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Human suffering during wartime: a StoryMap of violations of international law during the Russo-Ukrainian War

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Human suffering during wartime: a StoryMap of violations of international law during the Russo-Ukrainian War

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Content Human Suffering During Wartime:
A StoryMap of Violations of International Law During the Russo-Ukrainian War
by
William Acy Akridge
A Thesis Presented to the
FACULTY OF THE USC DORNSIFE COLLEGE OF LETTERS, ARTS, AND SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY)
December 2024
Copyright © 2024 William Akridge

ii
Dedication
To my wife, Kaitlyn, who encouraged me throughout my master’s program, and patiently
endured long weekends and late nights spent working throughout this thesis.
This achievement would not have been possible without you.

iii
Acknowledgments
Thank you to all the brilliant and inspirational professors who lead the Spatial Sciences Institute.
I am thankful to Dr. Darren Ruddell, who guided me through the first half of my thesis. I am
grateful to my advisor, Dr. Elisabeth Sedano, for the guidance and assistance throughout my
thesis development and writing. I am appreciative to my committee members, Dr. Diana TerGhazaryan and Dr. Guoping Huang who assisted me when I needed it most. I would like to thank
my dearest wife, Kaitlyn, who supported me through many years of studies to complete my
master’s degree. I want to thank my wonderful parents. They have provided me with countless
opportunities for my growth and educational development. To my basset hound, Mabel.
Thank you for always letting me know when it was time to take a break and head outside.

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Table of Contents
Dedication ....................................................................................................................................... ii
Acknowledgments..........................................................................................................................iii
List of Figures............................................................................................................................... vii
Abbreviations................................................................................................................................. ix
Abstract........................................................................................................................................... x
Chapter 1 Introduction .................................................................................................................... 1
1.1 Background ......................................................................................................................... 1
1.2 International Humanitarian Law......................................................................................... 3
1.2.1 War Crimes................................................................................................................ 4
1.2.2 Crimes Against Humanity.......................................................................................... 4
1.2.3 Genocide .................................................................................................................... 5
1.2.4 Violations of International Humanitarian Law in Ukraine ........................................ 6
1.3 Study Area .......................................................................................................................... 6
1.3.1 War Crimes Study Area ............................................................................................. 8
1.3.2 Crimes Against Humanity Study Area ...................................................................... 9
1.3.3 Genocide Study Area ............................................................................................... 10
1.4 Project Overview .............................................................................................................. 11
1.4.1 Data Overview ......................................................................................................... 12
1.5 Structure of Thesis............................................................................................................ 12
Chapter 2 Related Work................................................................................................................ 13
2.1 The Significance of Identifying and Alleviating Human Suffering.................................. 13
2.2 Spatial Investigations Related to Human Rights Violations............................................. 15
2.3 Spatial Data Storage, Dashboards, and Storytelling ......................................................... 17
2.3.1 Esri ArcGIS Online.................................................................................................. 17
2.3.2 Esri Dashboards....................................................................................................... 18
2.3.3 Esri StoryMaps......................................................................................................... 20
2.4 Spatial Applications of War and Human Tragedies ......................................................... 21
Chapter 3 Methods........................................................................................................................ 25
3.1 Methods Overview............................................................................................................ 25
3.2 War Crimes – Mariupol .................................................................................................... 26
3.2.1 Data for War Crimes – Mariupol ............................................................................. 26
3.2.1.1 Mariupol city boundary................................................................................... 26
3.2.1.2 Mariupol city building footprints.................................................................... 27
3.2.1.3 Mariupol City Damaged Hospitals ................................................................. 28
3.2.1.4 Mariupol City Damaged Education ................................................................ 30
3.2.1.5 Mariupol City Power Lines............................................................................. 31
3.2.1.6 Mariupol City Power Stations......................................................................... 32

v
3.2.1.7 Mariupol City Power Towers.......................................................................... 33
3.2.1.8 Mariupol City Key Water Network ................................................................ 34
3.2.1.9 Mariupol City Key Water Facilities................................................................ 36
3.2.2 War Crimes Data Preparation .................................................................................. 37
3.2.3 Data Publishing for War Crimes – Mariupol........................................................... 38
3.2.4 War Crimes Layers and Map Preparation in ArcGIS Online .................................. 39
3.2.5 War Crimes Dashboard and StoryMap Development ............................................. 40
3.3 Crimes Against Humanity – Bucha .................................................................................. 42
3.3.1 Crimes Against Humanity Data ............................................................................... 43
3.3.1.1 Bucha city boundary ....................................................................................... 43
3.3.1.2 Bucha city bodies identified............................................................................ 44
3.3.1.3 Bucha city building footprints ........................................................................ 45
3.3.2 Crimes Against Humanity Data Preparation............................................................ 46
3.3.3 Crimes Against Humanity Data Publishing............................................................. 47
3.3.4 Crimes Against Humanity Layers and Map Preparation in ArcGIS Online............ 48
3.3.5 Crimes Against Humanity Dashboard and StoryMap Development....................... 49
3.4 Genocide – Ukraine .......................................................................................................... 51
3.4.1 Genocide data........................................................................................................... 51
3.4.1.1 Kidmapping..................................................................................................... 52
3.4.1.2 Re-education camps and military facilities for children ................................. 53
3.4.1.3 ACLED abduction event data ......................................................................... 54
3.4.1.4 Oblast boundaries............................................................................................ 55
3.4.2 Genocide Data Preparation ...................................................................................... 56
3.4.3 Genocide Data Publishing........................................................................................ 56
3.4.4 Genocide Layers and Map Preparation in ArcGIS Online ...................................... 57
3.4.5 Genocide Dashboard and StoryMap Development.................................................. 59
Chapter 4 Results.......................................................................................................................... 61
4.1 Human Suffering During Wartime StoryMap Section ..................................................... 61
4.2 War Crimes StoryMap Section ......................................................................................... 62
4.2.1 War Crimes StoryMap Context ............................................................................... 62
4.2.2 War Crimes StoryMap Study Area .......................................................................... 63
4.2.3 War Crimes StoryMap Dashboard........................................................................... 64
4.3 Crimes Against Humanity StoryMap Section................................................................... 66
4.3.1 Crimes Against Humanity Context.......................................................................... 66
4.3.2 Crimes Against StoryMap Study Area .................................................................... 67
4.3.3 Crimes Against Humanity Dashboard ..................................................................... 67
4.4 Genocide StoryMap Section ............................................................................................. 69
4.4.1 Genocide Context..................................................................................................... 69
4.4.2 Genocide StoryMap Study Area .............................................................................. 70
4.4.3 Genocide Dashboard................................................................................................ 71
Chapter 5 Discussion .................................................................................................................... 74
5.1 Finished Product ............................................................................................................... 74
5.2 Limitations and Challenges............................................................................................... 74
5.2.1 Data ......................................................................................................................... 75
5.2.2 Human Dignity......................................................................................................... 75

vi
5.3 Future Work ...................................................................................................................... 76
Appendix....................................................................................................................................... 78
References..................................................................................................................................... 83

vii
List of Figures
Figure 1. Study Area – Ukraine ...................................................................................................... 7
Figure 2. Mariupol Study Area ....................................................................................................... 9
Figure 3. Bucha Study Area.......................................................................................................... 10
Figure 4. Territory Height of Russian Military Study Area.......................................................... 11
Figure 5. AGOL Folder and Data Used ........................................................................................ 18
Figure 6. Fire Data Dashboard - Bushfire Data ............................................................................ 19
Figure 7. Fire Data Dashboard – Hot Spot Analysis Results........................................................ 20
Figure 8. StoryMap Design Page .................................................................................................. 21
Figure 9. Battles of The American Civil War StoryMap.............................................................. 22
Figure 10. Bombing Missions of the Vietnam War - flown by the United States........................ 23
Figure 11. Putting the Pieces Together Section of Mapping Russia's War on Ukraine................ 24
Figure 12. Workflow Diagram...................................................................................................... 25
Figure 13. Mariupol Boundary ..................................................................................................... 27
Figure 14. Mariupol OSM Building Footprints............................................................................ 28
Figure 15. Mariupol OSM Damaged Hospital Building Footprints ............................................. 29
Figure 17. Mariupol OSM Damaged Education Building Footprints........................................... 31
Figure 18. Mariupol City Power Lines ......................................................................................... 32
Figure 19. Mariupol City Power Stations ..................................................................................... 33
Figure 20. Mariupol City Power Towers...................................................................................... 34
Figure 21. Mariupol City Key Water Network............................................................................. 35
Figure 22. Mariupol City Key Water Facilities ............................................................................ 37
Figure 23. War Crimes Dashboard Development......................................................................... 42

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Figure 24. Bucha Boundary – Google .......................................................................................... 44
Figure 25. Bucha Bodied Identified (Source: The New York Times).......................................... 45
Figure 26. OSM Bucha Building Footprints................................................................................. 46
Figure 27. Crimes Against Humanity Dashboard Development .................................................. 51
Figure 28. Locations where Ukrainian Children were abducted to – Kidmapping ...................... 52
Figure 29. Re-Education Camps and Military Facilities for Children – Rubtyka ........................ 53
Figure 30. ACLED Civilian Abduction Data ............................................................................... 54
Figure 31. Oblast Boundaries – HDX........................................................................................... 55
Figure 32. Development of Genocide Dashboard......................................................................... 60
Figure 33. Human Suffering During Wartime StoryMap Cover.................................................. 61
Figure 34. Human Suffering During Wartime Section................................................................. 62
Figure 35. War Crimes Section of StoryMap ............................................................................... 63
Figure 36. War Crimes Study Area Section of StoryMap ............................................................ 64
Figure 37. War Crimes Dashboard Final ...................................................................................... 65
Figure 38. Crimes Against Humanity Section of StoryMap......................................................... 66
Figure 39. Crimes Against Humanity Study Area Section of StoryMap...................................... 67
Figure 40. Crimes Against Humanity Dashboard Final................................................................ 69
Figure 41. Genocide Section of StoryMap ................................................................................... 70
Figure 42. Genocide Study Area Section of StoryMap ................................................................ 71
Figure 43. Genocide Dashboard Final .......................................................................................... 73

ix
Abbreviations
AAAS American Association for the Advancement of Science
ABT American Battlefield Trust
ACLED Armed Conflict Location and Event Eata
AGOL ArcGIS Online
AP Associated Press
BBC British Broadcasting Corporation
CIA Central Intelligence Agency
DIL Digital Investigations Lab
DOD United States Department of Defense
GIS Geographic information system
HDX Humanitarian Data Exchange
HOT Humanitarian OpenStreetMap Team
HRW Human Rights Watch
ICC International Criminal Court
IHL International Humanitarian Law
ISW Institute of the Study of War
OSM OpenStreetMap
OIM Open Infrastructure Map
UN United Nations

x
Abstract
The Russo-Ukrainian War began with the large-scale invasion of Ukraine by Russian forces in
the early morning of February 24, 2022. As the war continues, there have been widespread
reports of violations of international humanitarian law with civilian populations being heavily
impacted by this war. This thesis aims to inform readers about human suffering during the war in
Ukraine and the use of spatial visualizations to convey events that contravene international
humanitarian law. The three violations researched within this thesis include war crimes, crimes
against humanity, and genocide. The study areas for these three sections are the city of Mariupol,
the town of Bucha, and the Russian-occupied regions of Ukraine. The data is from publicly
available datasets, authoritative news sources, the United Nations, the country of Ukraine, and
Armed Conflict Location and Event Data. This thesis displays the occurrence of human tragedies
such as civilian fatalities, explosions/remote strikes, battles, strategic developments, violence
against civilians, targeting of medical facilities, targeting of educational facilities, occurrences of
sexual violence, abducted persons, and damage to civilian infrastructure. The completed work of
this thesis is published in an Esri StoryMap to articulate the history of the conflict and visually
display the spatial data within a series of Dashboards. Further practices of researching and
visualizing human atrocities affecting civilian populations, such as spatial journalism, need to be
expanded within the realm of spatial sciences. Organizations seeking to relieve civilian
populations' suffering during wartime must adopt and expand upon these practices. The
preliminary results of this methodology successfully presented the occurrence of human
suffering in a StoryMap via the thesis definition of the violation of international humanitarian
law.

