# data[].attributes.body
Hello,My name is Tsuchiya Hibiki.

My hobby is watching movies.

I play soccer every week.

Nice to meet you.

# data[].attributes.body
Hello! I'm Yuya.

I'm a second year economic student.

I'm from Japan.🇯🇵

I love travel. Nice to meet you!!

# data[].attributes.body
I don't well english

My hobbies are watching and playing soccer. I also like cars very much. Nice to meet you.

# data[].attributes.body
Hi. I'm Youhei. I am a sophomore in the School of Engineering at Reitaku University.

I’m not very good at English, but I look forward to working with you.

# data[].attributes.headline
Mediterranean Migration Routes and Mortality, 2014–2024

# data[].attributes.subject
Mediterranean Migration Routes and Mortality, 2014–2024

# data[].attributes.body
We created a crisis map that tracks Mediterranean migration routes and migrant deaths between 2014 and 2024, against the backdrop of Frontex’s expanding mandate and budget. We mainly used GPS coordinates of the main Mediterranean migration routes, combined with data on deaths and disappearances recorded between 2014 and 2024. We divided this period into four phases to track how routes evolved over time. As Frontex’s presence and budget grew, from €143M in 2014 to €922M in 2024, crossings shifted away from the Eastern Mediterranean toward the Central and Western routes, which are significantly longer and more dangerous. The result is clear: fewer people attempted the crossing, but a greater proportion of them died. More border control didn’t make the sea safer but it redirected migrants onto deadlier paths.​​​​​​​​​​​​​​​​

Here is the link to the map ! https://maelbonneviale.wixsite.com/frontexbuster

Maelys, Mael, Lola, Laurine - Hitotsubashi University

# data[].attributes.attachment_link.title
Sciences Espace Poster Scientifique Affiche Gris Coloré Simple - 1

# data[].attributes.headline
US Import Risks and the Prevalence of Modern Slavery: A Global Supply Chain Map

# data[].attributes.subject
US Import Risks and the Prevalence of Modern Slavery: A Global Supply Chain Map

# data[].attributes.body
Background and Purpose

As the world’s largest economy, the United States currently faces the highest risk of importing goods produced using forced labor. This map explores the critical relationship between the volume of US imports and the prevalence of modern slavery across 13 exporting countries, focusing on the top five most valuable at-risk products.

According to estimates, nearly two-thirds of all forced labour cases are linked to global supply chains, particularly in lower-tier stages such as raw material extraction and early production processes. Because of this structure, understanding the importing risk is crucial. While goods are consumed in developed nations, the exploitation often occurs far beyond their borders. Currently, the US imports approximately US$169.6 billion worth of products that are considered at risk of being made using forced labor annually.

By visualizing these connections, this map aims to shed light on the reality of labor exploitation within global supply chains, serving as a starting point for discussing and developing effective countermeasures.

How to Read the Map

The visual elements on this map illustrate the connections between the US and exporting countries, as well as the severity of modern slavery in those regions.

Dots: Modern Slavery Prevalence and Trade Scale

Color: Represents the estimated prevalence of modern slavery per 1,000 population. Lighter colors indicate a lower prevalence, while darker colors indicate a higher prevalence.

Size: Represents the total import value of the at-risk products originating from that specific country.

Arches: Supply Chain Connections to the US

Color: Represents the top five imported at-risk products. The colors distinguish between electronics, fish, garments, textiles, and timber.

Thickness: Represents the scale of the trade. Thicker lines indicate a larger volume of goods flowing from the exporting country into the US.

Overlapping Elements: When the US imports multiple categories of at-risk products from a single country, the dots and arches will overlap. A higher degree of overlapping indicates that a country is deeply intertwined with US consumption across multiple high-risk sectors.

Data source: Walk Free, Global Slavery Index 2023 Dataset

Map: Kepler.gl

References:

https://www.walkfree.org/global-slavery-index/map/#mode=data:dimension=i:compare-country=USA

https://www.walkfree.org/global-slavery-index/country-studies/united-states/

by Rin Tanigaki, Hitotsubashi University

# data[].attributes.body
I created a map showing typhoons from 2023 to 2026. The Northern Hemisphere will experience more typhoons starting in September. However, in January, many typhoons in the Southern Hemisphere.

