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A spatial narrative of alternative fueled vehicles in California: a GIS story map
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Content
A Spatial Narrative of Alternative Fueled Vehicles in California:
A GIS Story Map
by
Christina Marie Brunsvold
A Thesis Presented to the
Faculty of the USC Graduate School
University of Southern California
In Partial Fulfillment of the
Requirements for the Degree
Master of Science
(Geographic Information Science and Technology)
August 2019
Copyright © 2019 by Christina Brunsvold
To my patient and loving husband, Larsson, who provided encouragement and support through
this journey.
iv
Table of Contents
List of Figures ............................................................................................................................... vii
List of Tables ................................................................................................................................. ix
Acknowledgements ......................................................................................................................... x
List of Abbreviations ..................................................................................................................... xi
Abstract ........................................................................................................................................ xiii
Chapter 1 Introduction .................................................................................................................. 14
1.1. Motivation .........................................................................................................................17
1.2. Alternative Fueled Vehicles ..............................................................................................18
1.2.1. Hybrid Vehicles .......................................................................................................18
1.2.2. Battery-electric Vehicles ..........................................................................................19
1.2.3. Fuel Cell Electric Vehicles ......................................................................................19
1.2.4. Fossil Fuel Vehicles .................................................................................................19
1.3. Project Overview ..............................................................................................................19
Chapter 2 Background .................................................................................................................. 22
2.1. Similar Web Applications .................................................................................................23
2.2. Importance of Alternative Fueled Vehicles ......................................................................25
2.2.1. Legislation and Mandates for California .................................................................25
2.3. Barriers to Communicating Science to the Public ............................................................26
2.4. Social and Policy Impacts .................................................................................................30
2.5. Cartographic Design .........................................................................................................33
2.6. Web GIS Story Maps ........................................................................................................34
Chapter 3 Design and Development ............................................................................................. 36
3.1. Requirements ....................................................................................................................36
3.1.1. Data Preparation.......................................................................................................38
v
3.1.2. Applications Goals ...................................................................................................39
3.1.3. User requirements ....................................................................................................40
3.1.4. Functional requirements...........................................................................................40
3.1.5. Design Principles and Choices.................................................................................41
3.2. Story Map Creation ...........................................................................................................43
3.2.1. Cascade Template ....................................................................................................44
3.2.2. Development ............................................................................................................46
3.2.3. Data ..........................................................................................................................47
3.3. Intended Users ..................................................................................................................50
3.4. Application Evaluation .....................................................................................................51
3.4.1. Subjects ....................................................................................................................51
3.4.2. Design of survey ......................................................................................................52
3.4.3. Time involved in testing ..........................................................................................54
Chapter 4 Results .......................................................................................................................... 55
4.1. Overview ...........................................................................................................................55
4.2. Maps ..................................................................................................................................55
4.2.1. ZEV 2010 .................................................................................................................55
4.2.2. ZEV 2017 .................................................................................................................56
4.2.3. Heat Map ..................................................................................................................57
4.2.4. EV Charging Stations ..............................................................................................58
4.2.5. Low Income ZEV ....................................................................................................59
4.2.6. DAC ZEV ................................................................................................................60
4.3. Infographics ......................................................................................................................61
4.3.1. Main infographic ......................................................................................................61
4.3.2. Supporting Infographics...........................................................................................63
vi
4.4. Supporting Documentation ...............................................................................................64
4.5. Survey Results ..................................................................................................................65
Chapter 5 Discussion and Conclusion .......................................................................................... 66
5.1. Summary Description .......................................................................................................66
5.2. Challenges in Development ..............................................................................................66
5.3. Limitations of the Project..................................................................................................66
5.4. Future Expansion and Full Deployment of the Application .............................................67
5.5. Conclusion ........................................................................................................................68
References ..................................................................................................................................... 69
Appendix A Story Map ................................................................................................................. 74
Appendix B Survey Results .......................................................................................................... 97
vii
List of Figures
Figure 1 CVRP Rebate Map: Number of Rebates by County ...................................................... 16
Figure 2 Types of Electric Vehicle Technologies ......................................................................... 18
Figure 3 Esri Story Map Cascade template ................................................................................... 21
Figure 4 NOAA Story Maps web page ......................................................................................... 22
Figure 5 Esri An Atlas of Electricity Story Map – Immersive Web Map .................................... 24
Figure 6 Esri An Atlas of Electricity Story Map – Immersive Mixed Media............................... 24
Figure 7 Unnormalized Map of Vacant Houses in the U.S. ......................................................... 28
Figure 8 Normalized Map of Vacant Houses in the U.S. ............................................................. 29
Figure 9 Monmonier’s classic example of how to lie with maps ................................................. 30
Figure 10 Esri Strive for simplicity .............................................................................................. 32
Figure 11 Story Map title page ..................................................................................................... 33
Figure 12 Methodology................................................................................................................. 38
Figure 13 Lutz Oceanic Blue Carbon Immersive Infographic ..................................................... 45
Figure 14 Lutz Oceanic Blue Carbon Infographic with Legend .................................................. 46
Figure 15 Story Map Creation Process ......................................................................................... 47
Figure 16 CalEnviroScreen 3.0 Scoring and Model ..................................................................... 50
Figure 17 ZEV 2010 Immersive Map and Narrative Box ............................................................ 56
Figure 18 ZEV 2017 Immersive Map with Narrative Box ........................................................... 57
Figure 19 Heat Map Slider View .................................................................................................. 58
Figure 20 Electric Vehicle Charging Stations Immersive Map .................................................... 59
Figure 21 ZEV and Income Immersive Map ................................................................................ 60
viii
Figure 22 ZEV 2017 and DAC Immersive Map ........................................................................... 61
Figure 23 Story Map Infographic ................................................................................................. 62
Figure 24 Story Map Infographic Highlighted Area..................................................................... 63
Figure 25 Vehicle Comparison Between 2010 and 2017 ............................................................. 64
Figure 26 Vehicle Manufacturer Fuel Type Infographic .............................................................. 64
Figure 27 Survey Results .............................................................................................................. 65
ix
List of Tables
Table 1. Percentage of electricity generated in 2010 by fuel source in California compared to the
entire US ........................................................................................................................... 25
Table 2. Data Types ...................................................................................................................... 39
Table 3. Potential Survey Form Layout ........................................................................................ 53
x
Acknowledgements
A special thanks my thesis chair, Dr. Jennifer Bernstein, for her guidance and patience through
this process. I would also like to thank my committee members, Dr. Katsuhiko Oda and Dr.
Jennifer Swift for their excellent insight and support. I would also like to thank all of my
professors and staff at USC throughout my graduate program.
xi
List of Abbreviations
AB Assembly Bill
ARB California Air Resources Board
AGOL ArcGIS Online
ARFVTP Alternative and Renewable Fuel and Vehicle Technology Program
BEV Battery electric vehicle
CalEPA California Environmental Protection Agency
CEC California Energy Commission
CPUC California Public Utilities Commission
CVRP Clean Vehicle Rebate Project
DAC Disadvantaged community
DOE Department of Energy
DMV California Department of Motor Vehicles
EV Electric vehicle
FCEV Fuel cell electric vehicle
GIS Geographic information system
GISci Geographic information science
NOAA National Oceanic and Atmospheric Administration
PEV Plug-in electric vehicle
PHEV Plug-in hybrid electric vehicle
PNG Portable Network Graphics
SSI Spatial Sciences Institute
USC University of Southern California
xii
USCB United States Census Bureau
ZEV Zero-emission vehicle
xiii
Abstract
Alternative fueled vehicles are positively shaping the environment, emissions, and social
perceptions of vehicles. Several pieces of legislation and mandates have been passed in
California to guide the state towards positive climate impact goals. Assembly Bill 118 and
Executive Order B-16-2012 are notable pieces of legislation passed within the last decade that
are driving California towards five million zero-emission vehicles by 2030. While these goals are
aspirational, several state agencies have collaborated to create programs to accomplish this goal,
including the Alternative and Renewable Fuel and Vehicle Technology Program. The California
Energy Commission (CEC) has been tasked with implementing this program and releasing an
annual Transportation Energy Demand Forecast. This report includes multiple charts and
datasets, but no maps or visualizations to facilitate the public’s understanding as to the progress
of said goals or the ability to achieve the interim 1.5 million zero-emission vehicles by the 2025
target. Research has shown that maps enable data to be better understood by both professionals
and the general public. The primary goal of this thesis was to create a Web GIS Story Map that
visualizes the progress towards meeting California’s alternatively fueled vehicle goals as a
means of demonstrating the viability of Story Maps as a communication approach. The Story
Map includes geographic representations of alternative fueled vehicles, spatial analysis of the
demographic and economic adoptions throughout the state, and immersive multimedia to
facilitate exploration of the alternative fueled vehicle program. This study evaluated the degree
to which internal staff determined the Story Map useful versus approaches that are more
traditional. Preliminary responses from internal staff showed that the Story Map was well
organized and intuitive. This pilot project serves as a flagship Story Map that can be expanded
upon and published by the CEC for the general public review in the near future.