1
Chapter 1 Introduction
Suffering caused by the hands of others has plagued human existence for thousands of years. In
the modern era of technology spatially tracking these human atrocities has become necessary for
identifying, analyzing, and appropriately reacting to different occurrences of human suffering.
The international community needs to further develop its methods within the spatial sciences in
the identification of the breaking of international law during wartime. The Russo-Ukrainian War
escalated with the large-scale invasion of Ukraine by Russian forces in the early morning of
February 24, 2022, after months of militarized buildup on the Ukrainian and Russian border. As
of this writing, it is estimated that nearly 500,000 Ukrainian civilians and troops have been killed
or wounded during the conflict (Cooper and Helene 2023). In addition to the loss of life and
violent crimes, there have been numerous intelligence sources stating Russian strikes on nonmilitary targets such as Ukrainian civilian infrastructure, places of worship, educational facilities,
and hospitals. This thesis uses spatial dashboards to depict current data and figures of multiple
violations of international humanitarian law during the Russo-Ukrainian war such as war crimes,
crimes against humanity and genocide.
1.1 Background
On February 24, 2022, Russia launched a full-scale invasion of Ukraine from multiple
fronts to topple the Western-aligned government. Russia’s so-called “special military operation”
endured bombardments that targeted Ukrainian cities while Russian troops entered Ukraine from
Russia, Belarus, and the Black Sea (Eichensehr 2022). Throughout the war, the Ukrainian
civilian population has suffered horrific attacks, loss of life, and damage to critical infrastructure
(Levy and Leaning 2022). These attacks have caused the displacement of more than 7.1 million

2
people and directly led to the largest humanitarian crisis in Europe since the Second World War
(Levy and Leaning 2022).
The historical relationship between Russia and Ukraine dates more than a thousand years
ago to when Kyiv was the center of Kyivan Rus the first Slavic state (Conant 2023). The grand
prince of Kyiv Volodymyr the Great accepted the Orthodox Christian faith in 988 A.D. (Conant
2023). This moment in history is what current Russian Leader Vladimir Putin declares as when
the Russians and Ukrainians became one people (Conant 2023). Although the Russian narrative
is that of unity and collaboration, Russia has subjected Ukraine to decades of abuse and
occupation.
In 1793 Ukraine was annexed by the Russian Empire and endured a policy known as
Russification where it was forbidden to use and study the Ukrainian language, and Ukrainians
were forced to convert to Russian Orthodox (Conant 2023). In the early 1900s, slightly over a
hundred years later, Ukraine suffered one of its darkest periods. Following the Communist
Revolution of Russia in 1917, Ukraine fought a devastating civil war before being absorbed into
the Soviet Union. While Ukraine was a member of the Soviet Union, it was one of the most
powerful and populated republics within the Union. (Masters 2023). In addition to having a large
population, Ukraine was the Soviet Union’s major hub of agricultural production, defense
industrial production, and military facilities like the Black Sea Fleet (Masters 2023). Although
Ukraine was a major contributor to the Soviet Union’s power, Soviet Dictator Joseph Stalin
orchestrated a national famine in the 1930s that resulted in the starvation and deaths of millions
of Ukrainians (Conant 2023). Following this famine, the Soviet Union relocated thousands of
Russians to repopulate the eastern region of Ukraine with Russian influence (Conant 2023). This
settlement of Russians in Eastern Ukraine created a divide in culture that can still be seen today.

3
After the Soviet Union’s collapse in 1991, Ukraine became an independent state but the
transition to Western democracy proved to be challenging. National pride was not as present in
eastern Ukrainians as it was in Ukrainians in the West. While Western Ukrainians were
embracing the governmental shift toward democracy and Western culture many Ukrainians in
the East longed for the stability and culture of the Soviet Union (Conant 2023). This divide
between the eastern and the western parts of Ukraine can be seen in the results of the presidential
elections in 2004 and 2010. This political alignment proved to come to a head in the Russian
military operations in Ukraine in 2014.
In February 2014 unidentified men began occupying key facilities and checkpoints in the
Crimean Peninsula (Pifer 2020). These professional-looking soldiers were dubbed “Little Green
Men” by the Ukrainian public as they did not bear a country's flag. After these troops secured the
entire Crimean Peninsula, the Russian Federation claimed that these were Russian troops (Pifer
2020). Following this claim the Russians conducted a rigged referendum for citizens to vote to
return Crimea to Russian control (Pifer 2020). This illegal referendum passed in March 2014 and
led to the illegal annexation of Ukrainian Crimea to Russia. Following this annexation, Russianbacked separatists began operating in Eastern Ukraine’s Donbas region which resulted in the
declarations of the Russian-backed People’s Republics of Luhansk and Donetsk (Conant 2023).
The tension caused by these events existed from the militarized buildup of Russian forces on the
Ukrainian border in 2021 and 2022 to the full-scale invasion of Ukraine in February 2022.
1.2 International Humanitarian Law
International humanitarian law in the form it is accepted today was established following
the horrors the world endured during the Second World War. The Geneva Convention of 1949
sought to protect victims of war. Additional rules were added to the Geneva Convention in 1977

4
with aid from the International Committee of The Red Cross. International humanitarian law
establishes rules that focus on limiting the effects of armed conflicts for humanitarian reasons
(UN 2024a). These laws protect individuals who are no longer considered to be participating in
the conflict and forbid means and methods of warfare. People these laws seek to protect include
humanitarian effects for civilian populations, sick or injured combatants, and prisoners of war
(UN 2024a). These laws establish a standard agreement between states’ militarized interactions.
1.2.1 War Crimes
War crimes establish a framework for the laws by which armed conflicts are conducted.
The Geneva Conventions in 1949 following the mass death and destruction of the Second World
War sought to establish rules to protect people who were not or no longer acting in the armed
conflict (UN 2024b). Article 8 of the Rome Statute classifies War Crimes as a deliberate attack
committed as a component of a scheme or policy on a large-scale employment of such crimes
(UN 2024b). To classify as war crimes these crimes must take place in the circumstances of
armed conflict (UN 2024b). Examples of war crimes as established by the UN are intentionally
directing attacks against civilian populations or individuals, intentionally directing attacks
toward civilian objects and infrastructure, intentionally targeting humanitarian efforts,
intentionally conducting attacks with the knowledge that such an attack causes loss of life or
injure civilians, and attacking or bombarding buildings dedicated to religion, education, art,
science, monuments, or hospitals (UN 2024b).
1.2.2 Crimes Against Humanity
It is unknown the exact origin of the use of the phrase crimes against humanity. Some
State that crimes against humanity were first seen in scholarly writings referring to atrocities
associated with European colonialism (UN 2024c). Others have pointed to the 1915 declaration

5
by France, Great Britain, and Russia to end the killing of Armenians by the Ottoman Empire as
the origin of the word concerning international crimes (UN 2024c). To prevent crimes against
humanity has become an established standard of International Law. Article 7 of the Rome Statute
of ICC states that Crimes Against Humanity occurs when a violent act is knowingly carried out
in connection to a widespread or systemic attack that targets a civilian population (UN 2024c).
Examples of crimes against humanity as established by the UN are murder, extermination,
enslavement, deportation or forcible transfer of populations, imprisonment, torture, rape,
enforced prostitution, forced pregnancy, enforced disappearance of persons, the crime of
apartheid, or other inhumane acts (UN 2024c).
1.2.3 Genocide
The word genocide was first used by a Polish lawyer in his 1944 book discussing the
Nazi occupation of Europe. The word consists of a combination of the Greek word for “race” or
“tribe” and the Latin word for “killing” (UN 2024d). This word was created to discuss the
systemic killing of the Jewish people by the Nazi party as well as historical instances to eradicate
a specific group of people (UN 2024d). genocide was later recognized as a crime under
international Law in 1946 by the United Nations. Article II of the Geneva Convention and
Article 6 of the Rome Statute of ICC states that genocide occurs when any of the following acts
are committed with intent to destroy, in whole or in part, a national, ethnical, racial, or religious
group (UN 2024d). Examples of genocide, as established by the UN, are forcibly transferring
children of a group to another group, targeted killings of members of a group, causing serious
physical or mental harm to members of a group, deliberately inflicting on a group situation of
life to cause physical elimination of part of the whole of the group, imposing situations to
prevent births within the group (UN 2024d).

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1.2.4 Violations of International Humanitarian Law in Ukraine
Since the full-scale invasion of Ukraine, there have been mass reports of violations of
international humanitarian law (IHL) committed by Russia. The Russian military has committed
acts that fall within the jurisdiction of war crimes, crimes against humanity, and genocide. The
human suffering of civilians is mounting as the result of Russia’s lack of respect for basic human
rights and principles of humanitarian law (UN OHCHR 2024a). As of the writing of this thesis,
The Office of the United Nations High Commissioner for Human Rights (OHCHR) estimates
that 11,520 civilians have died, 23,640 civilians have been injured, and 6.6 million refugees from
Ukraine have been registered globally (UN OHCHR 2024b). Widespread violence and
destruction have been recorded throughout the Russo-Ukrainian War with over 140 states calling
for the end of Russian aggression.
1.3 Study Area
The study area for this research is the country and specific cities of Ukraine. Figure 1
shows an aerial map of the oblast and country boundaries of Ukraine with a drop shadow effect
to make the study area more visible.

7
Figure 1. Study Area – Ukraine
According to the United States Central Intelligence Agency (CIA), the country of
Ukraine is approximately 603,550 sq km with 579,330 sq km of land and 24,220 sq km of water
(CIA 2024). Ukraine’s territory is located in Eastern Europe with bordering countries of Russia
to the east Poland, Romania, and Moldova to the west, and the Black Sea and the Sea of Azov to
the south. As of the writing of this section, approximately 43,133 sq km, or roughly 7.1% of
Ukraine’s territory, is Russian-occupied (CIA 2024). The work within this thesis focuses on the
town of Bucha, the City of Mariupol, and areas in which Russian forces have occupied Ukraine.
These three locations were chosen to aid in depicting the occurrence of human suffering in the
three areas of focus war crimes, crimes against humanity, and genocide.

8
1.3.1 War Crimes Study Area
To research the occurrences of war crimes during the Russo-Ukrainian War this thesis
focuses on the Port City of Mariupol in the Donetsk Oblast Russia’s military operations in
Ukraine have drawn criticism from many countries calling for a cease-fire to prevent further
tragedies such as the war crimes that occurred during the Siege of Mariupol. The Siege of
Mariupol occurred from February 24, 2022 - May 20, 2022, in the Port City of Mariupol,
Donetsk Oblast (Farge 2024). During the two months, three weeks, and five-day Russian assaults
Ukrainian civilians suffered through heavy bombardments that targeted infrastructure such as
residential apartments, hospitals, education facilities, religious establishments, and electricity &
water infrastructure (Sabbagh 2024). Figure 2 depicts the major streets, buildings, and city
boundaries of the City of Mariupol in Ukraine.

9
Figure 2. Mariupol Study Area
1.3.2 Crimes Against Humanity Study Area
To research the occurrences of crimes against humanity during the Russo-Ukrainian War
this thesis focuses on the Town of Bucha in the Kyiv Oblast. Russia has justified its invasion by
claiming to bring freedom to the Ukrainian people. However, violent and horrific crimes
committed by Russian troops are present in towns occupied by Russian forces. The Ukrainian
city of Bucha was occupied by Russian forces from February 27, 2022, to March 31, 2022
(Zhukova 2024). Throughout the occupation of the city, Russian forces carried out mass
executions, interrogations/tortures, and rapes of Ukrainian civilians. After the withdrawal of
Russian troops on March 31, 2022, the crimes that Ukrainian civilians experienced were

10
uncovered (Shuster 2022). Ukrainian bodies were found strewn through the streets and makeshift
dungeons with bound hands (Shuster 2022). This reveal prompted international outrage and an
investigation from the United Nations. Figure 3 depicts the road system, buildings, and boundary
of Bucha in Ukraine.
Figure 3. Bucha Study Area
1.3.3 Genocide Study Area
To research the occurrences of genocide during the Russo-Ukrainian War this thesis
focuses on the territory wherein Russian forces have abducted civilians, notably of Ukrainian
children. Since the start of the Russo-Ukrainian War, around 20,000 children have reportedly
been taken (Revill 2024). These children are being taken and relocated to Russian foster homes,
technical schools, military training facilities, and re-education camps to turn them into Russian

11
citizens (Holligan 2024). Children who have been returned to Ukraine have exhibited serious
harm to their mental well-being. Figure 4 depicts the oblast boundaries, country boundaries, and
the furthest territorial gain made by Russian troops during the Russo-Ukrainian War.
Figure 4. Territory Height of Russian Military Study Area
1.4 Project Overview
The objective of this thesis is to develop a StoryMap depicting three violations of
international law such as war crimes, crimes against humanity, and genocide that were
committed by Russia during their invasion of Ukraine. Spatial data will be prepared and
uploaded to ArcGIS Online using ArcGIS Pro. Non-spatial data will be prepared using Microsoft
Excel and uploaded directly into ArcGIS Online. The interactive dashboards and StoryMap will
be developed using the ArcGIS Online platform. The final product of this thesis will be a
publicly available StoryMap discussing and depicting human suffering via violations of
international law.

