Application of 3d Spatio-Temporal Data Modeling, Management, and Analysis in Db4geo

Abstract

ABSTRACT:Many of today´s world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

Efficient and Practical Handling of Spatio-Temporal Data Based on Time-Dependent Net Components

“…The data management model presented in this paper is based on two concepts: the concept of Point Tubes and the concept of Net Components. The Point Tube concept separates the net topology from the vertices of a d-simplicial complex (Breunig et al, 2013a;Kuper et al, 2016;Breunig et al, 2016). These vertices are managed in so-called Point Tubes, a special time dependent data structure.…”

“…Based upon this separation the vertices of a net are managed in a special data structure, the so-called Point Tubes (Rolfs, 2005;Breunig et al, 2013a;Kuper et al, 2016;Breunig et al, 2016). Thus, the movement of these vertices in space is clearly assigned and can be tracked over time.…”

Fuzzy Spatiotemporal Data Modeling Based on UML

“…With the increasing dependence on computers and networks, more and more fields need to be digitized. In the real world, almost every object, event and phenomenon is related to time and space, thus producing a large range of spatiotemporal data [1]- [5]. With the wide use of spatiotemporal data, people need to deal with a large number of spatiotemporal data.…”