14
Chapter 1 Introduction
California leads the nation in reducing greenhouse gases (GHG) in part by increasing the number
of alternative fuel vehicles. Since transportation related energy is the single largest source of the
state’s GHG emissions, state mandates and legislation have been passed to reduce GHG levels
(California Energy Commission 2018b). In 2007, Assembly Bill 118 created the Alternative and
Renewable Fuel and Vehicle Technology Program, which authorized the California Energy
Commission (CEC) to develop and deploy alternative fueled vehicles to help attain the state’s
climate change goals. In 2012, Governor Brown issued executive order B-16-2012 to set a goal
of 1.5 million zero-emission vehicles (ZEV) in California by 2025 (California Executive Order
B-16-2012 2012). Since then, several mandates, incentives, and legislative bills have been passed
increasing the use of ZEVs to reduce GHG emissions.
In an effort to facilitate public engagement with the progress towards these state
mandates and goals, the CEC is tasked with reporting the trends and forecasts for transportation
energy. Currently, this process is done through a Transportation Energy Demand Forecast and
Revised Transportation Energy Demand Forecast, which is adopted on a sliding biannual scale
through 2030. The 2017 report was revised for 2018 and adopted as the Revised Transportation
Energy Demand Forecast, 2018-2030. While the report discusses economic and demographic
data, there are no maps in the report (California Energy Commission 2018b). This is problematic
because it has been shown that people can draw conclusions more effectively through maps
rather than static tables of data (Paul 2018).
By displaying the number of vehicles registered since 2010, this project initiated a
dialogue between the transportation staff and other CEC staff and management through a Story
Map. This thesis created a smaller pilot project Story Map to allow internal CEC staff to view
15
and test the Story Map for layout, content, and ease of use, while the future goal is to create a
public-facing Web GIS Story Map. The Esri Story Map templates and designs for the creation of
this project’s Story Map were used because the interface allows for seamless integration with
ArcGIS software and web-based display. Spatial analysis of the correlation between successful
areas and the increase in a number of alternative fueled vehicles were performed to understand
geographic regions that are adapting to registering more electric vehicles per population.
While the state goal is important, it is equally important to evaluate how each county is
progressing and determine if there are gaps or areas of concern throughout the state. For
example, according to the California Air Resources Board, there are no alternative fueled vehicle
rebates claimed for Modoc County, as shown in Figure 1, which would imply that an entire
county is not participating in the goal to a greener California (Center for Sustainable Energy
2018b). This statistic may not be completely accurate since there are other eligibility criteria for
vehicle rebates. Due to these statistical complications, it is important to determine how the
counties within the state are progressing towards the mandates as well as the correlations
between the demographic and socioeconomic levels across the state.
16
Figure 1 CVRP Rebate Map: Number of Rebates by County (Center for Sustainability, 2018b)
This project uses alternative fueled vehicle data to display the progress towards the state
mandates and goals for alternative fueled vehicles between 2010 and 2017. This thesis lays the
foundation to create a Story Map that includes the legislative history, programs, and major events
that constitute the alternative fueled vehicles programs in California. The Story Map includes the
incentives, pricing levels, car manufacturer changes, and successes and failures of the programs.
This project utilizes data from the CEC, California Department of Motor Vehicles, United States
Census Bureau, California Department of Finance, and other sources as needed. The second
phase of this project will include enhancements to the Story Map and vetting by management
17
before publishing this Web GIS Story Map to the public. The Story Map enhancements can be
implemented to allow the general public to identify the progress towards the state mandates and
goals, determine if any geographical barriers exist, and visualize the future trends that are
identified in the transportation forecasts.
1.1. Motivation
As with most state agencies, information is shared with the public after rigorous reporting
and data collection, analysis, findings, vetting, and finally a public adoption. By the time most
reports are adopted, the data is at least six months old if not more. The status is no longer a real-
time notification and instead is an archive of the degree of success. Reports are often adopted
with confusing titles, dates, and minimal graphics or visualizations that baffle laypersons. Joint
agency programs can lead to outdated or incorrect websites. GIS can add clarity with maps and
visuals that inform the public without obscuring the data. This Web GIS Story Map is intended
to be understandable, contain a simple and effective format, and maintain the attention of the
user through interactive maps and visual graphics.
The California Energy Commission publishes a transportation forecast report biannually
that describes the trends of vehicles, the forecast for the next ten years, and summarizes the
previous years’ datasets. While this is done biannually, the data is often a year old since it covers
the previous complete year and requires time to perform the analysis, and is displayed in charts
and tables that are unclear to the user as to their importance. By complementing this strategic
report with a Web GIS Story Map that guides the user through data via maps, charts, and visual
displays, the user can gain an understanding of the data within a spatial context. Visualization
tools like maps are important mechanisms to inform the public on where things happen. In fact,
the earliest cartographic maps were actually “story” maps (Paul 2018). To date, the California
18
Energy Commission has no Story Maps published, yet publishes over five reports a year that
contain vast amounts of spatial data (CEC 2018a).
1.2. Alternative Fueled Vehicles
Alternative fueled vehicles have been widely called hybrid vehicles. The three main
alternative fueled vehicles studied for this thesis are hybrid, battery-electric, fuel cell electric,
and fossil fuel. The definitions of each vehicle fuel type are listed below as specified in the
Transportation Energy Demand Forecast. In addition, the category “zero-emission vehicle” or
ZEV refers to any vehicle that produces zero tailpipe emissions during operation (CEC 2018b).
Figure 2 Types of Electric Vehicle Technologies (CEC 2018b)
1.2.1. Hybrid Vehicles
A hybrid vehicle uses more than one type of energy and is typically a combination of
fossil fuel and electric engine and a battery. The determination of a hybrid versus a plug-in
hybrid electric is based on the battery charging. For this thesis, the term hybrid includes hybrid
vehicles and plug-in hybrid electric vehicles (PHEV). The more well-known hybrids are
Chevrolet Volt, Ford’s C-MAX and Fusion Energi, and Toyota Prius, although there are several
new models that have been released since 2016. In the dataset, these are labeled “PHEV.”
19
1.2.2. Battery-electric Vehicles
A battery-electric vehicle (BEV) contains an electric motor and is solely powered by
batteries. The more well-known BEVs are BMW i3, Chevrolet Spark EV, Ford Focus Electric,
Nissan LEAF, smart, and Tesla Model S; however, there are several other models available. In
the dataset, these are labeled “Electric.”
1.2.3. Fuel Cell Electric Vehicles
A hydrogen fuel cell electric vehicle (FCEV) contains a fuel cell, electric motor, and a
battery. The determination of a FCEV versus a plug-in hybrid fuel cell vehicle (PHFCV) is based
on the battery charging. For this thesis, the term fuel cell vehicles includes FCEV and PHFCV.
For example, the Honda Clarity Fuel Cell, Hyundai Tucson Fuel Cell, or Toyota Mirai Fuel Cell
vehicles. In the dataset, these are labeled “Hydrogen.”
1.2.4. Fossil Fuel Vehicles
A fossil fuel vehicle is primarily an internal combustion engine that uses a variety of
fossil-based fuels such as gasoline, diesel, natural gas, propane, and flex-fuel. Flex-fuel vehicles
refer to a subset of gasoline blended fuel sources. For this thesis, the term fossil fuel includes all
fossil fuel based fuel sources above and those that are not considered hybrid, BEV, or fuel cell.
1.3. Project Overview
This thesis created a pilot project for internal CEC staff to test a user-friendly Web GIS
Story Map that bridges the gap between bureaucratic reporting and public transparency. Story
Maps are a web-based application that can be updated with new data easily and has viewership
information like most other websites and social media platforms. The simplicity of the design
coupled with the considerable amount of information that can be displayed was key in choosing
20
this format for communication. This project illustrates a story for the public as to how far
California has come in reaching California’s goals without the overly bureaucratic reports that
readers bypass. Although the initial project is a small pilot project for internal CEC staff to use,
the ultimate goal is to create a foundation to shape the process, creation, and deployment of Web
GIS Story Maps for the future.
While there are many Esri Story Map templates, for this project the Cascade Story Map
template was used to guide the user through the story and provide minimal distraction from
required mouse-clicks or links that take the user away from the page. This template, as shown in
Figure 3, uses full-page graphics and immersive sections. The immersive sections are full-page
maps and infographics that click into place allowing the user to see the comment box narratives
and view the entire map for the page as they continue to scroll. Additional information is
embedded within the Story Map to provide context to the user, however the links offer
supplemental data that is not required to understand the material contained within the Story Map.
Several web maps were created in ArcGIS Online and used in the Story Map to create the
immersive sections. Additional visualizations including infographics, charts, and mixed media
were used to draw in the user and tie the narrative together. This process was done with the Esri
Story Map template builder.