12
1.4.1 Data Overview
The data used within this thesis is centered around violations of international law related
to war crimes, crimes against humanity, and genocide during the Russo-Ukrainian War. Data
focuses on three locations from the beginning of the war to the time of writing this paper. The
data used within this thesis articulates a specific type of violation of international humanitarian
law. The statistics that are used come directly from investigative sources or governmental
statements. Datasets consist of geospatial locations, atrocities count, actors, event types, fatality
counts, and several population breakdowns from the different locations. Additional data sets are
geographic boundaries of Ukraine such as oblast boundaries and city geographies. Specific
information on individual datasets is provided in the following sections.
1.5 Structure of Thesis
This Thesis includes a literature review, methodology, results, and discussion sections.
Chapter 2 provides a literature review on the importance of researching human rights violations
during wartime, other spatial investigations, and methods of spatially displaying this data.
Chapter 3 describes the data, and the methods employed to complete this thesis. Chapter 4
presents the results of the StoryMap and Dashboards created by completing the methods
described in this thesis. Chapter 5 discusses challenges and how future works can improve upon
the methodology.

13
Chapter 2 Related Work
This chapter examines how researchers attempt to understand and track human sufferings,
produce spatial datasets for humanitarian purposes, and what insights spatial visualizations
provide. Additionally, this chapter displays the current practices and challenges that exist within
responsively using spatial science for event tracking.
2.1 The Significance of Identifying and Alleviating Human Suffering
Armed conflicts and wars cultivate death and grief for people who endure and experience
them. International humanitarian law (IHL) seeks to establish the rules of what can and cannot be
done by fighting forces during wartime (International Committee of The Red Cross 2024). These
laws were instated to minimize human suffering and protect civilian populations and prisoners of
war (Amnesty International 2024). The primary agreement between nations was the 1949
Geneva Conventions which were established following the large-scale global conflict of World
War 2 (Amnesty International 2024). These rules of war state that combatant forces should not
deliberately target civilian populations. Militarized actors should minimize harm to civilian
structures such as residential buildings, educational institutions, and hospitals. IHL states that
crimes against humanity such as murder, extermination, forced movement/deportation, torture,
rape, and other forms of sexual violence during military operations (Amnesty International
2024).
Tracking violations of IHL such as war crimes, crimes against humanity, and genocide is
significant in the prosecution of war criminals. Diligent documentation of war crimes that occur
around the world leads to future prosecution of the assailants who oppress human rights (Horne
2023). Human rights do not disappear during armed conflicts and the suffering that civilian

14
populations experience must be documented to aid in the prevention of future agony and the
successful prosecution of the perpetrators (Horne 2023).
(ICC is governed by the international treaty called the Rome Statute and is one of the
authoritative courts that investigates and tries individuals who have been charged with the
harshest of crimes that are recognized by the international community (ICC 2024). These crimes
that the ICC investigates are war crimes, genocide, crimes against humanity, and the crime of
aggression. The ICC does not replace national courts but is meant to complement them by having
a broader ability to admit evidence (Jonathan and Harris 2018). The crimes that the ICC has
jurisdiction over are by their nature challenging to understand in both their inhumanity and their
complexity (Jonathan and Harris 2018). These types of crimes are difficult to document as they
can involve many actors who can enact human rights violations across large territories and
international boundaries. These investigations can take years and span over multiple locations to
be able to compile an abundant amount of proof to ensure a successful prosecution.
Since the mid-1800s, there have been two main lines of thought about human suffering in
wartime (Witt 2012). The first manner of viewing human suffering in wartime is that the
occurrence of suffering is inherently evil for humanity. The second perception of suffering sees it
as an inevitable occurrence and requires viewers to understand why suffering exists. The
combination of these two lines of thought shows there is value in alleviating the impact that war
and armed conflict on civilian populations by providing medical care and recognizing that their
loss is not undocumented (Rosa and Grant 2022).
This line of thinking aims to mitigate and alleviate the effects of suffering people in
wartime as a goal of external characters (Witt 2012). This stance is taken by the founder of the

15
Red Cross who sees any suffering of civilian populations during wartime as something that
should be prevented.
2.2 Spatial Investigations Related to Human Rights Violations
Spatial datasets provide a major societal opportunity for advancing and understanding
human rights violations. A significant portion of large datasets being created today has a spatial
component where locations are geographically situated (Venkatachalam 2023). The importance
of expanding abundant datasets for data analysis revolves around giving spatial sciences
abundant data points to study topics from several perspectives. Extensive datasets give decisionmakers various perspectives to break down real-world situations to enhance storytelling
capabilities. Spatial datasets of this caliber have been used in connection to save everyday
consumers time and money in their routing to and from retail locations (Lee and Kang 2015).
Having legible and abundant datasets and visualizations with spatial components enables Human
Rights researchers with the ability to dissect and interpret the space in which violations are
occurring.
Human Rights Watch (HRW) is an organization that investigates and reports on human
rights violations across the globe. HRW has utilized Geospatial data and visualizes to inform and
expand upon their reports (Human Rights Watch 2023). The HRW’s Digital Investigation Lab
(DIL) is responsible for making an ethical and accountable use of spatial data and modern
technologies to research human rights violations. DIL employs open-sourced spatial data
collection to conduct research geospatial analysis to document violations. DIL uses satellite
imagery to track the changes in locations over time, create 3D renders of buildings and locations
where violations occur, and data mining situations of arrest rates or deportations to draw
patterns.

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The American Association for the Advancement of Science (AAAS) provides a
comprehensive assessment of the use of geospatial technologies in the research of human rights
violations. The AAAS’s Scientific Responsibility, Human Rights, and Law Program (SRHRL) is
one of the world’s largest multidisciplinary organizations that address legal, ethical, and human
rights violations. The SRHRL conducts investigations into the effectiveness of differing
applications of science and engineering. Through their research, they determined that geospatial
technologies provide enormous potential in human rights violation documentation. By using
geospatial technologies analysts can generate data sets related to events in a study area that is
inaccessible to ground-based investigators due to security, legal, or logistical reasons (Jonathan
and Harris 2018). By mapping human rights violations researchers can assess the distribution of
events to determine if a pattern exists.
The AAAS within their assessment determined several limitations when using geospatial
data from sources such as governments, global organizations, private corporations, and nongovernmental organizations. These limitations are caused by the coverage or resolution,
governmental restrictions, ethical considerations, authenticity, and cost. Limitations vary based
on where the source of the data is coming from. While the ICC is investigating crimes the
discussion of evidence authenticity is often discussed. This was illustrated in the alleged war
crimes recorded in Sri Lanka where the perpetrators did not dispute the video evidence
authenticity but in hand claimed that the video was staged. In addition to data, the ICC tries to
obtain witness testimony to work with digital evidence (Jonathan and Harris 2018).
Location data is a strong aspect of digital journalism regarding how stories are created,
written, and understood. An emerging aspect of digital journalism is how it allows audiences or
users to interact with the story (Peters 2014). Narratives within spatial journalism can provide

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this interactivity while aiding readers in personalizing the story and situation being examined
(Peters 2014). Spatial journalism is created using data and information with a spatial capacity
connected to a social meaning through space, place, or location (Weiss 2014). This data is often
delivered in several aspects, from text, websites, videos, multimedia, and graphics (Weiss 2014).
This data should have the capability to be consumed by the general public in several forms, such
as digital, mobile, and physical (Weiss 2014). The ability to communicate a location or social
landscape is important to aid readers in understanding the significance of an event.
2.3 Spatial Data Storage, Dashboards, and Storytelling
Spatial data can be incredibly powerful and informative but without a way to prepare,
display, and provide context the data may fall flat. The software company Esri has created
several tools and resources that empower users to make impactful deliverables that provide
spatial context.
2.3.1 Esri ArcGIS Online
ArcGIS Online (AGOL) is Esri’s secure and private infrastructure for cloud-based
mapping and data storage solutions (Esri 2024). AGOL allows users to develop interactive webbased applications that can display geospatial insights. AGOL provides users with a single
platform where users can work with spatial data, make maps, analyze data, share results, and
collaborate with others (Esri 2024). AGOL is used to house the spatial data and to create web
maps that can be read and added to Esri applications to expand upon the geospatial data. Figure 5
depicts the AGOL content interface where data is stored within folders.

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Figure 5. AGOL Folder and Data Used
2.3.2 Esri Dashboards
Esri’s Dashboards provide users with the ability to display several pieces of spatial data
analytics on a single interactive page (Esri 2024). Dashboards are graphically designed webbased applications that display visualizations that work together on a single screen. Dashboards
present the capability to display spatial data in a map view with several data visualization
methods such as bar graphs, pie charts, and total sums of values. Dashboards offer a holistic
view of spatial data by providing major insights at a glance (Esri 2024).
Dashboards have been powerful tools in displaying and articulating the many
characteristics found within datasets. The implementation of a good Dashboard design can allow
users to combine several data sources into a single visualization that elaborates on data trends
(Orlovskyi and Kopp 2020). This incorporation of data allows for the expansion and
understanding of complex and unique data sets. An important characteristic of Dashboards for
spatial data is to show how multi-dimensional data can be (Lyer 2012). The importance of
displaying multi-dimensional spatial data is that the data can be incredibly deep with numerous

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variables that cannot be articulated in a single visualization. Dashboards allow users to expand
and display the multi-faceted data to elaborate on complex data points.
Spatial Dashboards were used by the Australian government to monitor how locations of
wildfires in South Whales have changed over time. Figure 6 and Figure 7 depict the Esri
Dashboard created by the Australian Government to display historic bushfire data. This research
sought to display the spatio-temporal changes in hotspot analysis of bushfires over southern
Australia. The importance of creating dashboards to display the results is to allow public access
for users to explore the data and directly interact with several different results (Michael and
Shirowzhan 2021). The importance of the Dashboard is to allow users to also interact and
understand the story that is being articulated. To further articulate the motives, methods, and
results of the research the Australian government produced an Esri StoryMap.
Figure 6. Fire Data Dashboard - Bushfire Data

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Figure 7. Fire Data Dashboard – Hot Spot Analysis Results
2.3.3 Esri StoryMaps
Esri produces ArcGIS StoryMaps which are web-based applications that infuse maps,
multiple forms of media, and text to create an informative story (Haynes 2023). Esri’s ArcGIS
StoryMap provides developers with a platform to inform audiences with spatial data via digital
storytelling. This platform allows for the combination of written text, spatial data, embedded
content, and data articulation to inform audiences of a situation. Figure 8 depicts part of the Esri
design page for cover and font options for StoryMaps.

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Figure 8. StoryMap Design Page
2.4 Spatial Applications of War and Human Tragedies
The American Battlefield Trust (ABT) created a spatially related StoryMap that displays
descriptions, locations, and outcomes of battles of the American Civil War and the American
Revolutionary War. These one-page StoryMap allows users to search for specific battles, read
detailed descriptions, see pictures of battles, and explore the spatial-temporal distribution of
when battles occurred. This StoryMap provides an easy to interpret map that displays locations
with the symbology depicting who won the battles and the size of the point showing how
historically significant the battle was. The left hand panel lists battles depicting the name, dates
of the battles, outcomes, state, picture, and description of the battle. Upon clicking on a specific
battle, the map pans to the location and expand the description of the battle. At the bottom of the
description, there is an external link to the ABT website where even more details of the battle
can be found such as how it ended, in context, before the battle, during the battle, aftermath, and
questions to consider of how this battle affected the overall war. Figure 9 depicts the Battles of
the American Civil War StoryMap zoomed into the State of Virginia.

