Geographic Information Systems for Intermodal Transportation: Methods, Models, and Applications

By Eunsu Lee

Geographic Information Systems for Intermodal Transportation: Methods, Models, Applications examines the basic concepts and applications of Geographic Information Systems for Transportation. The book discusses the unique characteristics of each transportation mode-- highway, railway, waterway and airway—as well as the combined intermodal transportation network. The book shows how GIS generates vehicle routes and shorted paths, develops transportation demand models, analyzes spatial data, and how three-dimensional modelling is applied to the intermodal transportation.

• Includes real-world case studies from diverse situations
• Provides step-by-steps insights using data to deliver effective outputs for all stakeholders
• Presents models and practices for using GIS techniques to solve intermodal transportation problems
• Includes learnings tools such as chapter objectives, discussion questions and a glossary

• Language: English
• Publisher: Elsevier Science
• Release date: Mar 21, 2023
• ISBN: 9780323901307

Eunsu Lee

EunSu Lee, Associate New Jersey City University, teaches courses at the undergraduate and graduate level in Supply Chain Management, Logistics, Transportation Management, Transportation Systems Modeling, Transportation Planning and Environmental Compliance, and GIS for Transportation. He holds professional certifications in Geographic Information Systems, Certified Production and Inventory Management, and Supply Chain. His articles have appeared in numerous journals including Transportation Research Record: Journal of Transportation Research Board, Journal of Transportation Research Forum, ISPRS International Journal of Geo-Information, and Management Research Review. He is an active member in TRB’s Standing Committee on Visualization in Transportation.

Book preview

9780323901307_FC

Geographic Information Systems for Intermodal Transportation

Methods, Models, and Applications

First Edition

EunSu Lee, Ph.D., CPIM, CSCP, GISP

School of Business, New Jersey City University, Jersey City, NJ, United States

Table of Contents

Cover image

Title page

Copyright

Dedication

Preface

Acknowledgments

Section A: Transportation network and designing database

1: Geographic information systems and intermodal transportation

Abstract

1.1: Introduction

1.2: What is GIS?

1.3: Multimodal and intermodal transportation?

1.4: GIS for transportation (GIS-T)

1.5: GIS for intermodal transportation?

