Sustainable transport planning using GIS and remote sensing: an integrated approach

Marios D. Giorgoudis; Diofantos G. Hadjimitsis; Yoram Shiftan

doi:10.1117/12.2077752

12 August 2014 Sustainable transport planning using GIS and remote sensing: an integrated approach

Marios D. Giorgoudis, Diofantos G. Hadjimitsis, Yoram Shiftan

Proceedings Volume 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014); 92291T (2014) https://doi.org/10.1117/12.2077752
Event: Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 2014, Paphos, Cyprus

Abstract

The main advantage of using GIS is its ability to access and analyze spatially distributed data. The applications of GIS to transportation can be viewed as involving either on data retrieval; data integrator; or data analysis. The use of remote sensing can assist the retrieval of land use changes. Indeed, the integration of GIS and remote sensing will be used to fill the gap in the smart transport planning. A four step research is going to be done in order to try to integrate the usage of GIS and remote sensing to sustainable transport planning. The proposed research will be held in the city of Limassol, Cyprus. The data that are going to be used are data that are going to be collected through questionnaires, and other available data from the Cyprus Public Works Department and from the Remote Sensing Laboratory and Geo-Environment Research Lab of the Cyprus University of Technology. Overall, statistical analysis and market segmentation of data will be done, the land usage will be examined, and a scenario building on mode choice will be held. This paper presents an overview of the methodology that will be adopted.

Citation Download Citation

Marios D. Giorgoudis, Diofantos G. Hadjimitsis, and Yoram Shiftan "Sustainable transport planning using GIS and remote sensing: an integrated approach", Proc. SPIE 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 92291T (12 August 2014); https://doi.org/10.1117/12.2077752

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KEYWORDS

Geographic information systems

Remote sensing

Statistical analysis

Data modeling

Satellites

Systems modeling

Data integration

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