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Figure 9. Battles of The American Civil War StoryMap
Cooper Thomas, a member of Esri’s StoryMap team created a StoryMap titled Bombing
Missions of the Vietnam War which is a visual record of the largest aerial bombardment in
human history. The StoryMap begins with setting the stage for the events discussed such as dates
for the war, total tons of munitions dropped, and the study area discussed. The StoryMap also
provides a detailed description of the United States Department of Defense (DOD) data and
where it was collected. The StoryMap provides users with a comprehensive understanding of
what types of planes were used during the Vietnam War, the number of missions, where
concentrations of bombings occurred, and what nations and military branches operated
throughout the country.

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Figure 10. Bombing Missions of the Vietnam War - flown by the United States
Cooper Thomas, a member of Esri’s StoryMap team created a StoryMap titled Mapping
Russia’s War on Ukraine which is a live map of territorial control to provide an up-to-date
overview of the situation on the ground. This StoryMap begins by establishing the Russian
invasion has been the largest and most destructive conflict in Europe since the Second World
War and how the Ukrainian people successfully repelled Russian forces in the West to Russia
reallocating their forces to the East. The StoryMap is updated daily to display the territory
controlled by Russia in Red and the reclaimed territory by Ukraine in Blue. The StoryMap
explains that the data itself is from the Institute of the Study of War (ISW) which is a
Washington DC based think tank. The StoryMap consists of seven sections and maps displaying
different aspects of the data collected by the ISW such as the big picture, Russian controlled
territory before February 24, 2022, Occupied Ukrainian territory, recent Russian advances,
recent Ukrainian counteroffensives, partisan actions behind the front lines, and putting the pieces
together. Figure 11 depicts all the different pieces of ISW data in the Putting the Pieces Together
section in the Mapping Russia’s War on Ukraine StoryMap.

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Figure 11. Putting the Pieces Together Section of Mapping Russia's War on Ukraine

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Chapter 3 Methods
This Chapter discusses the data and methods required for the completion of this thesis. The data
which is discussed is spatially related to the people and land that was been affected by the war in
Ukraine. This Chapter provides a detailed description of the data and process used in depicting
the occurrence of war crimes, crimes against humanity, and genocide in the Russ-Ukrainian War.
3.1 Methods Overview
The workflow to complete this case thesis requires the preparation and visualization of
spatially related data on violations of International Law. The identification of spatial data
requires research of sources of events connected to the three violations. Data preparation entails
preparing the identified data in a spatial format which can be rendered to inform users. The
visualization of this data is depicted in an Esri StoryMap with several Dashboards to give users
the ability to understand and explore the three violations of international law. Figure 12 depicts a
diagram of the workflow to complete this thesis.
Figure 12. Workflow Diagram

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3.2 War Crimes – Mariupol
This section describes the data and methodology for the development of the Dashboard
and StoryMap section on war crimes committed during the Siege of Mariupol. A combination of
spatial and non-spatial data was used. The first subsection enumerates the data used, the second
explains the steps taken in ArcGIS Pro and/or Microsoft Excel to prepare the data prior to
publication online, the third section describes the work done in AGOL to effectively map the
data, and the fourth section explains the steps to produce a AGOL Dashboard with the data and
the creation of a section on the topic in the final StoryMap.
3.2.1 Data for War Crimes – Mariupol
This section enumerates the data used on war crimes committed in Mariupol, including
the source of each data set, how each was acquired, and a description of the data as acquired. An
appendix itemizes these data sets.
3.2.1.1 Mariupol city boundary
The boundary polygon was downloaded from HDX and initially depicted every level of
administrative boundary. This layer was used to display the City of Mariupol to aid in visualizing
the geographic Study Area. This GeoJson titled “Subnational Administrative Boundaries”
contains boundaries for Country (ADM0), Oblasts (ADM1), Raions (ADM2), and Hromadas
(ADM3). GeoBoundaries produced the data for their global database of political administrative
boundaries. This database is an open license and contains standardized boundaries such as states
and counties for every country in the world (HDX 2024a). Figure 13 depicts the city outline
polygon of the City of Mariupol, Ukraine.

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Figure 13. Mariupol Boundary
3.2.1.2 Mariupol city building footprints
The building footprint polygons were downloaded from HDX as a polygon shapefile and
was imported into ArcGIS Pro. OpenStreetMap’s (OSM) building footprint polygons were used
to aid in visualizing the geographic setting of the city of Mariupol. OSM has roughly 6.8 million
records of building footprints within Ukraine (HDX 2024b). The data set was produced by
volunteer contributors within the Humanitarian OpenStreetMap Team (HOT). This makes data
quality a topic with the completeness of the dataset, accuracy of the data, and how up to date the
data is. This makes the data accurate and trustworthy to the extent that volunteers correctly
geofenced the buildings in an area. OSM includes an AI-mapping estimated 25% of all buildings

28
in Ukraine (HDX 2024b). Most of the residential buildings in Mariupol have been mapped but a
portion of industrial buildings appear to have been missing. The average age of the data within
the dataset is roughly three years (HDX 2024b). The Data within this thesis was downloaded
from HDX in the July 2024 update. Figure 14 depicts the OSM building polygons within the
City of Mariupol, Ukraine.
Figure 14. Mariupol OSM Building Footprints
3.2.1.3 Mariupol City Damaged Hospitals
This thesis utilizes OSM hospital campus outline polygons to aid in visualizing the geographic
setting of the city of Mariupol. The building footprint polygons were downloaded from HDX as
a polygon shapefile and were imported into ArcGIS Pro. This OSM feature displays healthcare

29
locations with classifications such as doctors, dentists, clinics, hospitals, and pharmacies (HDX
2024c). The data of medical campus boundaries appeared accurate when cross referencing other
datasets. The outline data within this thesis was downloaded from HDX in the July 2024 update.
The damaged classification comes from the damage assessment completed by HRW. Figure 15
depicts the OSM building polygons that are classified as healthcare facilities and damaged by
HRW within the City of Mariupol, Ukraine.
Figure 15. Mariupol OSM Damaged Hospital Building Footprints

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3.2.1.4 Mariupol City Damaged Education
This thesis utilizes OSM’s education building outline polygons to aid in visualizing the
geographic setting of the city of Mariupol. The damaged education building footprint polygons
were downloaded from HDX as a polygon shapefile and were imported into ArcGIS Pro. This
specific OSM feature displays education locations in Mariupol with Kindergarten, school,
college, and university classifications (HDX 2024d). The data on education campus boundaries
appeared accurate when cross referencing other datasets for education facilities. The outline data
within this thesis was downloaded from HDX in the July 2024 update. The damaged
classification comes from the damage assessment completed by HRW. Figure 16 depicts the
OSM building polygons that are classified as education facilities and damaged by HRW within
the City of Mariupol, Ukraine.

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Figure 16. Mariupol OSM Damaged Education Building Footprints
3.2.1.5 Mariupol City Power Lines
This thesis utilizes Open Infrastructure Map (OIM) Power Lines to aid in visualizing the
electric infrastructure of the city of Mariupol. Downloading this data directly from their webpage
produces a TileJson file. OIM is sourced from OSM’s database to display the world’s
infrastructure system (Open Infrastructure Map 2024a). With this data being collected by
volunteers it makes the data accurate to the extent that volunteers correctly geofenced the
infrastructure. OSM has identified and mapped 1,102 power plants and roughly 81,944 miles of
power lines (Open Infrastructure Map 2024b). The mapped electric infrastructure in Ukraine
OSM displays roughly sums to 51,391 Megawatts of power (Open Infrastructure Map 2024b).

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OIM provides users with the ability to view and download the world’s infrastructure data within
an extent that is not a direct feature in OSM (Open Infrastructure Map 2024a). Figure 17 depicts
the OIM Power Lines within the City of Mariupol, Ukraine.
Figure 17. Mariupol City Power Lines
3.2.1.6 Mariupol City Power Stations
This thesis utilizes Open Infrastructure Map (OIM) Power Stations to aid in visualizing
the locations of the power station infrastructure of the city of Mariupol. With this data being
collected by volunteers through OSM it makes the data accurate to the extent that volunteers
correctly geofenced the infrastructure. OSM has identified and mapped 1,102 power plants and
roughly 81,944 miles of power lines (Open Infrastructure Map 2024b). The mapped electric

33
infrastructure in Ukraine OSM displays roughly sums to 51,391 Megawatts of power (Open
Infrastructure Map 2024b). OIM provides users with the ability to view and download the
world’s infrastructure data which is not a direct feature in OSM (Open Infrastructure Map
2024a). Figure 18 depicts the OIM Power Stations points within the City of Mariupol, Ukraine.
Figure 18. Mariupol City Power Stations
3.2.1.7 Mariupol City Power Towers
This thesis utilizes Open Infrastructure Map’s (OIM) Power Towers to aid in visualizing
the locations of power Towers along the Power Lines infrastructure of the city of Mariupol. With
this data being collected by volunteers through OSM it makes the data accurate to the extent that
volunteers correctly geofenced the infrastructure. OSM has identified and mapped 1,102 power

34
plants and roughly 81,944 miles of power lines (Open Infrastructure Map 2024b). The mapped
electric infrastructure in Ukraine OSM displays roughly sums to 51,391 Megawatts of power
(Open Infrastructure Map 2024b). OIM provides users with the ability to view and download the
world’s infrastructure data which is not a direct feature in OSM (Open Infrastructure Map
2024a). Figure 19 depicts the OIM Power Tower points within the City of Mariupol, Ukraine.
Figure 19. Mariupol City Power Towers
3.2.1.8 Mariupol City Key Water Network
This thesis utilizes (OIM) Key Water Network lines to aid in visualizing the locations of
the major water infrastructure of the city of Mariupol. Downloading this data directly from their
webpage produces a TileJson file. The data contains a single key water network line that

35
transports water to the city is an underground water pipeline. The data does not provide a robust
water system infrastructure of water pipes from the filtration facilities to civilian infrastructure.
OIM is sourced from OSM’s database to display the world’s infrastructure system (Open
Infrastructure Map 2024a). With this data being collected by volunteers it makes the data
accurate to the extent that volunteers correctly geofenced the infrastructure. OIM provides users
with the ability to view and download the world’s infrastructure data which is not a direct feature
in OSM (Open Infrastructure Map 2024a). Figure 20 depicts the OIM Key Water Network
within the City of Mariupol, Ukraine.
Figure 20. Mariupol City Key Water Network

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3.2.1.9 Mariupol City Key Water Facilities
This thesis utilizes OIM data to display key water network facilities to aid in visualizing
the locations of the major water infrastructure of the city of Mariupol. Downloading this data
directly from their webpage produces a TileJson file. The data contains two water network
facilities that filter water to the city are called The Starokrymska filter stations. The data does not
provide a robust water system infrastructure of additional water storage facilities. OIM is sourced
from OSM’s database to display the world’s infrastructure system (Open Infrastructure Map
2024a). With this data being collected by volunteers it makes the data accurate to the extent that
volunteers correctly geofenced the infrastructure. OIM provides users with the ability to view
and download the world’s infrastructure data which is not a direct feature in OSM (Open
Infrastructure Map 2024a). The water network facilities that filter water to the city are called The
Starokrymska filter stations. Figure 21 depicts the OIM key water facilities within the city.