1.6: Summary

1.7: Discussions

References

2: Network representation and network modeling

Abstract

2.1: Introduction

2.2: Learning objectives

2.3: Concept and theory

2.4: Types of graphs

2.5: Network graph

2.6: Graph to network

2.7: Connectivity of road network

2.8: Network representation

2.9: Discussion

References

3: Data modeling and database design

Abstract

3.1: Learning objectives

3.2: Introduction

3.3: Concept and theory

3.4: Data models

3.5: Data modeling

3.6: Summary

3.7: Discussion

References

Section B: Network design and modeling

4: Roads and highways

Abstract

4.1: Introduction

4.2: Learning objectives

4.3: Highway network

4.4: Vehicle characteristics

4.5: Regulation and policy

4.6: Highway network design

4.7: Summary

4.8: Questions and problems

References

5: Railways

Abstract

5.1: Learning objectives

5.2: Introduction

5.3: Railway network characteristics

5.4: Railway network design

5.5: Summary

5.6: Questions and problems

References

6: Waterways

Abstract

6.1: Introduction

6.2: Learning objectives

6.3: Body of water

6.4: Navigable waters

6.5: Harbor

6.6: Waterway network design

6.7: Summary

6.8: Questions and problems

References

7: Skyways

Abstract

7.1: Introduction

7.2: Learning objectives

7.3: Aviation intermodal characteristics

7.4: Airport infrastructure

7.5: Aircraft

7.6: Unit load devices

7.7: Service

7.8: Aviation intermodal route design

7.9: Questions and problems

References

Section C: Intermodal network design and modeling

8: Intermodal network facilities

Abstract

8.1: Learning objectives

8.2: Introduction

8.3: Roads and highway facilities

8.4: Border crossing (point of entry) in North America

8.5: Railway facilities

8.6: Dams and locks

8.7: Summary

8.8: Questions and problems

References

9: Intermodal network design and management

Abstract

9.1: Learning objectives

9.2: Introduction

9.3: Facility types by functions

9.4: Facility types by combination of modes

9.5: Summary

9.6: Questions and problems

References

10: Routing problem

Abstract

10.1: Learning objectives

10.2: Introduction

10.3: Shortest path algorithm

10.4: Maximal flow model

10.5: Vehicle routing problem

10.6: VRP algorithms

10.7: Summary

10.8: Questions and problems

References

11: Mode choice

Abstract

11.1: Learning objectives

11.2: Introduction

11.3: Regression model

11.4: Logit choice model

11.5: Multinomial logit model

11.6: Nested logit model

11.7: Summary

11.8: Questions and problems

References

Section D: Advances in intermodal transportation network

12: Spatial analysis

Abstract

12.1: Learning objectives

12.2: Introduction

12.3: Detour

12.4: Facility location

12.5: Clustering: P-median problem

12.6: Spatial interaction: Gravity model

12.7: Buffer analysis: Service area

12.8: Summary

12.9: Questions and problems

References

13: Trends and Advances

Abstract

13.1: Introduction

13.2: Learning objectives

13.3: Open source

13.4: Emerging data sources

13.5: Big data

13.6: Summary

13.7: Questions and problems

References

Index

Copyright

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Dedication

To Hyun Jung Choi, who sacrificed many nights and weekends for this book to become possible

Preface

GIS has recently become one of the most familiar and useful technologies and software packages for the public due to the popularization of smartphones. Due to the mobility of the public and the growth of e-commerce conducted through smartphones and information technologies, product and customer information and location information are combined to provide companies with valuable data downstream and upstream for marketing and supply chain management through demand forecasting. In addition to the development of information technology, the advancement of Big Data and Analytics is also playing an important role in data-driven decision-making in corporate activities and public institutions by using GIS.

Socially and economically, we are moving further and faster across the globe using more diverse means than in previous times. Complexity and uncertainty of transportation and logistics operations and management also increase from origin to destination, as the travel and freight distances, the assortment of goods and products, and the combination of modes of transport increase. This complexity and uncertainty depend on the political, geographical, cultural, and economic environment. As the scope of supply chains and transport distances increase, various regulations and stakeholders are involved. Thus, traditionally, it has focused on building strong and reliable relationships with a single supplier through a single channel. An optimized approach to using a single supply chain has been disrupted by COVID-19, which has prevented us from replenishing the inventory and scheduling in-time shipments. As a result, consignors, producers, and buyers began to rebuild supply chains by building relationships with multiple suppliers and carriers through multiple channels. This has been exacerbated by the closure of global borders.

To make matters worse, natural disasters such as droughts, fires, floods, and heavy snowfall due to climate changes have unexpectedly disrupted supply and demand. Social, ethical, and cultural differences also play a role in changes in transportation modes, time, and cost. Economically developing or underdeveloped countries may have relatively insufficient infrastructure such as inland highways and railroads, and storage facilities, lacking the capacity to accommodate mega vessels and to facilitate seamless shipping routes.

Given all these political, geographical, cultural, and economic barriers, an integrated system that can collect, store, analyze, and share information for efficient transportation and shipping has become a necessity. GIS as part of this integrated system has become an essential business application to identify and visualize the geographical characteristics of transportation routes, facilities, and regulations to enable accurate and meaningful decision-making.

For students majoring in logistics and transportation or wishing to pursue a future career at a business school and programs or engineering school, I expected a textbook connecting the concept of intermodal transportation and the geographic information system. I have been thinking that it would be nice to have a textbook that helps students understand by hands-on practicing using the information publicly available. Right after their graduation the students can apply their knowledge to practice immediately by learning and practicing the tools along with the knowledge of the analytical tool, data, and concepts of intermodal transportation.

Therefore, this book discusses how to use public data and information from public agencies and utilize geographic information systems to help make decisions about intermodal transportation. The book is not designed to be practical based on a specific package but can be applied to any commercial or open source-based application. Thus, the readers will be able to process and deliver their desired information by changing the input data and transferring it into a geographic information system by understanding the basic concepts.

The book is organized for around a 15-week semester schedule that emphasizes hands-on practice with labs and semester projects. Chapter 1 offers an overview, and Chapters 2–6 can be used for the first half of the semester, with a midterm exam or a review process of projects in Week 7. Then, when students return from spring break, they could work through Chapters 7–13 in Weeks 8–14 and finish their final exam or projects in Week 15. If students need extra time for practice and projects, Chapter 13 can be a shorter discussion than the others.