21
Figure 3 Esri Story Map Cascade template (Esri 2018b)
At the end of this thesis, the goal is to educate CEC staff on the effectiveness of
conveying information to inform the public on the progress and future of alternative fueled
vehicles in California in a Web GIS Story Map pilot project. CEC staff were asked to complete a
survey about their experience viewing the Story Map, ease of use, comfort level while using the
Story Map, and overall effectiveness to use the Story Map as an additive piece to supplement the
transportation forecast report. As a method of viewership, the CEC tracks hits, likes, and views
to determine user interaction.
22
Chapter 2 Background
Cartography has been used for years to describe places. Cartography and GIS are also used in
everyday life. Cartography and GIS should be used by public agencies to share valuable
geospatial data with their customers – the public. Maps help create engagement with the public
and provides visualizations that are more useful to convey information geographically (Paul
2018). While some federal public agencies are utilizing Esri Story Maps, most state agencies in
California are not. The National Oceanic and Atmospheric Administration (NOAA), National
Park Service, and U.S. Department of Agriculture have used Story Maps to display various
themes and topics and educate the public on their projects. NOAA has several Story Maps in
their gallery as shown below that illustrate the complexities of spatial data topics in an eloquent
format that is easy to understand (NOAA 2018). Story Maps are an effective way to
communicate with the public and should be used more widely by public agencies (Esri 2018c).
Figure 4 NOAA Story Maps web page (NOAA 2018)
23
2.1. Similar Web Applications
With the abundance of data the CEC collects, coupled with the vast amount of public data
available, spatial data visualizations should be included in reports at a minimum. As Paul 2018
states, a static table tells us there is a problem, but not where. Adding supplemental maps inform
the public on where things are happening, where the vehicles are located, where charging
stations are, and where incentives are offered. Cartographic maps can also point out areas with
higher concentrations that may not be visible in a table (Paul 2018). In the previous
transportation report, only one map was provided, however, there were over thirty charts of data,
and the sole map was not published by the CEC, it was added from the California High-Speed
Rail Authority. This volume of information can be confusing to readers and should be displayed
on maps that allow the reader to draw context to the datasets. GIS has the power to unite people
through cartographic maps and web applications (Esri 2017a).
A Web GIS Story Map published by Esri tells the story of electricity in the United States.
While this was not published by a government entity, it could be used as a framework and
published by the CEC as an introduction to the state’s electricity infrastructure, renewable energy
goals and progress, and energy consumption. This example would be highly relevant to introduce
the public to the purpose of the CEC, display information, and guide the user through the story.
The immersive sections highlight the story, draw in the user to the interactive maps, and create
powerful messages with the mixed media as shown below in Figure 5 and Figure 6 (Thomas
2012).
24
Figure 5 Esri An Atlas of Electricity Story Map – Immersive Web Map (Thomas 2012)
Figure 6 Esri An Atlas of Electricity Story Map – Immersive Mixed Media (Thomas 2012)
To date, the CEC does not have a Web GIS Story Map, and GIS is still in its infancy.
Since this is the first Web GIS Story Map created for the CEC, this is aimed at a pilot project to
engage staff with the concepts and visuals that are possible with a Web GIS Story Map and to
25
gain traction from upper management on the process involved. As a state agency, the materials
published on behalf of the CEC must meet certain requirements by the media and executive
offices to establish the correct message and narrative of each item. This Web GIS Story Map
introduces the internal staff to the layout, maps, legends, and narratives that can be utilized to
accompany staff reports that are adopted across the commission.
2.2. Importance of Alternative Fueled Vehicles
GHG emissions are less in some parts of the United States, with California having a
significantly lower amount than the rest of the United States in 2010 as shown in Table 1 below
(Thomas 2012). However, even if all of the small-sized vehicles were replaced with battery
electric vehicles, it would not be enough to reach the 1990 GHG levels as desired since the
energy for charging the vehicles primarily comes from fossil fuel dependent power plants.
Table 1. Percentage of electricity generated in 2010 by fuel source in California compared to the
entire US
Fuel Source California United States
Coal 8.1 % 46.2 %
Oil 0.0 % 1.0 %
Natural Gas 41.0 % 20.3 %
Total Fossil Fuels 49.1 % 67.5 %
Nuclear 23.1 % 20.3 %
Renewables 28.0 % 9.4 %
Source: Thomas 2012
2.2.1. Legislation and Mandates for California
There are two main legislative pieces that drive the implementation of alternative fueled
vehicles: Assembly Bill 118 and Executive Order B-16-2012.
Assembly Bill 118 (AB 118) was approved in 2007 and created the Alternative and
Renewable Fuel and Vehicle Technology Program (ARFVTP) to be administered by the
California Energy Commission. Under this bill, the CEC was required to establish and
26
implement programs to reach the goal of reducing greenhouse gas emissions to 1990 levels by
2020. In addition, several programs and fees were established to support the reduction of
transportation-related greenhouse gas emissions.
Executive Order B-16-2012 was signed in 2012 and requires several state agencies to
work together to set benchmarks, goals, and programs in order to reach different goals for 2015,
2020, 2025, and 2050. By 2015, the California Air Resources Board (ARB), California Energy
Commission (CEC), and California Public Utilities Commission (CPUC) are required to
establish benchmarks to support metropolitan infrastructure, expand the manufacturing sector,
and contribute to academic institutions’ research to support zero-emission vehicles (ZEV). By
2020, the state infrastructure must support one million (ZEV), the cost of a ZEV must be
competitive with conventional vehicles and widely available to consumers, public transportation
must include ZEV, and the electric grid must support electric vehicle charging stations. By 2025,
ZEV infrastructure will be provided for easy access and over 1.5 million ZEV will be on the
roads. By 2050, the greenhouse gas emissions from the transportation sector will have eighty
percent fewer emissions than 1990 levels. In addition, fleet purchased vehicles must rapidly
increase to meet targets of ten percent by 2015 and twenty-five percent by 2020. Executive Order
B-48-18 was signed in 2018 to increase the number of ZEVs to 5 million by 2030.
2.3. Barriers to Communicating Science to the Public
Communicating science to the public is a difficult task that requires the author to
understand the intended audience. Displaying data accurately and correctly to direct the narrative
of a story is one way GIScientists are using maps to communicate more effectively.
With the rate that electric vehicles are entering the market in California, the progress
towards the state mandates should be known, however this number is unclear to most people.
27
Depending on when the information was posted and where the source of the information came
from, the estimates are between 200,000 and over 400,000 ZEVs registered in California. The
ARB released a fact sheet in 2018 stating since 2010, over 400,000 ZEV and plug-in hybrids
have been registered in California, Next 10 stated in 2018 that by October 2017, 337,483 ZEVs
have been sold in California, and the Union of Concerned Scientists stated in 2016 that more
than 200,000 EVs had been sold in California to date (ARB 2018; Perry 2018; Reichmuth 2016).
Each statement is different from the next, grouping ZEV and plug-in hybrids, only electric
vehicles (EV), and ranging from 2015 statistics to 2017. This information is misleading to the
public, and while all of these facts may have been correct at that time, it is confusing to know
what is the most current information and the current progress on these goals.
While San Francisco and Los Angeles appear to be leaders for vehicle rebates, the
population numbers are not factored into these accounts and are causing a disproportionate
outcome for the rest of the state as seen in Figure 1 above (Center for Sustainable Energy
2018b). A map can contain correct and true data while falsely implying a narrative (Monmonier
1998). Clearly, communicating normalized data to the public must be done, and while it is
difficult, with the assistance of GIS, this can be accomplished.
Creating an apples-to-apples comparison by normalizing the data onto a level platform,
like population, allows the user to understand the value of vehicles per population rather than the
overall number. It would not be surprising to see a higher number of vehicles in a highly
populated place. However, a higher number of vehicles per population would be important to
recognize and determine why the increased values exist. A classic example of this is vacant
housing versus vacant housing per people. One would expect vacant houses around populated
28
areas; however, a map showing vacant houses per population is more valuable and shows a
different picture as seen below in Figure 7 and Figure 8 (Robinson 2019).
Figure 7 Unnormalized Map of Vacant Houses in the U.S. (Robinson 2019)
29
Figure 8 Normalized Map of Vacant Houses in the U.S. (Robinson 2019)
In addition, the statistical variations for data can also skew the overall narrative for the
dataset as shown in Figure 9 below. The crude birth rate dataset is the same for each subfigure
below however depending on the statistical data groupings the message is different. These
statistical breaks are traditionally natural breaks, equal interval, and quantile. As shown below,
the differences between the equal interval and quantile figures are drastically different and can
swag the message while still using accurate data (Monmonier 1998). Using these communication
techniques, maps can be used as an effective tool to inform the public about confusing datasets in
a more logical format.