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Figure 21. Mariupol City Key Water Facilities
3.2.2 War Crimes Data Preparation
The war crimes data were prepared using ArcGIS Pro for data that contained a spatial
component and Microsoft Excel for data that did not contain a spatial component.
The data that was already in a spatial format was brought into ArcGIS Pro using the add
data button where all the required layers were selected and brought into the application. For
Microsoft Excel comma-separated values (CSV) that were not in spatial format but contained
latitude and longitude which could allow it to be converted into a spatial format was added to the
ArcGIS Pro document as a table. Then right clicking the table and converting the table to XY
format alters the table to a point feature using the latitude and longitude. Once all the data was

38
within the ArcGIS Pro document it was necessary to convert all the features to the same
coordinate system. Using the Project tool within ArcGIS Pro all features were converted to the
WGS 84 Web Mercator coordinate system. Once all features were in the same coordinate
system, The data was clipped to the Mariupol Boundary layer to only display data within the
study area. Once all the features were within the study area the data was ready to be shared with
AGOL.
The non-spatial data that was pulled from news articles were compiled within a single
Microsoft Excel document where each data point has its own column.
3.2.3 Data Publishing for War Crimes – Mariupol
Once the data related to war crimes was prepared it was uploaded to AGOL via two
methods depending on if the data contains a spatial characteristic.
Spatial data that exits in point, polygon, and line formats were uploaded directly from
ArcGIS Pro by right clicking the layer, hovering over Sharing, and then selecting Share as a Web
Layer. Within the Share as a Web Layer window sections such as Name, Summary, Tags, Layer
Type, Location, and Group Sharing. Every spatial layer is named and summarized according to
the data it represents, tagged with “WAKRIDGE”, marked as a feature layer, uploaded to the
user wakridge_USCSSI’s “Thesis – Part B” folder, and marked as shared with the organization.
Once all the appropriate fields are filled the button Publish is selected.
Non-spatial data that was prepared within Microsoft Excel was uploaded directly within
AGOL by selecting “New Item”, then “Your Device”, choosing the desired document, and
selecting “Upload”. The file was then opted to be uploaded and to create a hosted feature layer or
table. Next, the user confirms each field is assigned to the correct type i.e. String, Integer, or
Data. The location setting for this new feature is selected as “None” which states that this

39
Microsoft Excel file contains no location data, and the file is uploaded as a table. The following
page prompts users to provide sections such as Title, Folder, Tags, and Summary. The new
feature table is named and summarized as the table data for war crimes, tagged with
“WAKRIDGE”, and uploaded to the user wakridge_USCSSI’s “Thesis – Part B” Folder. Once
all the fields are filled out accordingly blue “Save” button is selected.
3.2.4 War Crimes Layers and Map Preparation in ArcGIS Online
Once the war crimes data is uploaded in AGOL it is time to create a Web Map called
“Mariupol – Web Map” which is later connected to the Dashboard. The first step to prepare the
war crimes Map within the New Map Viewer is to add all spatial related data by selecting the
“Layers” tab and then selecting “Add” to add in spatial data related to war crimes stored within
AGOL. To add the data tables the “Tables” tab is selected followed by the “Add Table” button to
add tables related to war crimes that are stored within AGOL. Once all the data was added it was
time to select how the spatial data would look by selecting the layer and followed by properties
to adjust the symbology.
The symbology selected is to aid in the expression the layer brings to the overall map
composition. The Mariupol boundary polygon was chosen to have a solid green and blue outline
with a high transparency fill so the layers within the study area take prominence. The building
polygons have a white stroke and a high transparent white fill to signify the peaceful and neutral
standing of civilian infrastructure. The damaged education facilities polygon has a solid red
outline and high transparent red fill which is to depict the violence directed toward a crucial
civilian infrastructure. Similarly to the education layer, the damaged hospitals layer polygon has
a solid orange outline and high transparent orange fill to communicate the violence inflicted on
this type of civilian infrastructure. The water infrastructure layers for pipes and filtration systems

40
are both a light blue color to communicate the commonly used color for water. The water
filtration facility is a white background point with a faucet and water symbol to aid in the
understanding that civilians lost access to clean drinking water. The power infrastructure layers
for substations, power lines, and power towers are all orange to communicate the electric current
of this infrastructure. The substations are depicted with a white point and an orange electric
symbol to show where civilian power is sourced. The power lines and power towers were both
orange with the lines being a solid orange line while the towers being an orange firefly
symbology to show electric energy.
After each layer has the appropriate symbology, each layer is configured to only display
important information within its pop-up. Lastly, the Basemap is selected by selecting the
“Basemap” tab and choosing “Dark Gray Canvas” as the Web Maps basemap. Once all data
layers, data tables, symbology selected, layers have been configured, and the basemap has been
selected it is time to save the war crimes Web Map by selecting the “Save and Open” tab
followed by “Save”.
3.2.5 War Crimes Dashboard and StoryMap Development
Once the Web Map is prepared with all the necessary data it is time for the Dashboard by
selecting “Create New App” followed by “Dashboards”. Next, a window opens where the title,
tags, summary, and folder location can be assigned. Once the dashboard was created it was time
to add elements by clicking on the circular button with a plus in the upper left corner. Once
selecting “Add Element” users are prompted to choose a location to place the desired elements.
The design of the war crimes Dashboard consists of eight different types of elements such as a
splash screen, map, five indicators, one table, one serial chart, one gauge, one pie chart, and one
embedded content in the form of a video. Splash screens are pages that populate before

41
displaying the product, allowing developers to display important notes to inform audiences of the
contents within the dashboard or explain how to use the dashboard. The map is the core of Esri
dashboard development and allows developers to embed an Esri Web Map that contains all the
spatial datasets and tables. Within Esri Dashboard development, Indicators are cards that show
numeric attributes of specific features and summarize statistical value. All indicators within the
War Crimes Dashboard use the table as source data and the value types are classified as a feature
with the value field being the desired data. The bottom text of the indicator displays the label of
the data displayed within the specific indicator. Each indicator has a unique icon that coordinates
with the specific data being shown. Tables within Esri’s dashboard development page tables
present data attributes in rows and columns to allow users to quickly examine values and specific
categories. The table within the War Crimes Dashboard is used to depict the list of major events
during the siege. The table type is a feature, and the value fields displayed are the dates and the
description. Serial charts within Esri dashboards can visualize one or more series of data points
along a horizontal axis and vertical axis. The Serial chart within the War Crimes Dashboard
depicts the sum of Armed Conflict Location and Event Data (ACLED) sub-event types. The
serial chart category was selected as a statistic count and numbers are shown from highest to
smallest. Gauges within Esri Dashboards allow developers to display a single metric of a
quantitative value from a feature numeric field or summary statistic. The gauge within the War
Crimes Dashboard was a half-circle and displayed the percentage of damaged infrastructure. Pie
charts within Esri dashboards are circular charts divided into sections for the proportional quality
of a feature. The pie chart depicted ACLED data to show the percentages of event types. Esri
dashboards allow developers to embed content such as images, videos, or other types of web
content. This dashboard displayed a YouTube video where the embedded content link URL was

42
used to display the city's destruction. Once all the desired elements were added to the dashboard
the spatial design was determined by placing the map in the middle and making all the elements
and spacing as equal as possible. Figure 22 depicts the Dashboard development process for the
war crimes Study Area. Once the Dashboard was fully developed it was time to embed the
Dashboard into the StoryMap along with a description of the crimes committed, event, and study
area.
Figure 22. War Crimes Dashboard Development
3.3 Crimes Against Humanity – Bucha
This section contains the methodology for the development of the crimes against
humanity Dashboard and StoryMap section. This section discusses the spatial and non-spatial
data used within the crimes against humanity section and how it was compiled, shared, stored,
and displayed within the final Dashboard and StoryMap.

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3.3.1 Crimes Against Humanity Data
This section enumerates the data used on crimes against humanity committed by Russian
forces during the occupation of Bucha, including the source of each data set, how each was
acquired, and a description of the data as acquired. An appendix itemizes these data sets.
3.3.1.1 Bucha city boundary
This thesis utilizes the Bucha town boundary to aid in visually displaying the area that
was occupied from February 27, 2022, to March 31, 2022. This polygon was determined by
searching for the town of Bucha in Google Maps and then manually geofencing the polygon
within ArcGIS Pro. Figure 23 depicts the polygon created by manually creating the feature
outline of Bucha, Ukraine.

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Figure 23. Bucha Boundary – Google
3.3.1.2 Bucha city bodies identified
This thesis utilizes field reports from The New York Times journalists on the locations of
bodies in Bucha to aid in depicting how the town was affected. This data was originally
published as a map displaying the location of bodies from the field reports research shortly after
the occupation in 2022. This data can be trusted as it was produced by eyewitness experience
from New York Times journalists. This data was replicated in Esri’s ArcGIS Pro by manually
creating a point feature where The New York Times plotted body locations. This dataset does not
provide a complete display of where bodies were discovered but it aids in understanding the
spatial distribution of crimes. Figure 24 depicts the Points where bodies were identified by New
York Times journalists in the town of Bucha, Ukraine.

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Figure 24. Bucha Bodied Identified (Source: The New York Times)
3.3.1.3 Bucha city building footprints
The building footprint polygons were downloaded from HDX as a polygon shapefile and
was imported into ArcGIS Pro. OpenStreetMap’s (OSM) building footprint polygons were used
to aid in visualizing the geographic setting of the town of Bucha. OSM has roughly 6.8 million
records of building footprints within Ukraine (HDX 2024b). The data set was produced by
volunteer contributors within the Humanitarian OpenStreetMap Team (HOT). This makes the
data accurate and trustworthy to the extent that volunteers correctly geofenced the buildings in an
area. OSM includes an AI-mapping estimated 25% of all buildings in Ukraine HDX 2024b). This
percentage of mapped buildings is apparent when looking at the town of Bucha. The
completeness of this dataset is questionable as many residential and commercial buildings are

46
missing from this dataset. The average age of the data within the dataset is roughly three years
(HDX 2024b). The Data within this thesis was downloaded from HDX in the July 2024 update.
Figure 25 depicts the OSM building polygons in the town of Bucha, Ukraine.
Figure 25. OSM Bucha Building Footprints
3.3.2 Crimes Against Humanity Data Preparation
The crimes against humanity data was prepared using both ArcGIS Pro for data that
contained a spatial component and Microsoft Excel for data that did not contain a spatial
component.
The data that was already spatially related was brought into ArcGIS Pro using the add
data button where all the required layers were selected and brought into the application. For
Microsoft Excel comma-separated values (CSV) that were not in spatial format but contained

47
latitude and longitude which could allow it to be converted into a spatial format was added to the
ArcGIS Pro document as a table. Then right clicking the table and converting the table to XY
format alters the table to a point feature in WGS 1984 coordinate system using the latitude and
longitude. Once all the data was within the ArcGIS Pro document it was necessary to convert all
the features to the same coordinate system. Using the Project tool within ArcGIS Pro all features
were converted to the WGS 1984 Web Mercator coordinate system. Once all features were in the
same coordinate system, The data was clipped to the Bucha boundary layer to only display data
within the study area. Once all the features were within the study area the data was ready to be
shared with AGOL.
The non-spatial data that was pulled from news articles were compiled within a single
Microsoft Excel document where each data point has its own column.
3.3.3 Crimes Against Humanity Data Publishing
Once the data related to crimes against humanity was prepared it was uploaded to AGOL
via two methods depending on if the data contains a spatial characteristic.
Spatial data that existed in point and polygon formats were uploaded directly from
ArcGIS Pro by right clicking the layer, hovering over Sharing, then selecting Share as a Web
Layer. Within the Share as a Web Layer window sections were filled out such as Name,
Summary, Tags, Layer Type, Location, and Group Sharing. Every spatial layer was named and
summarized according to the data it represented, tagged with “WAKRIDGE”, marked a feature
layer, uploaded to the user wakridge_USCSSI’s “Thesis – Part B” folder, and marked as shared
with the organization. After all the appropriate fields were filled out the button Publish was
selected.