Acknowledgments

This book project is the interdisciplinary culmination of years of learning, experimenting, and teaching geographic information systems (GIS), including management information systems (MIS) and transportation management systems (TMS), in the field of logistics and transportation. I am grateful to many people who have helped me directly and indirectly, especially Dr. Peter G. Oduor for his guidance and mentorship in encouraging me to explore and dedicate myself to the field of GIS.

I thank the hundreds of undergraduate and graduate students in my face-to-face and online classes for inspiring me and providing me with the feedback I needed to grow. I was fortunate to teach TL 785—Spatial Analysis in Transportation at Upper Great Plains Transportation Institute (UGPTI) of North Dakota State University in Fargo, North Dakota. I extend my special appreciation to Dr. Denver Tolliver, who inspired me and allowed me to teach the master’s course and design and develop a doctoral course, TL 885—Spatial Analysis in Transportation and Logistics. His constant support and encouragement live on in my heart.

Along with my mentors, I thank my research collaborators and coauthors who conducted many GIS projects, provided invaluable insights, and exchanged creative ideas. I also thank my coauthors and graduate advisees from Inha University for the book chapters: Jinmyeong Jang for Chapter 10 (Routing problem) and Sunkyu Kim for Chapter 11 (Mode choice).

I express my special appreciation to the School of Business of New Jersey City University for encouraging me and granting me a sabbatical leave to complete this project. I also thank my colleagues in the Department of Management of New Jersey City University for their support, encouragement, and consideration. The book was made possible by generous research support from Korea University Business School in Seoul, Inha University Asia-Pacific School of Logistics in Incheon, and Korea Maritime Institute in Busan, Korea.

From Elsevier, I thank Brian Romer, who started me on this course and motivated me to go through the challenges, and the team of dedicated professionals, who transformed my thoughts into pages: Omer M. Moosa, Aleksandra Packowska, Kiruthika Govindaraju, and Dinesh Natarajan. Finally, I thank my family members—my parents for their unending patience, encouragement, and love, and my brothers and sisters-in-law for their inspiration and support.

EunSu Lee at Harborside in Jersey City, NJ.

Section A

Transportation network and designing database

1: Geographic information systems and intermodal transportation

Abstract

Geographic information systems (GIS) have permeated our lives and have become an integral part of the business. The GIS is an innovative tool providing visibility of business activities and implementing digitalization. In particular, it is critical for inventory and asset management at places and transportation management delivering customers’ goods and services from one location to another. It provides digitized information in a variety of industrial and public sectors. Therefore, this chapter examines the importance of geographic information systems in the value chain that aims for customer satisfaction while increasing the efficiency of cargo transportation and reducing costs. In particular, the fundamental concepts are discussed, and definitions of the key concepts are explored.

Keywords

GIS; GPS; Intermodal transportation; Multimodal transportation; Geographic information system; Location analytics; Spatial analysis

1.1: Introduction

The satellite-based global positioning systems (GPS) project was started by the US Department of Defense in 1973. In 1978, the US Department of Defense launched Navistar satellites, a satellite-based radio-navigation system. In 1983, a Soviet SU-15 interceptor shot down a Korean passenger airline, Korean Airlines Flight 007 (Boeing KAL007), as it deviated from its planned route from Anchorage to Seoul into Soviet-prohibited airspace due to a navigational mistake by a crew. On September 16, 1983 President Ronald Reagan signed an executive order to open the GPS satellite system to the public to prevent that kind of tragedy [1]. The entire constellation of 24 satellites was in operation as of 1993. The first was Space Vehicle Number 14+, launched by a Delta rocket in 1989 at Cape Canaveral in Florida, USA [2]. Since the Magellan Corporation released GPS on the US market with the first hand-held navigation device, or the Magellan NAV 1000 [3,4], detailed geographic information has been used in various fields (based on data) for personal social media, hobbies, firm’s business, government’s administration, military, and other multiple purposes. The GPS embedded in a vehicle provides the shortest distance to our destination or the fastest way to take into account traffic jams with the help of GPS and navigation systems of GIS. When a member registered at the gym arrives at the door, the sensor automatically detects and records a visit. At the same time, the customer can easily find a geo-fencing system where text introducing a new menu is sent to the customer before passing the restaurant. Fig. 1.1 displays a flight location from the airport of O’Hare in Chicago in the United States to the airport of Incheon in Korea. The airplane’s site is based on latitude, longitude, and altitude collected from GPS devices and satellites.

