z.[Fen-Zhen],
A Novel Process-Oriented Graph Storage for Dynamic Geographic Phenomena,
IJGI(8), No. 2, 2019, pp. xx-yy.
DOI Link 1903

Qiang, Y.[Yi], van de Weghe, N.[Nico],
Re-Arranging Space, Time and Scales in GIS: Alternative Models for Multi-Scale Spatio-Temporal Modeling and Analyses,
IJGI(8), No. 2, 2019, pp. xx-yy.
DOI Link 1903

Shi, Z.C.[Zhi-Cheng], Pun-Cheng, L.S.C.[Lilian S.C.],
Spatiotemporal Data Clustering: A Survey of Methods,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link 1903

Qian, C.Y.[Chun-Yao], Yi, C.[Chao], Cheng, C.Q.[Cheng-Qi], Pu, G.L.[Guo-Liang], Wei, X.F.[Xiao-Feng], Zhang, H.C.[Huang-Chuang],
GeoSOT-Based Spatiotemporal Index of Massive Trajectory Data,
IJGI(8), No. 6, 2019, pp. xx-yy.
DOI Link 1908

Li, C.M.[Cheng-Ming], Wu, Z.[Zheng], Wu, P.[Pengda], Zhao, Z.J.[Zhan-Jie],
An Adaptive Construction Method of Hierarchical Spatio-Temporal Index for Vector Data under Peer-to-Peer Networks,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912

Song, W.W.[Wei-Wei], Fang, Y.M.[Yuan-Min], Chen, J.[Jie], Yang, Y.M.[Yong-Ming],
Operational Data Store of Multi-Platform, Multi-Source, Multi-Scale, Multi-Temporal Data Sets,

Zhao, Y.J.[Yi-Jiang], Zhou, X.G.[Xiao-Guang], Li, G.Q.[Guang-Qiang], Xing, H.F.[Han-Fa],
A Spatio-Temporal VGI Model Considering Trust-Related Information,
IJGI(5), No. 2, 2016, pp. 10.
DOI Link 1603

Urner, J.[Jorim], Bucher, D.[Dominik], Yang, J.[Jing], Jonietz, D.[David],
Assessing the Influence of Spatio-Temporal Context for Next Place Prediction using Different Machine Learning Approaches,
IJGI(7), No. 5, 2018, pp. xx-yy.
DOI Link 1806

Robertson, C.[Colin], Horrocks, K.[Kevin],
Spatial Context from Open and Online Processing (SCOOP): Geographic, Temporal, and Thematic Analysis of Online Information Sources,
IJGI(6), No. 7, 2017, pp. xx-yy.
DOI Link 1708

Lei, C.C.[Cheng-Cheng], Zhang, A.[An], Qi, Q.W.[Qing-Wen], Su, H.M.[Hui-Min], Wang, J.H.[Jiang-Hao],
Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Yin, Z.C.[Zhang-Cai], Jin, Z.H.N.[Zhang-Hao-Nan], Ying, S.[Shen], Liu, H.[Hui], Li, S.J.[San-Juan], Xiao, J.Q.A.[Jia-Qi-Ang],
Distance-Decay Effect in Probabilistic Time Geography for Random Encounter,
IJGI(8), No. 4, 2019, pp. xx-yy.
DOI Link 1905
Time issues. BibRef

Feng, M.X.[Ming-Xiang], Shaw, S.L.[Shih-Lung], Fang, Z.X.[Zhi-Xiang], Cheng, H.[Hao],
Relative space-based GIS data model to analyze the group dynamics of moving objects,
PandRS(153), 2019, pp. 74-95.
Elsevier DOI 1906
GIS data model, Relative space, Moving objects, Spatiotemporal analysis, Human dynamics BibRef

Zhu, L.[Lilu], Su, X.L.[Xiao-Lu], Hu, Y.F.[Yan-Feng], Tai, X.Q.[Xian-Qing], Fu, K.[Kun],
A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106

Carré, C.[Cyril], Hamdani, Y.[Younes],
Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link 2104