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Non-spatial data was prepared within Microsoft Excel and then uploaded directly within
AGOL by using “New Item”, then “Your Device”, choosing the desired document, and selecting
“Upload”. The file was then opted to be uploaded and created a hosted feature layer or table.
Next, each field was assigned to the correct type i.e. String, Integer, or Data. The location setting
for the new feature was selected as “None” which stated that the Microsoft Excel file contained
no location data, and the file was uploaded as a table. The following page prompted the user to
provide a Title, Folder, Tags, and Summary. The new feature table was named and summarized
as the table data for crimes against humanity, tagged with “WAKRIDGE”, and uploaded to the
user wakridge_USCSSI’s “Thesis – Part B” Folder. Once all the fields were filled out
accordingly the blue “Save” button was selected.
3.3.4 Crimes Against Humanity Layers and Map Preparation in ArcGIS Online
Once the crimes against humanity data were uploaded in AGOL it was time to create a
Web Map “Crimes Against Humanity – Web Map” which was later connected to the Dashboard.
The first step was to prepare the crimes against humanity Map within the New Map Viewer to
add all spatial related data by selecting the “Layers” tab and then selecting “Add” to add in
spatial data related to crimes against humanity stored within AGOL. The data tables were added
using the “Tables” tab followed by the “Add Table” button to add tables related to crimes against
humanity that are stored within AGOL. Once all the data was added it was time to adjust how the
spatial data looked by selecting the layer followed by properties to adjust the symbology.
The symbology selected was to aid in the expression the layer brings to the overall map
composition. The town of Bucha boundary polygon was chosen to have a solid green and blue
outline with a high transparency fill so the layers within the study area take prominence. The
building polygons have a white stroke and a high transparent white fill to signify the peaceful

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and neutral standing of civilian infrastructure within the town. The locations where bodies have
been spatially mapped were shown as red and orange firefly points to make them as visible as
possible while communicating the horrific nature of the actions of the Russian military on the
people of Bucha.
After each layer was given the appropriate symbology, each layer was configured to only
display important information within its pop-up. Lastly, the Basemap was selected by selecting
the “Basemap” tab and choosing “Dark Gray Canvas” as the Web Maps basemap. Once all data
layers, data tables, symbology were selected, layers been configured, and the basemap selected it
was time to save the crimes against humanity Web Map by selecting the “Save and Open” tab
followed by “Save”.
3.3.5 Crimes Against Humanity Dashboard and StoryMap Development
Once the Web Map was prepared with all the necessary data it was time to create the
Dashboard by selecting “Create New App” followed by “Dashboards”. Next, the window opened
where the title, tags, summary, and folder location were assigned. Once the dashboard was
created it was time to add elements by clicking on the circular button with a plus in the upper left
corner. Once selecting “Add Element” a prompt to choose a location to place the desired
elements was displayed. The crimes against humanity dashboard design consisted of six
elements: seven indicators, two pie charts, one table, one serial chart, one gauge, and the data
from the web map. Splash screens were pages that populate before displaying the product,
allowing developers to display important notes to inform audiences of the contents within the
dashboard or explain how to use the dashboard. The map was the core of Esri dashboard
development and allowed developers to embed an Esri Web Map that contain all the spatial
datasets and tables. Within Esri Dashboard development, indicators are cards that show numeric

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attributes of specific features and summarize statistical value. The indicators within the Crimes
Against Humanity Dashboard are connected to the table as the source data and the value types
are classified as a feature with the value field being the desired data. The bottom text of the
indicator displayed the label of the data displayed within the specific indicator. Each indicator
has a unique icon that coordinates with the specific data being shown. Tables within Esri’s
dashboard development page tables present data attributes in rows and columns to allow users to
quickly examine values and specific categories. The table within the Crimes Against Humanity
Dashboard was used to depict the list of descriptions of how bodies were found in Bucha. The
table type is a feature, and the value fields displayed are descriptions. Serial charts within Esri
dashboards can visualize one or more series of data points along a horizontal axis and vertical
axis. Gauges within Esri dashboards allow developers to display a single metric of a quantitative
value from a feature numeric field or summary statistic. The gauge within the Crimes Against
Humanity Dashboard was a half-circle and displayed the percentage of mapped bodies within the
map extent. The serial chart within the Crimes Against Humanity Dashboard depicted the sum of
ACLED sub-event types. The serial chart category was selected as a statistic count and numbers
are shown from highest to smallest. Pie charts within Esri dashboards are circular charts divided
into sections for the proportional quality of a feature. One pie chart depicted ACLED data to
show the percentages of sub-event types. The second pie chart depicted the percent of natural vs
inflicted deaths on bodies discovered. Once all the desired elements were added to the dashboard
the spatial design was determined by placing the map in the middle and making all the elements
and spacing as equal as possible. Figure 26 depicts an Esri Dashboard being created to depict
crimes against humanity in Bucha, Ukraine. Once the crimes against humanity Dashboard was

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fully developed it was time to embed the dashboard into the StoryMap along with a description
of the crimes committed, events, and study area.
Figure 26. Crimes Against Humanity Dashboard Development
3.4 Genocide – Ukraine
This section contains the methodology for the development of the Genocide Dashboard
and StoryMap section. This section discusses the spatial and non-spatial data used within the
genocide section and how it was compiled, shared, stored, and displayed within the final
Dashboard and StoryMap.
3.4.1 Genocide data
This section enumerates the data used on genocide via the abduction and relocation of
Ukrainian children that occurred in Russian controlled territory in Ukraine, including the source
of each data set, how each was acquired, and a description of the data as acquired. An appendix
itemizes these data sets.

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3.4.1.1 Kidmapping
This thesis utilizes locations identified by Kidmapping as locations where children have
been and where there are high concentrations of children in Russia, Belarus, and occupied
Ukraine and Russia. This data was created using open sources such as news reports, social
media, and video sources (Kidmapping 2024). This data was collected by a group of volunteers
to provide parents, human rights activists, and volunteers data on possible locations where
children are and have been (Kidmapping 2024). This data was originally published on their
webpage with an interactive interface. The point data set includes 155 Locations where children
were located and 109 Locations where there were high concentrations of Ukrainian children.
Figure 27 depicts the Points where Ukrainian children have been identified by Kidmapping.
Figure 27. Locations where Ukrainian Children were abducted to – Kidmapping

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3.4.1.2 Re-education camps and military facilities for children
This thesis utilizes locations of identified re-education maps and military training
facilities in Russia and occupied Ukraine. This data was created by volunteers using open
sources and was originally published as a custom Google Maps KML file (Rubryka 2024). The
point data set includes 45 children’s re-education camps locations and 12 military training
facilities. Figure 28 depicts the Points where Re-education camps and military facilities for
Ukrainian children have been identified.
Figure 28. Re-Education Camps and Military Facilities for Children – Rubtyka

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3.4.1.3 ACLED abduction event data
This thesis includes ACLED to aid in displaying the visual distribution of abductions of
the civilian population by Russian forces in the Russo-Ukrainian War. The ACLED data was
downloaded directly from their website as a table with columns for latitude and longitude.
ACLED is an independent non-profit organization that collects and analyzes spatial data on
violent conflicts globally (ACLED 2024). ACLED’s team tracks data such as actors, spatial
locations, fatalities, and event types (ACLED 2024). This section of the thesis focuses on the
event type related to reported civilian abductions across Ukraine. Figure 29 depicts the
distribution of abduction data from the escalation of the Russo-Ukrainian on February 24, 2022.
Figure 29. ACLED Civilian Abduction Data

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3.4.1.4 Oblast boundaries
The oblast boundary polygon was downloaded from HDX portal as a GeoJson containing
Ukraine’s 24 oblasts. This thesis depicts the oblast boundaries of Ukraine to provide a spatial
reference for viewers while looking at the dashboard. GeoBoundaries produced the data for
their global database of political administrative boundaries. This database is an open license and
contains standardized boundaries such as states and counties for every country in the world
(HDX 2024). In addition to providing spatial context to viewers in the dashboard, it allows users
to see the spatial distribution of ACLED abduction and disappearance data points. Figure 30
depicts the oblast boundaries.
Figure 30. Oblast Boundaries – HDX

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3.4.2 Genocide Data Preparation
The genocide data was prepared using both ArcGIS Pro for data that contained a spatial
component and Microsoft Excel for data that did not contain a spatial component.
The data that was already spatially related was brought into ArcGIS Pro using the add
data button where all the required layers were selected and brought into the application. For
Microsoft Excel comma-separated values (CSV) that were not in spatial format but contained
latitude and longitude which could allow it to be converted into a spatial format was added to the
ArcGIS Pro document as a table. Then right clicking the table and converting the table to XY
format alters the table to a point feature using the latitude and longitude. Once all the data was
within the ArcGIS Pro document it was necessary to convert all the features to the same
coordinate system. Using the Project tool within ArcGIS Pro all features were converted to the
WGS 84 Web Mercator coordinate system. Once all features are in the same coordinate system,
they are ready to be shared with AGOL.
The non-spatial data that was pulled from news articles were compiled within a single
Microsoft Excel document where each data point has its own column.
3.4.3 Genocide Data Publishing
Once the data related to genocide was prepared it was uploaded to AGOL via two
methods depending on whether the data contained a spatial characteristic.
Spatial data that exits in point and polygon formats are uploaded directly from ArcGIS
Pro by right clicking the layer, hovering over Sharing, then selecting Share as a Web Layer.
Within the Share as a Web Layer window sections such as Name, Summary, Tags, Layer Type,
Location, and Group Sharing. Every spatial layer is named and summarized according to the data
it represents, tagged with “WAKRIDGE”, marked as a feature layer, uploaded to the user

57
wakridge_USCSSI’s “Thesis – Part B” folder, and marked as shared with the organization. Once
all the appropriate fields are filled the button Publish is selected.
Non-spatial data that was prepared within Microsoft Excel is uploaded directly within
AGOL by selecting “New Item”, then “Your Device”, choosing the desired document, and
selecting “Upload”. The file is then opted to be uploaded and to create a hosted feature layer or
table. Next, the user confirms each field is assigned to the correct type i.e. String, Integer, or
Data. The location setting for this new feature is selected as “None” which states that this
Microsoft Excel file contains no location data, and the file is uploaded as a table. The following
page prompts users to provide sections such as Title, Folder, Tags, and Summary. The new
feature table is named and summarized as the table data for genocide, tagged with
“WAKRIDGE”, and uploaded to the user wakridge_USCSSI’s “Thesis – Part B” Folder. Once
all the fields are filled out accordingly blue “Save” button is selected.
3.4.4 Genocide Layers and Map Preparation in ArcGIS Online
Once the genocide data was uploaded in AGOL it was time to create a Web Map “Bucha
– Web Map” which is later connected to the Dashboard. The first step to prepare the genocide
map within the New Map Viewer is to add all spatial-related data by selecting the “Layers” tab
and then selecting “Add” to add in spatial data related to genocide stored within AGOL. To add
in the data tables the “Tables” tab is selected followed by the “Add Table” button to add in tables
related to genocide that are stored within AGOL. Once all the data was added it was time to
select how the spatial data would look by selecting the layer and followed by properties to adjust
the symbology.
The symbology selected is to aid in the expression the layer brings to the overall map
composition. The country of Ukraine boundary polygon was chosen to have a solid white outline

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with an empty fill, so the boundary is communicated. The oblast boundaries are the next
boundary with a thin slightly transparent outline to communicate the boundaries without
competing with the national boundaries. The next layer to aid viewers in understanding the study
area is the total height of Russian control which is displayed in transparent red grassland effect to
not take away from the point data but provide a visual understanding. The point data is
symbolized to communicate the two sides of the data with the ACLED data showing where they
were abducted and the kidmapping and open-source datasets showing where children have been
taken. The ACLED point data is displayed using a pink firefly to communicate the emotion of
sadness and loss. The location of the kidmapping and open-sourced data is symbolized in a cool
color. The two kidmapping data points are shown as purple firefly points for where high
concentrations of children likely are and as blue firefly points to show where children have been
at some point. The open-sourced data is symbolized as green firefly points for re-education
facilities and as yellow firefly points for military training facilities. These colors for locations of
abducted children are to communicate the hope that by knowing their location they may one day
be reunited with their family in Ukraine or other parts of the world.
After each layer has the appropriate symbology, each layer is configured to display
important information within its pop-up. Lastly, the Basemap is selected by selecting the
“Basemap” tab and choosing “Dark Gray Canvas” as the Web Maps basemap. Once all data
layers, data tables, symbology have been selected, layers have been configured, and the basemap
has been selected it is time to save the genocide Web Map by selecting the “Save and Open” tab
followed by “Save”.

