Network-oriented massive spatio-temporal data model and its applications

Renyi Liu; Nan Liu; Weizheng Bao; Yan Zhu

doi:10.1117/12.713211

28 October 2006 Network-oriented massive spatio-temporal data model and its applications

Renyi Liu, Nan Liu, Weizheng Bao, Yan Zhu

Proceedings Volume 6421, Geoinformatics 2006: Geospatial Information Technology; 64211Y (2006) https://doi.org/10.1117/12.713211
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

It is foundation and key of developing GIS platforms of new generation to study the network-oriented massive spatial and spatio-temporal data model. But the research has met many difficulties. The paper combines two models of massive spatial data and spatio-temporal data seemed to be independent to study together in theory and technique. On the base of analyzing the limitations of present geographical spatial data model and spatio-temporal data model, a new model with characteristics of new generation's GIS platform, that is, Feature-Oriented Massive Spatio-temporal Object Tree (FOMSOT) with four-tier architectures is presented. The FOMSOT breaks down the constraint of map layer. It can deal with the massive spatio-temporal data better. The dynamic multi-base state with amendment (DMSA), fast index of base state with amendment in section, storage factors of variable granularity (SFVG) are used in FOMSOT which can manage the massive spatio-temporal data in high efficiency. A prototype "LyranMap" of new generation's GIS platform with the theory and technical method of FOMSOT has been realized, and it has been used in some application systems, for example, the land planning system "LandPlanner", land investigation system "LandExplorer" and land cadastral system "LandReGIS". These verify the correctness and effectiveness of the FOMSOT.

Citation Download Citation

Renyi Liu, Nan Liu, Weizheng Bao, and Yan Zhu "Network-oriented massive spatio-temporal data model and its applications", Proc. SPIE 6421, Geoinformatics 2006: Geospatial Information Technology, 64211Y (28 October 2006); https://doi.org/10.1117/12.713211

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available