30
Figure 9 Monmonier’s classic example of how to lie with maps (Monmonier 1998)
2.4. Social and Policy Impacts
In addition to biased datasets, social and policy impacts are designing the future for
alternative fueled vehicles in the state. With aggressive statewide goals, some counties are being
left behind due to non-connected roadways and disadvantaged communities. Non-connected
roadways occur when the availability to charge an electric vehicle is too far away from the
residence or workplace, leading to the inability to charge the vehicle. Disadvantaged
31
communities often have lower income levels and face broader environmental and socioeconomic
burdens like poverty, low birth weights, and lower education levels (CalEPA 2018). Several
vehicle rebates are only offered for incomes less than $150,000 gross annually, however an
additional rebate is offered to those within 300 percent of the federal poverty level at the time of
purchase (Center for Sustainable Energy, 2018). Due to this distinction, it is important to
determine if there is an increase in the number of vehicles in low-income areas and
disadvantaged communities. Additionally, electric vehicles are becoming a status symbol as the
middle class tries to keep up with the Joneses’ (Axsen and Kurani 2013, Gordon-Bloomfied
2015) and consumer choice is driving car manufacturers towards greener cars. While the Toyota
Prius has been around since 2000, Tesla was introduced in 2008 and is seen as a luxury car in
comparison (Woody 2013). While the social constructs are beyond the scope of this project, it is
important to keep in mind the additional factors beyond the income and price points of the
vehicles. Even though most consumers are conscientious of the environmental impacts of driving
(Breetz 2018), it may not be feasible to own an electric vehicle without a rebate, as forty-six
percent of surveyors implied to the Center for Sustainability’s question: “Would you have
purchased or leased your PEV without the rebate?”
The trend for “green” vehicles and the environmental impacts are gaining support since
the initial Prius hit the street, and scientists are gathering data to determine how well these
alternative fueled vehicles are helping reduce greenhouse gas emissions (Thomas 2012).
Although the goal is to add more alternative fueled vehicles to reduce greenhouse gas emissions,
the effects may take years to fully understand. However, removing fossil-fueled vehicles from
the road and replacing them with zero-emission is a step toward the greener future for California
(CEC 2018b).
32
Nisbet (2009) discusses the two Americas of climate perceptions where one half is
engaged and involved, and the other questions the ideology of climate change. Purchasing an
electric vehicle has become a decision based on two trends; purchase an electric vehicle in order
to address climate change and the other to purchase a status symbol. As with all policy issues,
communication is key and can be used to frame an issue like a storyline. Since audiences rely on
the framework to guide the issue, a Web GIS Story Map can be used in a similar fashion to guide
the user to the policy issues and solutions (Nisbet 2009). Esri describes the best policy for
readability and the attention span of users is simplicity. A user should be able to gather all of the
necessary information in the current or next step rather than six steps later as the user will lose
interest and the Story Map will not be as effective as shown in Figure 10 below (Esri 2018c).
Figure 10 Esri Strive for simplicity (Esri 2018c)
Following Nisbet (2009) and Esri’s recommendations, a catchy title and graphic displays
must be used to engage the user to start the journey and continue along the pathway to the final
destination. A title The Transportation Outlook for the Suitability of the Alternative Fueled
Vehicles in California introduces a layer of confusion and boredom whereas Driving California
to a Greener Future provides more context and vision. Both titles were considered for this Story
33
Map, however, after identifying the audience and conducting a short poll, it was determined the
first was too similar to the transportation report that is not widely read outside of the primary
stakeholders and partnering state agencies. The second title allows the user to feel involved with
the change and part of the solution, which would reframe the perception to the user. Additional
comments for the title poll were “too long, didn’t read,” “I stopped reading after Outlook,” and
“I want to read the shorter one.” As shown in Figure 11 below, the immersive title section for the
Cascade template draws in the user to the story.
Figure 11 Story Map title page
2.5. Cartographic Design
Cartographic design techniques are important to provide context to map-readers and
inform on the subject. Simple map characteristics like colors can play a big role in map
perception. For example, the color red is often associated with crime and danger, so using red to
associate a topic could introduce unwanted feelings and bias from the map-reader (Slocum
34
2009). Additional color schemes relating to color-blind people must be used to ensure that all
map viewers can view and understand the maps without missing important color changes.
Symbology in maps can also provide context and distract the map-reader depending on
the amount of detail contained on the map. While maps require minimal information to provide
context like cities or counties, additional data can be distracting and deter the user from the
original intent of the map. This cluttered information is called map noise and should be avoided.
To avoid map noise, several maps in a series can be used to provide context and information to
the map-reader without cluttering individual maps. In addition, web maps that incorporate
symbology at different map scales allow the map-reader to view information necessary at that
scale (Esri 2017a).
Static maps are also different from web maps as the map elements are no longer fixed
within a single page. Map elements like labels, legends, scale, and pop-up boxes change the
layout of the available space and alter the frame for users. Additionally, new hierarchies exist for
web maps and fluid map layouts provide additional communication tools and parameters for
creating web maps. The zoom level interface creates additional space on the page where labels
and symbology can be applied at different zoom levels and allow more detailed information with
less map noise (Muehlenhaus 2014).
2.6. Web GIS Story Maps
Esri Story Maps have been used to communicate policy with constituents through
embedded maps and galleries on websites. A Web GIS Story Map, or simply a Story Map,
combines illustrative maps with rich narrative and multi-media to engage the user into the story
being told. Through the Five Principles of Effective Storytelling, a map or web application
35
creator can harness the power of GIS to inform the public and stakeholders about policy issues
(Esri 2018c).
With digital cartographic maps, the map-reader is now empowered with control over a
map (Roth 2015). The Web GIS Story Map enables the map-reader to zoom in and out, focus on
different areas, and dive into the narrative within the story. These Story Maps are a useful way to
communicate data to the map user over geographical areas with a greater understanding. The
public is most comfortable in their own geographical extent, understanding the roads, parks,
schools, et cetera within their community. A statistic from a neighboring community might be
understood, whereas a statistic from an unknown community may not. Enabling the map-reader
to gain a glimpse of an understanding about these communities and cities provides geographical
context to datasets that assist the map-reader to gain a better understanding (Esri 2017a).
36
Chapter 3 Design and Development
This chapter describes the process of creating the pilot project Web GIS Story Map and the
required spatial analysis and datasets. An initial review of the datasets determined the granularity
that was used to display each dataset and spatial extent of the maps. Once the data was obtained,
the datasets were analyzed spatially to determine any spatial correlations among the different
indicators. This analysis was performed at the census level to determine if there are additional
areas that should be disaggregated and evaluated. While the project aimed to capture the overall
statewide progress towards the state mandates, the interdependencies of each census tract and
county were evaluated to determine equitable adoption within the counties. The general process
for obtaining and preparing the data is described in Figure 12 below.
3.1. Requirements
The Web GIS Story Map was created in ArcGIS Pro and ArcGIS Online and published
on the CEC ArcGIS Online server.
To create a Web GIS Story Map that displays the spatial data and correlations among
demographic and socioeconomic factors, several datasets were required. The primary dataset was
the vehicle registrations for the state of California, which was provided by the California
Department of Motor Vehicles (DMV) via the CEC. This dataset was “scrubbed” and partially
processed for accuracy by CEC staff and includes the make, model, model year, fuel type, and
vehicle registration address. Due to the large size of the dataset, it was obtained in a SAS format
and needed to be integrated into ArcGIS. The dataset was geocoded to add the latitude and
longitude to each address in the file. The secondary datasets to analyze included demographic,
economic, and disadvantaged community areas. The demographic and economic datasets
contained the population and income levels for the state of California per county and census
37
tract. This dataset was provided by the US Census Bureau (USCB) and is downloaded annually.
Once the datasets were converted to a spatial format, the evaluation of census level and county
level aggregation were explored, and the findings determined that the granular data comparisons
would be performed at the census tract level and the overall vehicle counts would be displayed at
the county level. The disadvantaged community areas (DAC) are defined by the
CalEnviroScreen3.0 from Senate Bill 535, which rates the census tracts amongst 20
environmental and socioeconomic factors (CalEPA 2018). A DAC is described as a census tract
within the top 25% or top 10% of these barriers and is currently being evaluated by many state
agencies for equitable program success due to Senate Bill 350 (CPUC 2018). Due to the
increased attention to disadvantaged communities, management requested an analysis layer in
the Story Map showing the correlation between DAC and ZEV locations. More information
about the DAC areas can be found in 3.2.3.4 Disadvantaged Communities (DAC).
Supplemental datasets used to create detailed maps were the alternative fueled vehicle
charging stations and fuel pumps, incentive-based data, and car manufacturer model price points
for vehicles. The charging station dataset contains the locations of the different charging stations
across the state of California. This includes electric vehicle charging stations, connector types
and project status. This dataset is available for download from the Department of Energy. The
incentive-based data includes the available monetary incentives as well as customer-based
incentives offered by local utilities. The monetary incentives are determined by the vehicle
model and are available from the Clean Vehicle Rebate Project. The customer-based incentives
vary and are currently being researched, however, the Sacramento Municipal Utility District has
one program listed, and similar programs are being researched for other utilities within the state.
38
The car manufacturer model price points dataset was researched and determined to be
incomplete for this project.