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3.4.5 Genocide Dashboard and StoryMap Development
Once the Web Map is prepared with all the necessary data it is time for the Dashboard by
selecting “Create New App” followed by “Dashboards”. Next, a window opens where the title,
tags, summary, and folder location can be assigned. Once the dashboard was created it was time
to add elements by clicking on the circular button with a plus in the upper left corner. Once
selecting “Add Element” users are prompted to choose a location to place the desired elements.
The design of the genocide Dashboard consists of six different elements such as seven indicators,
four lists, one table, one pie chart, one bar graph, and the data from the web map. Splash screens
are pages that populate before displaying the product, allowing developers to display important
notes to inform audiences of the contents within the dashboard or explain how to use the
dashboard. The map is the core of Esri dashboard development and allows developers to embed
an Esri Web Map that contains all the spatial datasets and tables. Within Esri Dashboard
development, Indicators are cards that show numeric attributes of specific features and
summarize statistical value. All indicators within the Genocide Dashboard use the table as source
data and the value types are classified as a feature with the value field being the desired data. The
bottom text of the indicator displays the label of the data displayed within the specific indicator.
Each indicator has a unique icon that coordinates with the specific data being shown. Lists are
used to show features as rows and the symbology of a specific layer. The lists within the
Genocide Dashboard are filtered to only display the specific type of location. This is achieved by
having the filter equal to the specific value that is wanted to be shown. Tables within Esri’s
dashboard development page tables present data attributes in rows and columns to allow users to
quickly examine values and specific categories. The table within the Genocide Dashboard was
used to depict the list of locations of ACLED abduction data. The table type is a feature, and the
value fields displayed are the oblast, description, and source. Serial charts within Esri dashboards

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can visualize one or more series of data points along a horizontal axis and vertical axis. The
Serial chart within the Genocide Dashboard depicts the sum of ACLED abductions and
disappearances by year. The serial chart category was selected as a statistic count and numbers
are shown from lowest to highest year. Pie charts within Esri dashboards are circular charts
divided into sections for the proportional quality of a feature. The pie chart depicted ACLED
abduction and disappearances by the percent within each oblast seen within the map extent.
Figure 31 depicts the development of the genocide Dashboard within Esri’s AGOL. Once the
genocide Dashboard was completed, the genocide section of the Esri StoryMap was developed
providing context to the crimes and the event discussed.
Figure 31. Development of Genocide Dashboard

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Chapter 4 Results
This chapter provides an overview of the Human Suffering During Wartime StoryMap. displays
the results from running workflow pieces discussed in the methods chapter of this thesis. This
methodology successfully produced dashboards and a StoryMap that successfully explains and
depicts events where human rights violations occurred in the Russo-Ukrainian War. The link for
the StoryMap can be accessed by following the link provided. - StoryMap Link
4.1 Human Suffering During Wartime StoryMap Section
The StoryMap that is developed for this thesis contains multiple sections each diving into
the definitions of the violations of human suffering, locations in Ukraine which has experienced
this type of human suffering, spatial data, and statistics of researched and created datasets. This
allows users time to understand the type of suffering being discussed and the.
Figure 32. Human Suffering During Wartime StoryMap Cover

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Human suffering within the constraints of this thesis is defined at the beginning of the
StoryMap. This definition prepares readers for the topic before discussing and displaying the
data related to war crimes, crimes against humanity, and genocide. This was achieved by having
Human Suffering During Wartime sections that define IHL and how it was applicable within the
thesis. Figure 33 depicts the header and introduction to the thesis to provide context to readers.
Figure 33. Human Suffering During Wartime Section
4.2 War Crimes StoryMap Section
The war crimes section of the StoryMap contains a section on a written description of
war crimes as defined by the United Nations, a description of the Siege of Mariupol in 2022,
images of the Siege of Mariupol, and the Dashboard depicting spatial and non-spatial data of the
Siege of Mariupol.
4.2.1 War Crimes StoryMap Context
Before displaying the spatial data related to war crimes within the dashboard there is a
section that describes war crimes as how they are defined by the UN and how they apply to the

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study area chosen. The definition of war crimes is accompanied by a list of six examples of war
crimes defined by the UN. Figure 34 depicts the initial view of the war crimes Section of the
Human Suffering During Wartime StoryMap.
Figure 34. War Crimes Section of StoryMap
4.2.2 War Crimes StoryMap Study Area
After Scrolling past the UN definitions viewers see a description of the Siege of Mariupol
to provide informative context of the event and why it’s relative to this crime. After scrolling
past the historical context, seven images of the Siege of Mariupol are displayed to aid in visually

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understanding the spatial data within the dashboard. Figure 35 depicts the initial view of the war
crimes Section of the Human Suffering During Wartime StoryMap.
Figure 35. War Crimes Study Area Section of StoryMap
4.2.3 War Crimes StoryMap Dashboard
The war crimes Dashboard focuses on the loss of life and the destructive effect the battle
had on civilian infrastructure. The design of the StoryMap allows for the filtration of spatial data
based on the desired infrastructure type. The filter for infrastructure type can be found in the
upper right-hand corner of the Dashboard users can select options such as water infrastructure,
electric infrastructure, damaged education, and damaged medical facilities. The design of the
Dashboard places the map in the center and flows from the upper left corner to the bottom right.
The dashboards read from the initial population to the events that occurred during the siege to the
destruction that happened due to the Russian attacks.
All the elements within the War Crimes Dashboard are connected to the war crimes Web
Map and communicate different data points. The table of general stats of the siege of Mariupol is

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used within all of the five indicators and the gauge. These indicators and gauges depicted display
the total population before the war, death toll estimates, new grave estimates, hospital facilities
damaged, education facilities damaged, and the percent of civilian infrastructure reported to have
been damaged. The table of key events is depicted within a list feature within the dashboard to
display the date and description of the key events that occurred during the siege. The ACLED
data is connected to the serial chart and the pie the percent of key events and the number of subevents that occurred during the siege. All spatial data within the web map such as water
infrastructure, electric infrastructure, damaged hospitals, and damaged education facilities can be
toggled on and off by using the filter stating select infrastructure type in the upper right corner.
Both the Mariupol city and building footprints within the web map are there to provide visual
context for viewers. Figure 36 depicts the final war crimes Dashboard that can be found within
the final StoryMap.
Figure 36. War Crimes Dashboard Final

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4.3 Crimes Against Humanity StoryMap Section
The crimes against humanity section of the StoryMap contains a section on a written
description of crimes against humanity as defined by the United Nations, a description of the
Russian occupation of Bucha in 2022, images of the aftermath of the Bucha Massacre, and the
Dashboard depicting spatial and non-spatial data of the Bucha Massacre.
4.3.1 Crimes Against Humanity Context
Before displaying the spatial data related to crimes against humanity within the
dashboard there is a section that describes crimes against humanity as how they are defined by
the UN and how they apply to the town of Bucha. The definition of crimes against humanity is
accompanied by a list of eleven examples of crimes against humanity defined by the UN. Figure
37 depicts the initial view of the Crimes Against Humanity Section of the Human Suffering
During Wartime StoryMap.
Figure 37. Crimes Against Humanity Section of StoryMap

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4.3.2 Crimes Against StoryMap Study Area
After scrolling past the UN definitions viewers see a description of the Bucha Massacre
to provide informative context of the event and why it is relative to this crime. After scrolling
past the historical context, six images of the aftermath of the Bucha Massacre are displayed to
aid in visually understanding the spatial data within the dashboard. Figure 38 depicts the study
area and description of the Bucha Massacre within the Crimes Against Humanity Section of the
StoryMap.
Figure 38. Crimes Against Humanity Study Area Section of StoryMap
4.3.3 Crimes Against Humanity Dashboard
The final spatial dashboard that was created or the Crime Against Humanity Dashboard
communicated the graphic events that occurred in Bucha. The dashboard was designed to have
the map in the center of the page and for users to start in the top left and continue through the
facts displayed in the dashboard. The map contained the Bucha boundary, OSM building
footprints, and locations where bodies were discovered. The upper left corner displayed the

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number of bodies that were recovered. Next viewers should look at the spatially related locations
of where bodies were discovered such as the indicator, percent, and table which update based on
the map extent. Below the spatially located body data, there is the percent chart of cause of
death. Besides this chart, there are several data points of stats on the number of people who
remain missing, the number of children killed, and a single event of sexual violence that
occurred. Next, the viewers can see the number of people who remained within the city during
the occupation in the upper right followed by the ACLED event data shown in both pie charts
and graphs.
All the elements within the Crimes Against Humanity Dashboard are connected to the
crimes against humanity Web Map and communicate different data points. The data table that
contains general stats of the events that occurred during the occupation was used in six of the
seven indicators such as the bodies recovered, people remaining missing, children killed,
pregnancies, and the number of people who remained within Bucha during the occupation. The
mapped body locations within the map extent communicate to the indicator that displays the
number of bodies, the percent of mapped bodies, and the description of the mapped body within
the map extent. The cause of death data is used within a pie chart to depict the percent cause of
death on bodies recorded whether it be natural or inflicted upon them. The ACLED data that
depicts events that occur during the occupation are used to display a pie chart of the percent of
events and a bar graph of sub-events. The building and town boundary data is used to provide
visual context for viewers. Figure 39 depicts the initial view of the Crimes Against Humanity
Dashboard that is within the StoryMap.

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Figure 39. Crimes Against Humanity Dashboard Final
4.4 Genocide StoryMap Section
The genocide section of the StoryMap contains a section on a written description of
genocide as defined by the United Nations, a description of Russia’s abduction of Ukrainian
Children from their initial invasion in 2022 to the present, images of Ukrainian children, and the
dashboard depicting spatial and non-spatial data of the abduction and possible locations where
Ukrainian children are being housed within Russia.
4.4.1 Genocide Context
Before displaying the spatial data related to crimes against humanity within the
dashboard there is a section that describes crimes against humanity as how they are defined by
the UN. The definition of crimes against humanity is accompanied by a list of eleven examples
of crimes against humanity defined by the UN. Figure 40 depicts the initial view of the Crimes
Against Humanity Section of the Human Suffering During Wartime StoryMap.

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Figure 40. Genocide Section of StoryMap
4.4.2 Genocide StoryMap Study Area
After scrolling past the UN definitions viewers see a description of the abduction and relocations of Ukrainian children to provide informative context of the event and why it is relative
to this crime. After scrolling past the historical context, seven images of Ukrainian children are
displayed to aid in visually understanding the spatial data within the dashboard. Figure 41
depicts the study area and description of the situation of abdications and relocations of Ukrainian
children within the genocide section of the StoryMap.

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Figure 41. Genocide Study Area Section of StoryMap
4.4.3 Genocide Dashboard
This spatial data display provides end users with an easy-to-interpret final product of
genocide via the abduction and relocation of children during the Russo-Ukrainian War. The
dashboard has the map with spatial data placed in the middle of the dashboard with the oblast
boundaries, Russian troop furthest territorial control, ACLED abduction data, re-education
camps, military training facilities, locations where children have been, and locations where
children likely are. The data that surrounds the map is separated to display two sides of the
abduction and the locations of the children. The left-hand side of the dashboard focused on the
number of children abducted, the number of children returned, and where the children and people
have been abducted from using the ACLED data as the focus. This side of the dashboard
displayed a table of the locations and descriptions of abduction points in both a table and a pie
chart. In the middle right below the map, there is a bar graph showing the number of reported
abductions that were recorded for each year by ACLED. The right-hand side of the dashboard

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displays the locations where Ukrainian children have been relocated with indicators and lists.
Both the ACLED data and the location of children datasets are connected to the extent of the
map and update stats accordingly.
All the elements within the Genocide Dashboard are connected to the genocide Web Map
and communicate different data points. The general table of data related to child abductions is
displayed within two indicators showing the estimated number of children abducted and the
number of children who have been returned to their families in Ukraine or other parts of the
world. The ACLED Data is depicted within the web map and is connected to the indicator of the
number of events, the table of the description of events, the pie chart of the oblasts, and the
occurrence of abductions or disappearances by year which are all updated based upon the map
extent. The Kidmapping data is displayed in the web map and is connected to two indicators and
lists of data within the extent showing locations where children have been and locations where
children most likely are located. The data displaying locations of children’s re-education
facilities and military training facilities is displayed within the web map and is connected to two
indicators and lists of titles that update based on the map extent. The total Russian territorial
gain, oblasts, and country boundaries are included in this web map to provide context to the
viewers. Figure 42 depicts the initial view of the genocide Dashboard that is embedded within
the StoryMap.

