GIS-based identification and visualization of multimodal freight transportation catchment areas

Abstract

To estimate impacts, support cost–benefit analyses, and enable project prioritization, it is necessary to identify the area of influence of a transportation infrastructure project. For freight related projects, like ports, state-of-the-practice methods to estimate such areas ignore complex interactions among multimodal supply chains and can be improved by examining the multimodal trips made to and from the facility. While travel demand models estimate multimodal trips, they may not contain robust depictions of water and rail, and do not provide direct observation. Project-specific data including local traffic counts and surveys can be expensive and subjective. This work develops a systematic, objective methodology to identify multimodal “freight-shed” (or “catchment” areas) for a facility from vehicle tracking data and demonstrates application with a case study involving diverse freight port terminals. Observed truck Global Positioning System and maritime Automatic Identification System data are subjected to robust pre-processing algorithms to handle noise, cluster stops, assign data points to the network (map-matching), and address spatial and temporal conflation. The method is applied to 43 port terminals on the Arkansas River to estimate vehicle miles and hours travelled, origin, destination, and pass-through zones, and areas of modal overlap within the catchment areas. Case studies show that the state-of-the-practice 100-mile diameter influence areas include between 15 and 34% of the multimodal freight-shed areas mined from vehicle tracking data, demonstrating that adoption of an arbitrary radial area for different ports would lead to inaccurate estimates of project benefits.

Vulnerability and resilience of the road transport industry in Poland to the COVID-19 pandemic crisis

“…In total, all surveyed enterprises owned 24,975 vehicles, 97.3% of which were equipped with a telematics system (24,304 vehicles). This is in line with the possibility of participation in multimodal transport and the supply chain management rules (see, Asborno et al 2021 ).…”

Image Simulation of Traditional Village Spatial Layout Based on Computer Numerical Analysis

“…It is located in the southeastern part of the hilly area of central and southern Shandong and the southern part of the hilly area of eastern Shandong, the area of mountains and hills accounts for more than 3/5 of the city's area [11], it is a typical mountainous city, the Yimeng Revolutionary Base gave birth to Chinese red culture, Yimeng spirit. With its unique natural environment and historical culture, a traditional village with unique regional characteristics has been nurtured and preserved; it has very high historical and cultural value, architectural value, and social and economic value.…”

A Framework for Investigating the Adoption of Key Technologies: Presentation of the Methodology and Explorative Analysis of Emerging Practices

“…The digital applications category contains software, social networks, and digital tools, accessible from smartphones and browsers, which run on web servers and support paperless activities [54]. Geospatial technologies comprise instruments and tools to collect, process, and analyze geographic data [55]. Immersive environments collect technologies that allow immersion into virtual reality and nonphysical worlds or the employment of virtual instruments to enhance human perception within the real-world environment [56].…”