Fig. 1.1

Fig. 1.1 Location of a flight from the US to Korea. Credit: EunSu Lee.

Geospatial information has been embedded in business information systems. On the contrary, a stand-alone geographic information system is first developed; then, customer relationship management (CRM) or a geographic statistical analysis module is loaded [5]. For example, Khatib and Alami integrated geospatial information systems (GIS) and enterprise resource planning (ERP) by partnering with Esri and SAP [6].

The truck’s location is sent to a customer to share the estimated delivery time or track the parcel’s location. For example, the customers or shippers can trace container ships carrying the shipper’s container. The location of the Ever Given container ship, trapped in the Suez Canal in Egypt in 2021, was informed through the ship tracking system. Satellite photos were also released through media and social media worldwide.

This chapter examines geographic information systems (GIS) and intermodal transportation systems and defines geographic information systems (GIS) for intermodal transportation. Based on this definition, we look at application systems and their use. Detailed and various applications will be investigated in later chapters by modes of transportation. In addition, we will learn about the standards, institutions that lead the rules and guidelines, and related procedures for establishing geospatial information standards.

After completing this chapter, you will be able to explain the definition of geographic information systems. You will be able to discuss the linkage of GIS and intermodal transportation and demonstrate various approaches to using GIS to solve intermodal transportation and supply chain systems.

1.2: What is GIS?

It is sometimes used as an abbreviation for geographic information systems or geographic information science, but abbreviations are used slightly differently to clarify the meaning.

•Geographic Information Systems (GIS)

•Geospatial Information Sciences (GISci)

•Geographic Information Sciences (GISci)

The concept of GIS was conceived in 1962 and developed by Dr. Roger Tomlinson in Canada in the early 1960s for Canada Land Inventory (CLI) [7,8]. The CLI is the first geographic database and technique for managing land use using digitized spatial information. Dr. Tomlinson is known as a father of GIS. He published his doctoral thesis, entitled The application of electronic computing methods and techniques to the storage, compilation, and assessment of mapped data, at the University of London in 1974.

This book focuses on geographic information systems and attempts to demonstrate a practical approach to using computerized systems. GIS can be analyzed by dividing it into three terms: geographic (or geospatial), information, and system. These elements should be integrated with subsystems that collect, store, analyze, and distribute geographic location information using effective electric systems. Geographic location refers to a point, a line, or an area on Earth. The geographic boundary can be expanded to other planets in the Universe.

Percival Lowel published the map of Mars in 1985, and JMARS (Java Mission planning and Analysis for Remote Sensing) was developed by ASU’s Mars Space Flight Facility [9]. In the future, the remote sending analysis can be on Moon, Mars, or other planets. Lunar maps and Interactive GIS Maps of Mars are some of the examples [10–12].

A location is a place where social and economic activity occurs, or an object is placed or exists. This point, line, or area can be named with coordinates for administrative and political reasons. For example, the public is familiar with a landmark or address for communication. Even if this landmark is customary to some citizens, it can be extinguished at any time unless recognized or standardized by public institutions such as organizations or the local, state, and federal agencies. This geographic location, as data, is distributed word of mouth or temporarily without formal procedures. Then, the proper procedure, including collection, storage, and manipulation, may convert to the desired information type or size. Let’s look at geographic, information, and systems.

U.S. Geology Survey, [13] (USGS) defines a geographic information system (GIS) as a computer system that analyzes and displays geographically referenced information. It uses data that is attached to a unique location. Cowen [14] defines a geographic information system as a decision support system (DSS) involving the integration of spatially referenced data in a problem-solving environment [14].

1.2.1: Geographic

Geographic is the study of the distribution of human and natural structures and processes over the earth’s surface and the role of space and place in understanding these human and natural structures and processes [15]. Geographical thoughts commence when it is realized that the different locations have different characteristics due to human and natural variation. Human variations are caused by military, political, cultural, and economic activities, while natural variations are related to geomorphological, climatological, botanical, and other characteristics [15]. In addition to regional geography, the concept of geography evolved with systematic geography, called quantitative revolution, known as statistics, geometry, calculus, information technology, aviation, satellite, and remote sensing.