Figure 12 Methodology
3.1.1. Data Preparation
Data obtained was prepared as spatial datasets in ArcGIS Pro. The datasets were
converted to GIS tables, joined with existing spatial datasets, and geoprocessed to complete
39
analysis necessary before map creation. Once the data was prepared, the datasets were shared as
web layers and tile layers to ArcGIS Online (AGOL) as content. These datasets were used to
create the various maps necessary in the Story Map.
For the Web GIS Story Map, there will be several web maps created by the various
datasets. Due to the specific nature of the project, some maps will be fully immersive and
interactive while others will be cast images of the maps. The intended datasets listed in Table 2
were used for these maps, infographics, and charts.
Table 2. Data Types
Data Data Type Source Format
California DMV vehicle stock
database
Spatial
*
California DMV via CEC .csv
Shapefile*
Household Income Spatial US Census Bureau Shapefile
Population Spatial US Census Bureau Shapefile
Disadvantaged Communities
+
Spatial CalEnviroScreen 3.0 Shapefile
Alternative Fuel Charging
Stations
Spatial Department of Energy Shapefile
Note:
*
The DMV Dataset was geocoded to create the main spatial dataset.
+
Disadvantaged communities are defined by CalEnviroScreen 3.0, specifically in relation
to Senate Bill 535.
3.1.2. Applications Goals
The goal of the project is twofold; first to pilot the creation of a Web GIS Story Map that
can be expanded upon for future work and secondly to create an expanded public-facing Web
GIS Story Map. This pilot will document the process to plan, develop, build, and display a Story
Map. While several decisions have already been made, including the topic, datasets, level of
granularity and enumeration unit, and Story Map template, there are several decisions that will
be made with CEC staff to complete the Story Map. In order to facilitate these discussions, the
pilot project will demonstrate the flow of the Story Map, the integration of mixed media, and the
incorporation of immersive maps and legends. After the general understanding and presentation
40
of the Story Map, discussions with CEC staff to expand the pilot into a public-facing Web GIS
Story Map will begin and include discussions about the overall narrative portrayed, additional
messages and maps, specific details and areas to highlight or focus on, and on-going
maintenance and updates to the Story Map. Due to the robust review process, these discussions
and implementation may take months to craft.
3.1.3. User requirements
For the purposes of this thesis project, the users were internal CEC staff. The staff also
functioned as the application test subject. Internal CEC staff will take a short survey after they
have viewed the Story Map to provide feedback on the usefulness, ease of layout, and overall
understanding of the information portrayed in the Story Map. Since most staff do not use or
know about GIS daily, as with the general public, the Story Map will be constructed as simply as
possible for maximum user interaction and satisfaction. It will be assumed that the knowledge
level required would be zero so that the Story Map could be expanded in the future for a wider
audience.
3.1.4. Functional requirements
The Story Map will work on all internet platforms, mobile devices, and tablets. Users will
be able to access the Story Map without needing an Esri account since the Story Map will be
publicly available. However, the link will not be shared publicly until the narrative is vetted in
the future. Users will be able to scroll through the story, click and drag maps and pop-up
configuration boxes, and zoom to different areas on the maps.
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3.1.4.1. Software
Due to the limited open source software and web application knowledge, this pilot project
was created using Esri ArcGIS Pro 2.1, and ArcGIS Online. Supplemental infographics and
media were created using Adobe Design suite including Adobe Illustrator. Analysis and
supplemental charts were created in Microsoft Excel before converting to Adobe Illustrator. A
GitHub Excel Hybrid Geocoder was used to geocode the DMV vehicle dataset (Github 2014).
3.1.4.2. Web Services
This pilot project Web GIS Story Map is hosted on the CEC ArcGIS Online account for
internal staff viewing. Since the CEC already has an Esri account and is using ArcGIS Online,
the potential costs are expected to be minimal and within the current scope of the project. Future
costs for the expanded public-facing Story Map will be based on estimated credits for viewing
and hosting as well as potential page views. This pilot project will provide detailed information
about the Story Map hosting and viewing estimates for management consideration. Esri provides
these analytics in the CEC administrator account to view the number of views.
3.1.5. Design Principles and Choices
The Story Map must be supported with existing CEC available software and will,
therefore, be created using ArcGIS Pro and ArcGIS Online. The initial maps were created in
ArcGIS Pro and symbolized using Color Brewer 2.0 recommendations. Once the layers were
created, each layer was shared to AGOL as a web layer. The maps were created to provide easy
user interaction, and therefore each map contained its own message and theme instead of a single
map with multiple layers and content. The web layers were added to web maps and stylized with
basemaps, transparency, and pop-up boxes before being saved and added to the Story Map. The
design of the web maps was important because it sets the tone for the user experience. Having a
42
visually pleasing, easy to use map not only enhances the mood of the map-user, but also enables
the map-user to understand the map content (Roth 2017).
Using Color Brewer 2.0, recommended color schemes were chosen. Since electric
vehicles do not have an associated color theme like green for money or red for crime, a neutral
blue hue was chosen. In order to provide context, a green-blue hue was used which contained
seven color variations. Darker colors are associated with more or higher values, and lighter
colors are associated with less or lower values, so darker blue was associated with higher values,
and lighter green-yellow was used to show lower values (Brewer 2004).
Specific maps were chosen to provide an accessible format without requiring mouse-
clicks to add or remove layers. This required a separate map for each theme, creating a map for
ZEV 2010, ZEV 2017, Electric Vehicle Charging Stations, Income, and Disadvantaged
Communities. Each map was symbolized using the applicable color scheme and layout to show
the entire state of California before zooming in to higher concentrated areas in Los Angeles and
San Francisco. These designs were selected based on Esri’s Five Principles of Effective
Storytelling (Esri 2018c).
3.1.5.1. Desired Maps and Infographics
• 2010 Vehicle Heat Spot Map – ZEV
• 2017 Vehicle Heat Spot Map – ZEV
• Comparison of 2010 - 2017 Vehicle Heat Spot Map (map slider)
• 2017 ZEV by Census Tract
• 2010 ZEV by Census Tract
• 2017 ZEV by County
• 2010 ZEV by County
43
• Guided map/infographic comparing Vehicle Counts by census level from 2010-
2017.
• 2017 Vehicle Count by census level interactive map with 4 layers (each fuel type)
• Electric Vehicle Charging Station
• Disadvantaged Communities
• Household Income Level by Census Tract
3.2. Story Map Creation
The Esri Story Map Builder was used to create this pilot project Web GIS Story Map.
The Cascade template was used for the Story Map that guides the user through the story. The
Story Map contained several web maps including the primary maps for vehicle counts.
Supporting maps displaying the ZEV 2010 and ZEV 2017 vehicle counts as heat maps were
created to show the concentrations of ZEVs near urban areas and larger cities. In addition, the
ZEV 2017 map was used to compare vehicle counts to disadvantaged communities and income
levels as two additional maps. The electric vehicle (EV) charging stations were added as a
separate map to illustrate the locations of chargers and establish a relationship between ZEV and
EV charging stations.
To design the maps, Color Brewer 2.0 was used to determine the most suitable color
schemes for the maps and ensure the public viewing ease. Since the optimal color ramp is no
more than seven colors (Brewer 2004), the class ranks were set to seven. Additionally, using
Color Brewer 2.0, the color-blind color sets were removed to reduce the public inability to see
the color variations within the web maps. The Esri ArcGIS Pro color ramp Green-Blue 7 class
was consistent with the Color Brewer 2.0 colors (Brewer 2004).
44
The ZEV 2010 and ZEV 2017 vehicle count by census tract and county level aggregation
were created as the primary maps. These maps were normalized by population to show the
number of vehicles relative to the population in each county and census tract.
While several maps were proposed, limitations occurred with the datasets and web
acceptable formats that drove the decision to create the web maps. The proposed local incentives
map was not created because the boundaries of the local areas overlapped and complete data was
not available. Instead of a map, a simple graphic was created. Similarly, for the vehicle
distribution, the vehicle types were not available as intended for map creation and would have
caused more confusion than the graphic created to show the manufactures and available vehicle
technology types.
3.2.1. Cascade Template
The Cascade Story Map template was chosen because of the ease of use, immersive
sections, and guided path for users. While the Story Map Journal, Tabbed Layout, and Swipe
were potential templates, each template lacked a vital component to drive the users toward the
message. The Story Map Journal template provided a similar layout as Cascade; however, the
clunky bar of information caused excessive scrolling for long narrative sections. The Tabbed
Layout had a useful past, present, and future sectional feel. However, the user must click and
navigate through each tab, which may leave some tabs undiscovered. The Swipe template was
also a promising choice to display the past and present comparisons, however like the tabbed
layout; it lacked direction for the users to explore the other swipe maps. The Cascade template
combined the positives from each of these templates into one, allowing the user to explore larger
sections of text, compare past and present maps and graphics, and guides the user through the
story without missing information.