Guo, S.N.[Sheng-Nan], Xu, J.Q.[Jian-Qiu],
CPRQ: Cost Prediction for Range Queries in Moving Object Databases,
IJGI(10), No. 7, 2021, pp. xx-yy.
DOI Link 2108

Car, N.J.[Nicholas J.], Homburg, T.[Timo],
GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202

Liu, C.[Chun], Chen, L.[Li], Yuan, Q.[Quan], Wu, H.B.[Hang-Bin], Huang, W.[Wei],
Revealing Dynamic Spatial Structures of Urban Mobility Networks and the Underlying Evolutionary Patterns,
IJGI(11), No. 4, 2022, pp. xx-yy.
DOI Link 2205

Xu, D.W.[Dong-Wei], Peng, H.[Hang], Wei, C.C.[Chen-Chen], Shang, X.[Xuetian], Li, H.[Haijian],
Traffic State Data Imputation: An Efficient Generating Method Based on the Graph Aggregator,
ITS(23), No. 8, August 2022, pp. 13084-13093.
Roads, Detectors, Generative adversarial networks, Training, Correlation, Data models, Generators, Traffic data imputation, graph network BibRef

Shi, Y.[Yan], Wang, D.[Da], Ni, Z.H.[Zi-He], Liu, H.M.[Hui-Min], Liu, B.[Baoju], Deng, M.[Min],
A Sequential Pattern Mining Based Approach to Adaptively Detect Anomalous Paths in Floating Vehicle Trajectories,
ITS(23), No. 10, October 2022, pp. 18186-18199.
Trajectory, Roads, Space vehicles, Feature extraction, Directed graphs, Public transportation, Focusing, Anomalous paths, semantic analysis BibRef

Yao, Z.X.[Zhi-Xin], Zhang, J.Q.[Jian-Qin], Li, T.[Taizeng], Ding, Y.[Ying],
A Trajectory Big Data Storage Model Incorporating Partitioning and Spatio-Temporal Multidimensional Hierarchical Organization,
IJGI(11), No. 12, 2022, pp. xx-yy.
DOI Link 2301

Liu, H.[Hong], Yan, J.N.[Ji-Ning], Wang, J.L.[Jin-Lin], Chen, B.[Bo], Chen, M.[Meng], Huang, X.H.[Xiao-Hui],
HGST: A Hilbert-GeoSOT Spatio-Temporal Meshing and Coding Method for Efficient Spatio-Temporal Range Query on Massive Trajectory Data,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link 2303

Sang, N.[Neil],
Does Time Smoothen Space? Implications for Space-Time Representation,
IJGI(12), No. 3, 2023, pp. xx-yy.
DOI Link 2303

García, L.[Luz], Mota, S.[Sonia], Titos, M.[Manuel], Martínez, C.[Carlos], Segura, J.C.[Jose Carlos], Benítez, C.[Carmen],
Fiber Optic Acoustic Sensing to Understand and Affect the Rhythm of the Cities: Proof-of-Concept to Create Data-Driven Urban Mobility Models,
RS(15), No. 13, 2023, pp. 3282.
DOI Link 2307

Semnani, N.M.[N. Mazroob], Breunig, M., Al-Doori, M., Heck, A., Kuper, P., Kutterer, H.,
Towards Intelligent Geo-database Support for Earth System Observation: Improving the Preparation and Analysis of Big Spatio-temporal Raster Data,
DOI Link 2012

Li, J., Liu, J.Q., Mei, X.L., Sun, W.T., Huang, Q., Zhang, Y.Y., Qiao, L.W., Zhang, C.Y.,
Design and Implementation of Trajectory Data Management and Analysis Technology Framework Based on Spatiotemporal Grid Model,
DOI Link 2012

di Martino, F.[Ferdinando], Sessa, S.[Salvatore],
Dynamic Buffer Areas Obtained by EFCM Method in GIS Environment,
Springer DOI 0809

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
GIS: Volunteered Geographic Information, Open Access, Crowd Sourcing, Crowdsource .

Last update:May 6, 2024 at 15:50:14