Work

Spatial Big Data and Analysis Strategies Supporting Geographic Information System for Transportation (GIS-T) in Conceptual Design, Modelling, and Decision-making: A Review

Year: 2024

Type: article

Abstract: . Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.

Source: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences

DOI: 10.5194/isprs-annals-x-4-2024-461-2024

Authors: Zehua Zhang, Yongze Song

Institution: Curtin University

Language: English

Topic: Geographic Information Systems Studies

Subfield: Geography, Planning and Development

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

Funder: Florida State University