Spatial-temporal data model and fractal analysis of transportation network in GIS environment

Yongjiu Feng; Xiaohua Tong; Yangdong Li

doi:10.1117/12.812871

5 November 2008 Spatial-temporal data model and fractal analysis of transportation network in GIS environment

Yongjiu Feng, Xiaohua Tong, Yangdong Li

Proceedings Volume 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics; 71443D (2008) https://doi.org/10.1117/12.812871
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

How to organize transportation data characterized by multi-time, multi-scale, multi-resolution and multi-source is one of the fundamental problems of GIS-T development. A spatial-temporal data model for GIS-T is proposed based on Spatial-temporal- Object Model. Transportation network data is systemically managed using dynamic segmentation technologies. And then a spatial-temporal database is built to integrally store geographical data of multi-time for transportation. Based on the spatial-temporal database, functions of spatial analysis of GIS-T are substantively extended. Fractal module is developed to improve the analyzing in intensity, density, structure and connectivity of transportation network based on the validation and evaluation of topologic relation. Integrated fractal with GIS-T strengthens the functions of spatial analysis and enriches the approaches of data mining and knowledge discovery of transportation network. Finally, the feasibility of the model and methods are tested thorough Guangdong Geographical Information Platform for Highway Project.

Citation Download Citation

Yongjiu Feng, Xiaohua Tong, and Yangdong Li "Spatial-temporal data model and fractal analysis of transportation network in GIS environment", Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71443D (5 November 2008); https://doi.org/10.1117/12.812871

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