Geographic, or geospatial, location can be viewed as zero-, first-, second-, and third-dimensional spaces (Fig. 1.2). If you add the time dimension, you can also analyze the quaternary (fourth) dimension. In other words, where economic and social activities occur becomes a zero-dimensional location. Just as this zero-dimensional position has values of the x-axis and y-axis on a plane, the global reference point on Earth is the center of the Earth with 0°. It is expressed as an angle based on the prime meridian or the Royal Astronomical Observatory in Greenwich, England. From the prime meridian, the east is defined as a positive value, and the west is expressed as a negative value. Latitude is a position that represents the angle of how far north or south it is from the equator on the Earth’s surface. Thus, the latitude of 0° is the equator, the north pole point is 90°N (north latitude 90°), and the south pole point is 90°S (south latitude 90°).

Fig. 1.2

Fig. 1.2 Basic geometry presenting locations and places. Credit: EunSu Lee.

This zero-dimensional location is called a point. When a space moves from one fixed place or region to another, the continuous movement of the place where this action occurs is called a line (i.e., link), which is represented in one dimension. In this one-dimensional space, there is distance, and if it is a movement line, there is time and speed of movement. If this continuous line is a logical connection, it carries additional attributes in addition to the attributes of time and distance. For example, it can be said that the trade volume in 2020 was $154.9 billion between the United States and Korea, which was connected by a line to indicate the trade volume and moved through this line [16]. This is called a link, which is a trade lane. This one-dimensional line can be a set of multiple lines connected in a series, called a polyline.

If the occurrence of an event in dimension 0 is extended to a logical and regional space or a logical and physical buffer space is created, this object can be represented in two dimensions. Likewise, a logical space is represented by a one-dimensional line, while a lane is a narrow passage between marks, walls, fences, and other subjects. The space can be used to calculate the area or density of a highway. If physical buffer space is created on the road, it can be expanded to two dimensions and used for spatial analysis. Accordingly, this two-dimensional space may have area and density values.

In summary, places are classified into points, lines, and polygons. The line may have attributes such as length, distance, and traveling speed. The space may have an area and a density value.

Because this geographic data is based on the Earth’s surface, an altitude of Z-value is added to indicate how high or low the sea level or ground level is when expressing and analyzing the actual location of buildings, overpasses, underpasses, railroad bridges, etc. Expressways are also displayed on paper maps or computer screens, but real highways move up and down from the ground and have different altitude values. You may find an example of elevation information on a road with the following steps. It will show the altitude value of a road section in Hershey, Pennsylvania.

•Open https://earth.google.com

•Search US 422 in Hershey, PA

•Hover your mouse over the road to review the elevation at the bottom of the right corner

When the time dimension is added, spatial-temporal information may be expressed by a combination of spatial and temporal data. It includes temporal information regarding transportation assets, logistics operations, and economic and social activities. Fig. 1.3, for example, is a traffic geo-portal system that allows us to check traffic volume information in the state of Washington [17]. This road is Interstate Highway 90 (I-90) coming through Idaho, with a Route ID of 90R129982 and an average daily traffic volume of 2400 vehicles in 2020. Of this traffic volume, single-unit trucks account for 3.69%, double-unit trucks account for 1.48%, and triple-unit trucks account for 0.11%. The traffic data are collected and analyzed annually at the same point. Although the collection location changes depending on the traffic collection method or tool, it is common for traffic volume information to be aggregated and analyzed for each section.

•Object ID: 3201

•Route ID: 090R129982

•2020 AADT: 2400

•Single Unit Truck Percent: 3.69%

•Double Unit Truck Percent: 1.48%

•Triple Unit Truck Percent: 0.11%

•Direction of Travel: Westbound

•Location: On R1 Ramp (SR 90WB to Spokane Br Rd.) after LEFT Intersection SR 90WB

•Shape Point

Fig. 1.3

Fig. 1.3 Traffic information on highways. Credit: EunSu Lee.

1.2.2: Information

GIS is crucial in capturing, storing, checking, and displaying geographically referenced data [18]. Expanded GIS activities include collecting, processing, analyzing, visualizing, and distributing geospatial data and information. Data collection is performed by people or an algorithm set by a developer. This data is stored in the form of raw data in hardware or processed data that can be used directly for analysis. This stored data is distributed without further processing to users who want to refer to the data or is further processed and then stored as information to help decision-makers make decisions. With a combination of information, decision-makers can make timely and appropriate decisions by conveying them with knowledge. It provides wisdom by combining, transmitting, and reprocessing this knowledge (Fig. 1.4).