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Figure 42. Genocide Dashboard Final

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Chapter 5 Discussion
This chapter concludes the thesis with a discussion of the final projects, limitations, challenges,
and potential future work.
5.1 Finished Product
The target audience of this work consists of academics and the public, where they can
learn about the atrocities that occurred in Ukraine and how spatial journalism can be used as an
effective tool for storytelling. The spatial storytelling element of this thesis provided a platform
that elaborated on atrocities that occurred during the war in Ukraine. By elaborating on these
atrocities, the StoryMap entices viewers to consider how human suffering is not isolated to this
event but is occurring in many conflicts around the world. Spatially tracking suffering by
documenting violations of international humanitarian law is necessary for humanity to
understand the atrocity, seek justice, and memorize those who were lost. Through this
understanding, comes the recognition that suffering is not an isolated event but exists wherever
human rights violations occur. This thesis achieved the objective of developing a StoryMap with
embedded dashboards that depict human suffering during the Russo-Ukrainian War. The
StoryMap consists of five sections such as defining human suffering during wartime, war crimes,
crimes against humanity, genocide, and epilogue.
5.2 Limitations and Challenges
Creating an application that discusses human atrocities was difficult to produce due to the
horrific subject matter. The themes and facts related to this thesis contain some of the worst acts
that humans can inflict upon one another. The seriousness of these acts and the topics discussed
created pressure to provide the most accurate, informative, and respectful StoryMap possible.

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However, the feeling of accurately displaying data related to human atrocities and providing
victims with dignity was a challenge.
5.2.1 Data
The main limitation when it came to data is that the Russo-Ukrainian war is still ongoing
during the completion of this thesis. This means that counts and data are as accurate as possible
as of the completion of this thesis. Accurate counts and datasets are currently being updated as
human rights violations within Ukraine are investigated. Data sources are cited within the
StoryMap because first-hand accounts vs second-hand accounts can hold significantly different
weights. Updated facts and data points will eventually be recorded to display true numbers or
numbers that are closer to accurate estimates.
This thesis only used open-source data to compile and produce the applications.
Authoritative sources are conducting thorough and classified investigations to be able to produce
accurate documentation of the atrocities. These official investigations are guaranteed to have
more accurate and complete datasets that are not open to the public. Not having only official data
makes the reliability of the data an important topic to discuss.
5.2.2 Human Dignity
Once the data was collected it became an emotional struggle to determine how to
appropriately display this data that both accurately spoke to the event and provided respect and
dignity to the victims. Word choice and how data was shown was an aspect that took significant
congestive thought. Text, indicator icons, images, and the type of data visualization were crucial
pieces in the creation of this thesis. It was important to elaborate on the horrors of this war
without seemingly glorifying the war itself. It was a conscious decision to not display the bodies
of victims of Russia’s aggression. It was not taken lightly when depicting data in a way that was

76
accurate and respectful. Colors needed to be mindful of the subject matter and the data could not
be shown seemingly without purpose. All these aspects of depicting human suffering during
wartime took longer and were more of a mindful development than initially expected.
5.3 Future Work
Future work on this thesis could entail updating and streamlining data, expanding data,
and researching more study areas related to IHL such as war crimes, crimes against humanity,
and genocide.
As time goes on more accurate data will be released which should be incorporated in
future works. It would be great if future works could incorporate fully authoritative sources from
investigative organizations such as national governments or the UN. Streamlined data can be
incorporated using GeoJSON so the application is updated without user interaction. These
updates could entail correcting valued stats to have more accurate numbers or appending new
data to track new and updated locations.
To expand the scope of this thesis and depict human suffering on a larger scale future
work should expand the study areas discussed within this thesis. There can be further work to
display more violations that are not discussed within this thesis. Future work can go more into
depth on examples of violations and tracking every single type of violation. This will ensure that
the entire picture of a single study area is being depicted. This could look like having more data
sets discussing all the aspects of a single crime.
Once the study areas within this specific thesis have been updated it would be appropriate
to expand to more study areas to widen the scope of the thesis. By looking for more study areas
where the three IHL violations during the Russo-Ukrainian War. This would entail having
multiple locations or events where war crimes have occurred. It would be interesting to have a

77
single interactive application where users can select locations throughout Ukraine and have as
detailed a description and dashboard for that event. This would further expand the goal of this
thesis to have a concise and informative location where people can become informed about
human suffering during wartime.

78
Appendix
Mariupol Spatial Data
Building footprints (All)
o Source: HDX
o Data type: Shapefile polygon
o URL: https://data.humdata.org/dataset/hotosm_ukr_buildings
Building footprints (Education)
o Source: HDX
o Data type: Shapefile polygon
o URL: https://data.humdata.org/dataset/hotosm_ukr_education_facilities
Building footprints (Health)
o Source: HDX
o Data type: Shapefile polygon
o URL: https://data.humdata.org/dataset/hotosm_ukr_health_facilities
Campus footprints (Damaged Education)
o Source: Human Rights Watch
o Data type: Shapefile polygon
o URL: https://github.com/HumanRightsWatch/Mariupol-data-2024
Campus footprints (Damaged Health)
o Source: Human Rights Watch
o Data type: Shapefile polygon
o URL: https://github.com/HumanRightsWatch/Mariupol-data-2024
City boundary
o Source: HDX
o Data type: Shapefile GeoJson
o URL: https://data.humdata.org/dataset/geoboundaries-admin-boundaries-for-ukraine
Power (Facilities)
o Source: Open Infrastructure Map
o Data type: GeoJson polygon
o URL: https://openinframap.org/#11.17/47.1358/37.5546/P
Power (Lines)
o Source: Open Infrastructure Map
o Data type: GeoJson line
o URL: https://openinframap.org/#11.17/47.1358/37.5546/P

79
Power (Towers)
o Source: Open Infrastructure Map
o Data type: GeoJson point
o URL: https://openinframap.org/#11.17/47.1358/37.5546/P
Waterways (Facilities)
o Source: Open Infrastructure Map
o Data type: GeoJson point
o URL: https://openinframap.org/#11.17/47.1358/37.5546/P
Waterways (Pipes)
o Source: Open Infrastructure Map
o Data type: GeoJson line
o URL: https://openinframap.org/#11.17/47.1358/37.5546/P
Mariupol Non-Spatial Data
Death toll estimate
o Source: Human Rights Watch
o Data type: Text
o URL: https://www.hrw.org/feature/russia-ukraine-war-mariupol/counting-the-dead
New graves identified
o Source: AP News
o Data type: Text
o URL: https://apnews.com/article/russia-ukraine-war-erasing-mariupol-methodologyf74b28016b8dea4b82811655f14931f2#:~:text=The%20Associated%20Press%20esti
mated%20at,the%20earth%20had%20been%20disturbed.
Population before war
o Source: The Economist
o Data type: Text
o URL: https://www.hrw.org/feature/russia-ukraine-war-mariupol/counting-the-dead
Ukraine conflict monitor
o Source: ACLED
o Data type: Table
o URL: https://acleddata.com/ukraine-conflict-monitor/
Ukraine drone footage shows before and after the invasion
o Source: YouTube
o Data type: Video
o URL: https://www.youtube.com/watch?v=kT6pV4rK5Gk

80
Bucha Spatial Data
Body locations
o Source: The Washington Post
o Data type: Image
o URL: https://x.com/nytimes/status/1513549965792100363
Bodies recovered
o Source: AP News
o Data type: Text
o URL: https://apnews.com/article/russia-ukraine-kyiv0aced874ccf203a5219ad37c2ed3f636#
Ukraine conflict monitor
o Source: ACLED
o Data type: Table
o URL: https://acleddata.com/ukraine-conflict-monitor/
Bucha Non-Spatial Data
Bodies recovered
o Source: AP News
o Data type: Text
o URL: https://apnews.com/article/russia-ukraine-kyiv0aced874ccf203a5219ad37c2ed3f636#:~:text=Municipal%20authorities%20say%204
58%20bodies,the%2033%2Dday%20Russian%20occupation
Cause of death
o Source: The Washington Post
o Data type: Text
o URL: https://www.washingtonpost.com/world/2022/08/08/ukraine-bucha-bodies/
Children killed
o Source: CNN
o Data type: Text
o URL: https://www.cnn.com/2022/05/03/europe/bucha-ukraine-russia-war-victimsintl-cmd/index.html
Civilians remained in town during the occupation
o Source: TIME
o Data type: Text
o URL: https://time.com/6166681/bucha-massacre-ukraine-dispatch/
People missing
o Source: Euromaiden Press

81
o Data type: Text
o URL: https://euromaidanpress.com/2024/03/31/ukrainian-police-many-still-missingbucha-civilian-death-toll-not-final-two-yearson/#:~:text=Ukrainian%20police%20report%20that%20after,of%20Ukrainian%20citi
zens%20remaining%20unidentified.
Sexual violence (Pregnancies Count)
o Source: BBC
o Data type: Text
o URL: https://www.bbc.com/news/world-europe-61071243
Sexual violence (Victim Count)
o Source: BBC
o Data type: Text
o URL: https://www.bbc.com/news/world-europe-61071243
Ukraine Spatial Data
Kid mapping
o Source: Kidmapping
o Data type: polygon point
o URL: https://mapping.kids/
Oblast boundary
o Source: HDX
o Data type: Shapefile Polygon
o URL: https://data.humdata.org/dataset/cod-ab-ukr
Re-education camps and military facilities for children
o Source: Rubtyka
o Data type: polygon point
o URL: https://rubryka.com/en/2023/03/29/v-ukrayini-stvoryly-mapu-taboriv-kudyrosiyany-vyvozyat-ukrayinskyh-ditej/
Ukraine conflict monitor
o Source: ACLED
o Data type: Table
o URL: https://acleddata.com/ukraine-conflict-monitor/
Ukraine Non-Spatial Data
Estimated number of abducted children
o Source: BBC
o Data type: Text
o URL: https://www.bbc.com/news/world-europe-68249102
Estimated number of children returned

82
o Source: BBC
o Data type: Text
o URL: https://www.bbc.com/news/world-europe-68249102

83
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Abstract (if available)

Abstract The Russo-Ukrainian War began with the large-scale invasion of Ukraine by Russian forces in the early morning of February 24, 2022. As the war continues, there have been widespread reports of violations of international humanitarian law with civilian populations being heavily impacted by this war. This thesis aims to inform readers about human suffering during the war in Ukraine and the use of spatial visualizations to convey events that contravene international humanitarian law. The three violations researched within this thesis include war crimes, crimes against humanity, and genocide. The study areas for these three sections are the city of Mariupol, the town of Bucha, and the Russian-occupied regions of Ukraine. The data is from publicly available datasets, authoritative news sources, the United Nations, the country of Ukraine, and Armed Conflict Location and Event Data. This thesis displays the occurrence of human tragedies such as civilian fatalities, explosions/remote strikes, battles, strategic developments, violence against civilians, targeting of medical facilities, targeting of educational facilities, occurrences of sexual violence, abducted persons, and damage to civilian infrastructure. The completed work of this thesis is published in an Esri StoryMap to articulate the history of the conflict and visually display the spatial data within a series of Dashboards. Further practices of researching and visualizing human atrocities affecting civilian populations, such as spatial journalism, need to be expanded within the realm of spatial sciences. Organizations seeking to relieve civilian populations' suffering during wartime must adopt and expand upon these practices. The preliminary results of this methodology successfully presented the occurrence of human suffering in a StoryMap via the thesis definition of the violation of international humanitarian law.

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Asset Metadata

Creator Akridge, William (author)

Core Title Human suffering during wartime: a StoryMap of violations of international law during the Russo-Ukrainian War

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Geographic Information Science and Technology

Degree Conferral Date 2024-12

Publication Date 11/22/2024

Defense Date 09/27/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag Crimes against humanity,dashboard,data journalism,Esri,Genocide,Geographic Information Science,geographic information science & technology,geospatial intelligence,GIS,human security,human suffering,international law,Russia,Russian-Ukrainian War,Russo-Ukrainian War,spatial journalism,storymap,Storytelling,Suffering,Ukraine,violations of international law,War,war crimes,wartime

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