45
The immersive section capabilities in the Cascade template were the original reason this
format was chosen. After viewing several Story Map examples, Lutz’s Oceanic Blue Carbon
Story Map showed the ability to utilize the immersive section and scrolling legend to draw in the
user to understand each section of the infographic in detail allowed. This functionality could be
used to highlight sections of the alternative fueled vehicles progress infographic in the Story Map
to guide the user. In the figures below, Lutz described different sections of the infographic while
greying out other areas so the user could focus on one specific item at a time. This will help
guide the user through more challenging areas that could have distractions from the linear flow
intended in the narrative.
Figure 13 Lutz Oceanic Blue Carbon Immersive Infographic (Lutz 2018)
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Figure 14 Lutz Oceanic Blue Carbon Infographic with Legend (Lutz 2018)
3.2.2. Development
The Story Map creation process comprised three main components: web maps, narrative,
and infographics. The web maps were created as six individual sections to the viewer while
actually comprising nine maps. The maps were inserted into the Story Map as immersive
sections, which “locked in” the maps to a full page and allowed the user to scroll while having a
narrative box scroll with the mouse. This allowed for additional map views to be added for the
Los Angeles and San Francisco areas while the user continued to scroll without requiring map
movement on the user. The design principles were implemented on the maps, infographics, and
narrative, maintaining the same color scheme throughout.
The Story Map was created with a past, present, and future layout. This allowed the user
an introduction to the subject, given a brief overview of the history, an understanding of the
current progress, and the outlook for the future. Each section was a new topic that had an
associated map or infographic, which allowed the user to finish each thought before moving to
the next one. A simple process showing the steps taken is provided in Figure 15 below.
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Figure 15 Story Map Creation Process
3.2.3. Data
Several datasets were created in order to create the web maps. The primary dataset was
the DMV vehicle stock dataset, and the supporting datasets were the electric vehicle charging
stations, household income, and disadvantaged communities. Each dataset required different
processes to convert the data to spatial data and prepare the data for integration into ArcGIS
Online for web map creation.
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3.2.3.1. Department of Motor Vehicles (DMV) Data
The primary dataset was the DMV vehicle stock data, which contained the vehicle
address, fuel type, manufacturer, model, and model year. This data was provided in a .csv file
format with the full address, city, state, and zip code. In order to convert the dataset for GIS, the
dataset was geocoded using an Excel Hybrid Geocoder from Github. This produced the GPS
coordinates for each vehicle along with a confidence level. The confidence level was associated
with how accurate the algorithm thought the location was. Once the DMV vehicle stock data was
geocoded, this table was imported to ArcGIS Pro and converted to a GIS table. This process was
completed for the 2010 and 2017 datasets. Once imported, the datasets were displayed as X, Y
data and the locations of vehicles were displayed as points on the map. Points that were located
outside of California were evaluated for accuracy, and many were removed due to old addresses
that were not within the state. Other addresses that were not accurate were moved to the correct
location, and those with registrations outside of California were removed. This provided 762 and
332,506 vehicles in California for 2010 and 2017 respectively.
To create the choropleth maps, the dataset was summarized by county and census tract
for 2010 and 2017 to provide boundary layers with vehicle counts. Then the data was normalized
by population counts to show the number of vehicles per population in each county and census
tract. These datasets were the foundational datasets for this project and used in conjunction with
other datasets to create the maps.
To create the heat maps, the point dataset of vehicles were used with the Kernel Density
geoprocessing tool. The Kernel Density tool calculates the distance of neighboring points and
produces a raster cell for the count of points. The default settings for cell size, output radius, and
area units were used. The 2017 dataset contained more points and provided a smoother transition
showing peak areas of San Francisco, Los Angeles, San Diego, Sacramento, and Fresno. The
49
symbology was set to stretch with three standard deviations. The same process was performed
for 2010. However, due to the limited number of data points, the transition was rough and called
out San Francisco and Los Angeles areas generically. In order to evaluate the heap map trends
between the two years, the same color ramp was used by applying the symbology from the 2017
ZEV Heat Map layer with the Apply Symbology from Layer tool.
3.2.3.2. Electric Vehicle Charging Station
The 2019 electric vehicle (EV) charging station dataset was obtained from the
Department of Energy website and downloaded as a .csv file. This dataset provided the charging
station location, name, descriptive address, city, charger connector type, and operational date
among other fields. Since the dataset contained the location as both the address and GPS
coordinates, it was ready to be imported to ArcGIS Pro. Once the dataset was imported and
displayed as X, Y, the locations of each EV charging station were shown. In order to correlate
the number of vehicles and the availability and number of EV chargers, the dataset was displayed
as a point dataset showing each location.
3.2.3.3. Income
Income data was obtained from the US Census Bureau and was provided per census tract.
This dataset contained the American Community Survey (ACS) 5-year estimates for 2013-2017.
This dataset was already prepared for GIS as a shapefile by the CEC, whom joined the median
household income data with the respective census tract. This was added to ArcGIS Pro and used
as a file geodatabase to be joined with the census tract level ZEV 2017 dataset.
50
3.2.3.4. Disadvantaged Communities (DAC)
The DAC dataset was a shapefile downloaded from CalEnviroScreen 3.0 and contained
data fields by census tract. A DAC is defined as the top twenty-five percent scoring from the
CalEnviroScreen. The CalEnviroScreen dataset is the output of a model created from twenty
statewide indicators for pollution burden and population characteristics. Each census tract
receives a score for each indicator, which are ranked from highest to lowest. The population
characteristic score for sensitive populations and socioeconomic factors are averaged. The
pollution burden score contains the average of exposures and one-half of the average of
environmental effects because the environmental effects make a smaller contribution to the
pollution burden. The formula multiplies the pollution burden by the population characteristic to
create the CalEnviroScreen score (CalEPA 2018).
Figure 16 CalEnviroScreen 3.0 Scoring and Model (CalEPA 2018)
This data was added to ArcGIS Pro and used as a file geodatabase, which was paired with
the census tract level ZEV 2017 dataset as two layers on the same map. Each layer displayed the
respective information for 2017 ZEV and DAC areas. The 2017 ZEV layer was made transparent
and is the top layer while the DAC layer is a full-colored bottom layer.
3.3. Intended Users
The intention of this thesis was to create a pilot project for a Web GIS Story Map that can
be used to understand the progress towards the state mandates and goals for alternative fueled
vehicles. The initial Story Map was created and tested by internal CEC staff to determine the
51
usefulness of using a Story Map as a communication tool with the public. In addition to
introducing staff to Story Maps and creating a dialogue for enhancements of the current Story
Map was started. This second phase will include additional maps and narrative for the future
audience. This unique group of future users will range from the general public and stakeholders
to other state agencies and car manufacturers as the Story Map will be publicly available on the
CEC’s website and linked from the transportation forecast page. These users will have the ability
to see a glimpse of the information within the 117-page report and selected historical background
concerning alternative fueled vehicles without needing to go to several locations.
Once the Story Map pilot project was completed, internal staff were given a timeframe to
view the Web GIS Story Map, interact with the maps and images, and then asked to take a
survey on their experience. The survey asked their name, previous knowledge of alternative fuels
and the state goals and mandates, the user experience viewing the Story Map, and whether they
learned anything new or relearned something after viewing the application. A sample survey is
included below in Table 3. A minimum of 10 staff and a maximum of 25 staff will take the
survey.
3.4. Application Evaluation
3.4.1. Subjects
The intended users for this pilot project are internal CEC staff, namely the staff within the
Energy Assessments Division that focuses on the Transportation Energy Demand Forecast.
These subject matter experts develop the transportation forecast report and have key knowledge
about the public message surrounding the alternative fueled vehicles progress and future. These
staff were identified as the survey subjects to view this Story Map and provide feedback based
on the ease of use, optimal flow of the narrative, and overall layout and understanding of the
52
Story Map. Sixteen staff members were asked to complete the survey. Staff had a range of
knowledge and skills about the transportation report, Web GIS Story Maps, and changing
technologies. These staff were identified as test subjects based on their length of experience;
obtaining a wide range of subjects. One test subject performs the duties of the lead role while
another subject is a student. This range of knowledge and skills provided an overview of the
different levels of knowledge that may be seen in the public for the future users.
3.4.2. Design of survey
The survey was designed in Google forms as a simple ranking and binary survey that
users will fill out after viewing the Story Map. The purpose was to gather feedback on the Story
Map ease of use, flow, and overall organizational layout. Any comments and edits made will be
implemented before presenting the Story Map to other CEC staff and management. The results
of this survey are included as percentages to show the overall user experience.
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Table 3. Survey Form Layout
Survey Question Possible Answers
Before using this Web GIS map, what was your familiarity with
the following?
No knowledge
A small amount of knowledge
A moderate amount of knowledge
A significant amount of knowledge
A great deal of expertise
Alternative fueled vehicles generally
Alternative fueled vehicle mandates in California
Alternative fueled vehicle California state goals
Web-based Story maps
In general, how comfortable do you feel with new technology? Very comfortable
Somewhat comfortable
Neither comfortable or
uncomfortable
Somewhat uncomfortable
Very uncomfortable
How well do the following terms describe this Story Map? Very well
Somewhat well
Neither well or poorly
Somewhat poorly
Very poorly
Intuitive
Clear
Confusing
Disorganized
Engaging
How appropriate do you think this Web GIS Story Map is for
the following audiences?