Fig. 1.4

Fig. 1.4 Steps of developing wisdom using data. Credit: EunSu Lee.

The type and capability of equipment and applications, as well as purpose and user or organization, depends on the type and ability of the collection, storage, processing, and distribution of data. In other words, it depends on the subsystem’s configuration or the management strategy for data processing.

Data is categorized into structured data and unstructured data. Structural data is a form of number, date, and text that can be stored in and queried from a relational database with rows and columns. Unstructured data, on the other hand, cannot be shown as rows and columns in a relational database, such as images, voices, videos, emails, documents, or spreadsheets. Therefore, the structured data type uses less storage space than unstructured data and is easy to manage.

These data might be inaccurate, damaged, duplicated, incomplete, or incorrectly shaped, and the process of fixing them by adding, deleting, or modifying them is called data cleaning [19]. In particular, some fields would be duplicated if an attribute table is not normalized. In case multiple sources are utilized without cleaning, some data would be copied or recorded numerous times. It is to make mistakes in the data collector or errors in the equipment.

Data cleaning is a process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset (Fig. 1.5). When combining multiple data sources, there are many opportunities for data to be duplicated or mislabeled [20]. If data is incorrect, outcomes and algorithms are unreliable, even though they may look correct. There is no absolute way to prescribe the exact steps in the data-cleaning process because the processes will vary from dataset to dataset. But, it is crucial to establish a template for your data-cleaning process so you know you are doing it correctly every time.

Fig. 1.5

Fig. 1.5 Steps for cleaning data. Credit: EunSu Lee.

Unprocessed or processed data can be further processed as needed. Inaccurate data also damages the accuracy of the information generated, which puts a lot of effort into correcting it. This modified, processed data may be transformed into information that can be used for decision-making using statistical analysis or visualization tools and then stored or distributed through a workflow to store, distribute, or generate results. In other words, if you want to reuse the analysis results, you should keep the information securely. If a tool capable of instant analysis can be applied, the stored data should be accessible quickly. The study’s data and output can be distributed to the public or decision-makers. At this time, the information is transmitted through maps, tables, spreadsheets, or infographics.

1.2.3: Systems

A system is a unified whole, with each part structured according to certain principles. A system is a set of things working together as parts of a mechanism or an interconnecting network [21]. The system may include examples of human bodies, tissue systems, galaxies, and computer systems. Thus, a portion of the system refers to a secondary and subordinate system as a minor system present in an extensive system to form subsystems. For example, a computer system is a unified system because the computer communicates with the interaction of subsystems of hardware, software, and communications systems (Fig. 1.6).

Fig. 1.6

Fig. 1.6 Essential components of GIS. Credit: EunSu Lee.

According to Dictionary.com [22] hardware in computer science is the mechanical, magnetic, electronic, and electrical devices comprising a computer system. For example, hardware includes a central processing unit (CPU), random access memory (RAM), storage devices, and other external auxiliary devices. The CPU is the component that processes instructions. It receives input from the computer’s user, operates applications and the operating system, and processes data to provide output. RAM provides the working memory for the computer. The more processes a computer needs to run simultaneously, the more RAM it needs. Operating methods from RAM are much faster than running them from a disk or hard drive. A computer’s storage permits it to store files and data permanently. The hard drive is a standard storage device that varies in capacity. Other external auxiliary devices are the peripheral, a device used to collect, input, store, display, and output information into and out of computer systems. For example, a peripheral device includes a computer mouse, image scanner, digital camera, keyboard, stylus pen, microphone, speaker, printer, monitor, plotter, external hard drive, USB (Universal Serial Bus) drive, etc.

Software [23] is the programs used to direct the operation of a computer, as well as documentation giving instructions on how to use them. For example, the software includes operating systems and applications. Operating systems (OS) are the collection of software that directs a computer’s operations, controlling and scheduling the execution of other programs, and managing storage, input and output, and communication resources. An application program [24] is a program or software used for a particular application such as statistics, simulation, financial trade, marketing, human resource management, voice over Internet protocol (VoIP), geospatial data, etc.

Before the computer came to be in use, a paper-based map or a three-dimensional globe was used for position and space analysis. Projection techniques were used through various mathematical techniques to represent three dimensions of earth surfaces on paper. Converting zero-, one-, two-, or three-dimensional information expressed on a paper into digital information is called digitization. This process requires human judgment and hardware that can store and distribute algorithmic software and data that can process information. Subsystems such as application software and storage devices, scanning devices, and displayers must be well integrated to form a system of integrity. The integrity of the system at this time is to maintain accuracy and consistency to ensure a complete life cycle while meeting the design purpose. The software exports the map to an external output device (i.e., hardware) using mathematical techniques according to built-in algorithms and logical commands. At this time, the external output device is a monitor, printer, plotter, external storage, and built-in storage device. The hardware includes input and output devices, the graphic processing unit, and the communication network.

Hardware runs GIS software. It could be anything from powerful servers, mobile phones, or a personal GIS workstation. The CPU is your workhorse. Dual monitors, extra storage, and crisp graphic processing cards are must-haves too in GIS. ArcGIS and QGIS are the leaders in GIS software. GIS software specializes in spatial analysis by using math in maps. It blends geography with modern technology to measure, quantify, and understand our world.

At this phase, the process of configuring and operating geographic information should employ a scientific research method. This means that spatial data must be collected and converted by scientific methods and analyzed in a scientific approach. Storytelling using popular geographic information in recent years also requires the use of information collected scientifically to prevent distortion of information. Even information collected empirically must be recognized or factually accepted by many people and should be reusable.

1.3: Multimodal and intermodal transportation?

Humans pursue economic and social activities. Transportation becomes necessary as economic and social activities increase in frequency and distance increases. Thus, transportation demand is called derived demand arising to pursue these activities. A vehicle is required in various forms to meet Maslow’s hierarchy of needs. This transportation can be distinguished by passenger transportation for human mobility and freight transportation for shipping products and freight. This book focuses on freight transportation and logistics management with multimodal transportation. This cargo transport can be further distinguished by the land transportation of bicycles, motorcycles, vehicles, etc.; air transportation using skyways; and waterborne transportation, except for using animal and human bodies. In particular, waterways can be divided into inland waterways using fresh water and ocean waterways. The seaways are an essential mode of the long-distance international trade.

The shipping cost of long-haul freight varies depending on the type of cargo, distance and time, contract, and other factors. In particular, the method of transporting the same cargo to its destination through multiple modes of transportation to reduce costs is called multimodal transportation. The products carried at this time may be bulk cargo, general cargo, or special cargo, which can be transported in a specialized package or unpackaged status (Fig. 1.7). In order for unpackaged cargo to take a suitable form for other cargo transport means the volume may be split or debulked (combine or merge) at the time of transfer. For example, tofu beans being exported from North Dakota to Asia can be transported in bulk form to a rail terminal in St. Paul-Minneapolis in Minnesota and then packaged in a 20-ft marine container at the terminal. The container would be shipped to Seattle in Washington by BNSF railway, and then transported by an ocean-going vessel from the Port of Seattle to Busan, Korea.

Fig. 1.7

Fig. 1.7 Coal transshipment from rail to ship using conveyor equipment. Credit: EunSu Lee.

In particular, intermodal transportation is the method of transporting a product or cargo in a standardized container utilizing multimodal transport as if it were a relay to the destination by transferring it from one mode of transportation to another (Fig. 1.8). Therefore, the intermodal transportation method can be said to be a single product (i.e., a container) handling in a single-ordered manner utilizing a multimodal transport method.

Fig. 1.8

Fig. 1.8 Containers being loaded onto a truck by an automated crane in Bayonne, NJ. Credit: EunSu Lee.

Unitized packaging uses a standardized container (box, sack, tote, etc.) to handle larger volume with safety, security, and ease. The advantage of using is that it is able to transport multiple transportation means to the final customer or destination for cost optimization while securing space for transshipment equipment such as forklifts. However, due to the additional time and cost of transshipment, it is necessary to make a decision whether to use a single mode of transportation or a complex one. Take, again, organic tofu beans exported from North Dakota to Asia. A tofu producer (i.e., customer) in Korea purchases non-GMO tofu beans from a farm in Carrington, North Dakota, to produce organic tofu.