Not at all appropriate
Somewhat appropriate
Very appropriate The general public
Laypeople who understand the basics of alternative
fueled vehicles
Policymakers and Legislators
Stakeholders
Other State Agencies (ex. CPUC and ARB)
As a tool for communicating with the following groups, how do
you think this Web GIS Story map compares to the
Transportation Energy Demand Forecast Report?
Much better
Somewhat better
Neither better or worse
Somewhat worse
Much worse
N/A – I am unfamiliar with the
report
The general public
Laypeople who understand the basics of alternative
fueled vehicles
Policymakers and Legislators
Stakeholders
Other State Agencies (ex. CPUC and ARB)
Demographics Possible Answer
What is your age 0-18
19-24
25-34
35-44
45-54
55-64
65+
54
Gender Female
Male
Prefer not to say
Other
What is your race/ethnicity (select all that apply)? White/Caucasian
Hispanic/Latino
Black/African American
Asian
Prefer not to say
Other
What is your highest level of education? High school or less
Vocational/trade school
Some college
Bachelor’s Degree
Masters/JD
PhD
Prefer not to say
What is your profession Open-ended answer text box
Email address (note- this will only be used for personal
communication and will not be shared with any 3rd parties)
Open-ended answer text box
3.4.3. Time involved in testing
Users had access to the Story Map to view the narrative, maps, and infographics. The
entire survey testing took approximately two weeks to select internal staff for the survey, view
the Web GIS Story Map, conduct the survey, and compile the results. The Cascade template
provides a logical flow to the story to guide the users throughout the storyline as intended. The
users were instructed to follow the original flow of the story and provide feedback with their
experience. The Story Map took on average fifteen minutes to scroll through, and staff were
asked to spend approximately fifteen to thirty minutes reviewing the Story Map before
completing the survey.
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Chapter 4 Results
4.1. Overview
The pilot Story Map was created using ArcGIS Pro, ArcGIS Online, and Esri Story Map
Builder. Several datasets were used to create file geodatabases and web layers in ArcGIS Pro for
publishing to ArcGIS Online. Once the maps were created, they were integrated into the Story
Map web application and paired with narratives and supporting infographics and charts.
4.2. Maps
As mentioned before, several maps were created to illustrate the story of the alternative
fueled vehicles. The ZEV datasets were used as the foundation to create the maps and serve as
the supporting layer for the DAC and income level maps.
The maps were constructed by creating the layers in ArcGIS Pro. The datasets were
symbolized and then shared as web GIS layers to ArcGIS Online (AGOL). Once the layers were
added to AGOL, the layers were added to maps and the individual maps were created. Each layer
was re-symbolized for the online environment including selecting the appropriate basemap,
setting zoom levels and transparency, and creating pop-up boxes. Each layer had its own pop-up
box that contained detailed information within the layer specific for the purpose of that map.
4.2.1. ZEV 2010
This map was created as two maps, one for the county and one for the census tract level.
The ZEV 2010 County layer was added to the map, symbolized as a choropleth map with natural
breaks classification, and then the pop-up was configured to show the county name and the
vehicle count. The census tract maps were created in the same manner, by adding the 2010 ZEV
Census Tract layer, symbolizing the layer, and configuring the pop-up to display the census tract
56
name and vehicle count. For each of these layers, the counties and census tracts without a vehicle
were omitted or greyed out. This helped illustrate the lack of vehicles in those areas of
California. The mouse scroll function was used to move from the county level to census tract
level map. To guide the user to the important areas, copies of the map were created in the
immersive section to show the user the concentrated areas of vehicles in Los Angeles and San
Francisco. The narrative boxes were added to provide context to the user as shown in Figure 17
below and described the map content.
Figure 17 ZEV 2010 Immersive Map and Narrative Box
4.2.2. ZEV 2017
This map was created as two maps, one for the county and one for the census tract level.
The ZEV 2017 County layer was added to the map, symbolized as a choropleth map with natural
breaks classification, and then the pop-up was configured to show the county name and the
vehicle count. The census tracts that did not have a vehicle were omitted similar to the 2010
57
map. The mouse scroll function was also used to move from the county to census tract map. To
guide the user, copies of the maps were created to build the immersive section that showed the
user where the concentrated vehicles were. The narrative box and colors were used instead of
traditional map legends to focus the user on the main point for the map. As shown in Figure 18
below, the focus was a large number of ZEV registrations as displayed with the dark blue text.
By applying the colors to the text, the user can gain the information necessary to draw
conclusions without distracting from the map content (Esri 2017).
Figure 18 ZEV 2017 Immersive Map with Narrative Box
4.2.3. Heat Map
The 2010 normalized heat map tile web layer was added to a map with the basemap.
Since this dataset was normalized to the same scale as the 2017 dataset, the blue variation was
shown on the map as a single color. The 2017 heat map showed the typical heat map. The
“slider” function was used to horizontally swipe between the 2010 and 2017 maps to really show
58
the differences. Narrative boxes were used to highlight the increase of ZEVs between 2010 and
2017 using the colored text to describe the concentrated areas.
Figure 19 Heat Map Slider View
4.2.4. EV Charging Stations
The EV charging stations web layer were added to the map, and the appropriate basemap
was selected. The comparison of streets and roads were the priority for this map, so the basemap
containing roadways was used to illustrate the locations of EV chargers near major cities and
along the major roads in California. The narrative box and colored text were used to inform the
user that the purple dots on the map were electric vehicle chargers and provide context.
Additional concentration level maps were used to show the areas of Los Angeles and San
Francisco when the user continued to scroll. The pop-up box was configured to show the user the
location name and charger type when selected.
59
Figure 20 Electric Vehicle Charging Stations Immersive Map
4.2.5. Low Income ZEV
The ZEV income layer was added along with the low-income layer. The ZEV layer was
symbolized as a choropleth map with natural breaks classification and a pop-up that contained
the census tract number, the vehicle count, income for that census tract, and the statewide median
household income percentage for the census tract. A separate layer, Low income, was added and
symbolized to show the census tracts that were under eighty percent of the statewide median
income. This layer was not selectable and was used as a supporting layer since the data was
joined to the ZEV layer.
60
Figure 21 ZEV and Income Immersive Map
4.2.6. DAC ZEV
The DAC and ZEV 2017 web layers were added to a map. The DAC layer was the
bottom layer, and the ZEV 2017 layer was made transparent and placed on top. The DAC layer
was symbolized as a choropleth map with an equal interval classification for ten-percent of the
DAC score. Due to the two color ramps, green-blue for the ZEV 2017 and a red-green for the
DAC layers, the transparency allowed the color concentrations to highlight the extremes of the
map. A bold, dark green highlighted the lower DAC and higher ZEV areas. Conversely, the high
DAC and low or no ZEV concentrated areas were bright red since the ZEV layer that did not
contain vehicles was not colored, and the low areas were light yellow/green in color. The pop-up
was configured to show the census tract name, vehicle count, and CalEnviroScreen score.
61
Figure 22 ZEV 2017 and DAC Immersive Map
4.3. Infographics
Several infographics were created to pair with the immersive section maps and narrative
text in the Story Map. These infographics were created in Adobe Illustrator from a starter file
downloaded from Freepik. The colors used were the color scheme from the CEC with blue,
green, and orange as the primary colors. This provided a cohesive look across the Story Map and
a smooth transition from narrative text, immersive sections, and infographics. Once created,
these infographics were added to the Story Map through the Esri Story Map Builder as .png files.
4.3.1. Main infographic
The main infographic for the Story Map details the summary statistics, and major points
about the alternative fueled vehicles. The sections relevant to each major point were highlighted,
and the remaining infographic was greyed out to emphasize the point being made similar to
62
Lutz’s Oceanic Blue Carbon infographics. These graphics were then used in the Story Map as an
immersive feature in which the user scrolls through and the graphic changes with each point.
Each section was created as a separate .png file to be added to the immersive section. This
allowed the new infographic highlighted area to appear and the narrative box to scroll with the
mouse scroll.
Figure 23 Story Map Infographic
63
Figure 24 Story Map Infographic Highlighted Area
4.3.2. Supporting Infographics
The other infographics, comparison of vehicle counts (Figure 25) and the vehicle
manufacturer fuel types (Figure 26). These were added within the text line of the narrative
sections, as they did not need to be full-page immersive sections.
64
Figure 25 Vehicle Comparison Between 2010 and 2017
Figure 26 Vehicle Manufacturer Fuel Type Infographic
4.4. Supporting Documentation
Since the pilot project Story Map purpose is to guide internal staff along the narrative of
alternative fueled vehicles, additional links were imbedded for further reading and understanding
of the complex programs, mandates, and legislation. Once this Story Map is published for the
public, they will be able to access these supporting links to gain access for legislative guides,
programs with funding and charging station information, as well as incentives and local
programs.
65
4.5. Survey Results
The results showed most users felt the Story Map was intuitive, clear, and organized.
Users were engaged with the map and agreed that the Story Map was a good tool for
communicating with the general public, laypersons, policy makers, and legislators, and
stakeholders. Additionally, users liked maps and infographics that drew attention to sections of
the Story Map. The overall feedback was positive, and users recognized the value to adding the
Story Map as a complimentary component to the Transportation Energy Demand Forecast. The
additional survey questions and results can be found in Appendix B Survey Results.
Figure 27 Survey Results
0
1
2
3
4
5
6
7
8
9
The general public Laypeople who
understand the basics
of alternative fueled
vehicles
Policymakers and
Legislators
Stakeholders Other State Agencies
(ex. CPUC and ARB)
How appropriate do you think this Web GIS Story Map is for the
following audiences?
Not at all appropriate Somewhat appropriate Very appropriate
66
Chapter 5 Discussion and Conclusion
5.1. Summary Description
The Story Map created was a well-organized, functioning Story Map that engaged CEC
internal staff and introduced a new tool that could be used with the traditional reports. Staff
agreed that the Story Map was easy to use and were excited for the final version to be deployed
along with the Transportation Energy Demand Report in the near future.
5.2. Challenges in Development
While the initial goal was to create a Story Map for the general public, the timeframe
limitations for the thesis project and the internal review process did not align. This thesis project
was shifted to provide the first of two phases: phase one as the internal CEC staff introduction to
Story Maps and review of the Story Map process, creation, and possibilities and phase two as the
fully published, publicly available Story Map. In addition to the timeframe restrictions, ad hoc
requests to add data layers, maps, infographics, and additional narrative sections were outside of
the initial scope of the project. These additional pieces, however, can be added to phase two in
the near future.
5.3. Limitations of the Project
The main limitation of this project was the confidentiality of the DMV dataset since it
contains personally identifiable information (PII) and must remain confidential. This was noted,
and the datasets were carefully managed to ensure proper data confidentiality occurred, and
aggregation standards were met. An original goal of the project was to provide more granular,
detailed information about the locations of alternative fueled vehicles. Since the exact locations
67
were not allowed to be shared, census tract level grouping were made, however these
enumeration units also provided vague ambiguity.
Another limitation was the availability of several datasets, including the statewide
incentives for each utility, county, and city. This dataset does not exist and requires additional
staff expertise to gather the information for the incentives and the jurisdictional boundaries for
each component. This can be added as a phase two addition. The other main dataset was the
manufacturer specific registrations. The intent was to analyze the locations of manufacturer and
model specific vehicle locations; however, the registration database limited the vehicle fuel-type
options, which limited this analysis. This can be evaluated for a future project.
5.4. Future Expansion and Full Deployment of the Application
This Story Map includes data and maps for 2010 as the base year and 2017 as the most
current complete year at the time of this thesis start date (Fall 2018). Since 2018 was not yet
completed, that year’s dataset was not yet available. Each compete year’s dataset can be added
and updated in the spring of the following year to continue the narrative and provide the progress
towards reaching the alternative fueled vehicle goals. In the enhanced phase of this project, a
closer look into the spatial correlations of alternative fueled vehicles and poverty levels,
demographic associations for race, and income inequality can be evaluated. Creating a baseline
of data for 2010 allows the creation of 2011 through 2016 datasets to be compared as well as
future datasets from 2018 to 2030. This detailed analysis will uncover the geographical links and
discover new solutions for providing alternative fueled vehicles in California.
In addition, this Story Map will be used as a guideline for the creation of new Story Maps
to support other reports. The design elements, techniques, and fundamental choices can be used
as a framework to implement the creation of Story Maps for public facing reports and updates.
68
This will cut down on a considerable amount of time to create this process and insure that the
GIS techniques are implemented accordingly to communicate science with the public.
5.5. Conclusion
The initial goal of this thesis project was to complete a Story Map for internal CEC staff
and was successful. This introduction to web GIS Story Maps has provided staff with a new
vision to create complimentary Story Maps to inform the public on the progress made on several
state mandates and goals. The functionality of the Story Map was intuitive, easy to use, and
provided a natural flow to the users. The ability to edit and update the maps when new data
becomes available is also key since this will reduce staff time to create new Story Maps from
scratch. This template can also be used to create Story Maps for other reports and content by the
CEC in the future. The Story Map also provides historical context for the baseline years and the
progress made to date and shows the historical trends.
69
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74
Appendix A Story Map
The graphics and illustrations provided in this appendix are intended to provide context to the
content within the Web GIS Story Map. The purpose of this section is to show the layout,
narrative, infographics, and interactive web maps. Each web map contains pop-up boxes,
interactive map functions, and map scales that allow the user to visualize the content within the
Story Map.
75
76
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79
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84
85
86
87
88
89
90
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93
94
95
96
97
Appendix B Survey Results
This section shows the survey that was provided to internal CEC staff and the summarized
responses from the survey.
0
1
2
3
4
5
6
7
8
Alternative fueled vehicles
generally
Alternative fueled vehicle
mandates in California
Alternative fueled vehicle
California state goals
Web-based Story maps
Before using this Web GIS map, what was your familiarity with
the following?
No Knowledge A small amount of knowledge A moderate amount of knowledge
A significant amount of knowledge A great deal of expertise
In general, how comfortable do you feel with new
technology?
Very comfortable Somewhat comfortable
Neither comfortable or uncomfortable Somewhat uncomfortable
Very uncomfortable
98
0
1
2
3
4
5
6
7
8
Intuitive Clear Confusing Disorganized Engaging
How well do the following terms describe this Story Map?
Very well Somewhat well Neither well or poorly Somewhat poorly Very poorly
0
1
2
3
4
5
6
7
8
9
The general public Laypeople who
understand the basics
of alternative fueled
vehicles
Policymakers and
Legislators
Stakeholders Other State Agencies
(ex. CPUC and ARB)
How appropriate do you think this Web GIS Story Map is for the
following audiences?
Not at all appropriate Somewhat appropriate Very appropriate
99
0
1
2
3
4
5
6
The general public Laypeople who
understand the basics
of alternative fueled
vehicles
Policymakers and
Legislators
Stakeholders Other State Agencies
(ex. CPUC and ARB)
As a tool for communicating with the following groups, how do
you think this Web GIS Story map compares to the
Transportation Energy Demand Forecast Report?
Much better Somewhat better
Neither better or worse Somewhat worse
Much worse N/A - I am unfamiliar with the report
Abstract (if available)
Abstract
Alternative fueled vehicles are positively shaping the environment, emissions, and social perceptions of vehicles. Several pieces of legislation and mandates have been passed in California to guide the state towards positive climate impact goals. Assembly Bill 118 and Executive Order B-16-2012 are notable pieces of legislation passed within the last decade that are driving California towards five million zero-emission vehicles by 2030. While these goals are aspirational, several state agencies have collaborated to create programs to accomplish this goal, including the Alternative and Renewable Fuel and Vehicle Technology Program. The California Energy Commission (CEC) has been tasked with implementing this program and releasing an annual Transportation Energy Demand Forecast. This report includes multiple charts and datasets, but no maps or visualizations to facilitate the public’s understanding as to the progress of said goals or the ability to achieve the interim 1.5 million zero-emission vehicles by the 2025 target. Research has shown that maps enable data to be better understood by both professionals and the general public. The primary goal of this thesis was to create a Web GIS Story Map that visualizes the progress towards meeting California’s alternatively fueled vehicle goals as a means of demonstrating the viability of Story Maps as a communication approach. The Story Map includes geographic representations of alternative fueled vehicles, spatial analysis of the demographic and economic adoptions throughout the state, and immersive multimedia to facilitate exploration of the alternative fueled vehicle program. This study evaluated the degree to which internal staff determined the Story Map useful versus approaches that are more traditional. Preliminary responses from internal staff showed that the Story Map was well organized and intuitive. This pilot project serves as a flagship Story Map that can be expanded upon and published by the CEC for the general public review in the near future.
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Asset Metadata
Creator
Brunsvold, Christina Marie
(author)
Core Title
A spatial narrative of alternative fueled vehicles in California: a GIS story map
School
College of Letters, Arts and Sciences
Degree
Master of Science
Degree Program
Geographic Information Science and Technology
Publication Date
06/13/2019
Defense Date
04/25/2019
Publisher
University of Southern California
(original),
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Tag
alternative fuel vehicles,California,geographic information systems,GIS,OAI-PMH Harvest,renewable,story map,zero emission vehicles,ZEV
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Bernstein, Jennifer (
committee chair
), Oda, Katsuhiko (
committee member
), Swift, Jennifer (
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)
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ccrume@usc.edu,christina.brunsvold@gmail.com
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Tags
alternative fuel vehicles
geographic information systems
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renewable
story map
zero emission vehicles
ZEV