The closer you are to the sea, the more likely you are to be hit by typhoons.

sudo kuon

reitaku university

Index of /data/international-best-track-archive-for-climate-stewardship-ibtracs/v04r01/access/csv/

# data[].attributes.headline
Warnings from traffic accident-prone areas in Tokyo"

# data[].attributes.subject
Warnings from traffic accident-prone areas in Tokyo"

# data[].attributes.body
① Hidden danger in everyday life

Accidents don’t only happen in obviously dangerous places.
They occur more often on familiar roads where people feel most at ease.

② More movement, more risk

Accidents are not just about speed—they happen where paths intersect.
Where cars, cyclists, and pedestrians cross, risk naturally increases.

③ Risk changes with time

The same road can become a different place depending on the time of day.
As the flow of people increases, accidents begin to appear.

④ Not random, but clustered

Accidents may seem random, but they tend to cluster in specific areas.
There are hidden patterns behind where they occur.

⑤ The illusion of safety

Accidents are more common on familiar, comfortable streets than on roads that feel dangerous.
Risk hides not in fear, but in familiarity.

# data[].attributes.headline
The Impact on Japan if a Conflict Were to Break Out in Taiwan

# data[].attributes.subject
The Impact on Japan if a Conflict Were to Break Out in Taiwan

# data[].attributes.body
If a crisis were to arise in Taiwan, how would oil transport routes to Japan change? This website provides an interactive, map-based visualization comparing current sea lanes, the distribution of U.S. military bases in Japan, and alternative routes.

To be clear, this is not a political statement; I

have simply used Mapbox to visualize the potential oil crisis that could affect Japan if a conflict were to break out in Taiwan.

This is not to say that I am hoping for such a conflict.

Source

https://www.e-stat.go.jp/stat-search/files?page=1&layout=datalist&toukei=00700011&kikan=00700&tstat=000001149526&cycle=0&tclass1=000001241996&tclass2val=0

https://www.youtube.com/watch?v=bLqhe9n-axU&t=86s

Reitaku University

# data[].attributes.body
We researched global literacy rates, focusing in particular on gender disparities, which many people may not often have the opportunity to think about, and created a map based on our findings.

This was our first time creating a map like this, but through trial and error and by using computers, we were able to work together and complete it successfully.

We hope that not only high school and junior high school students, but also adults, will take an interest in this topic. Through this research, I realized that while I have been given the opportunity to enter university and engage in learning and research, there are still many people around the world who want to study or attend school but are unable to do so.

We created this map because we wanted as many people as possible to become aware of this reality.

Reitaku University, Faculty of International Studies, IEC Major

Shiraki Yuka

Takada Yui

# data[].attributes.headline
Travel Safety Map for Middle East region

# data[].attributes.subject
Travel Safety Map for Middle East region

# data[].attributes.body
This interactive web map visualizes the complex crisis in the Middle East as of 2026. It overlays two primary layers: the current conflict zones and regional travel risk levels.A choropleth map coloring each country based on the latest MOFA Ministry of Foreign Affairs travel advisories, ranging from Level 4 Evacuation Advice to Level 2 Avoid Non-Essential Travel.

# data[].attributes.body
This indicates the location where the Noto Peninsula earthquake occurred.

# data[].attributes.body
私たちはデータ集めからすべて初めて地図作りに挑戦しました。それも短時間でやりきりました。

まだまだ未熟なところもありますが私たちにとってとても有意義な時間で良い経験になりました。

この地図を作ることでどこで争いが起きているか、繰り返されているか、どの国が勢力を広げたかが一目でわかるようになります。

私たちの中のひとりが特に太平洋戦争について詳しく調べました。

We took on the challenge of creating a map entirely from scratch, beginning with data collection.

Although we are still inexperienced, we successfully completed the project within a short period.

This process was highly meaningful and provided us with an invaluable learning experience.

By creating this map, you can clearly see where conflicts occurred, where they were repeated, and how different countries expanded their influence over time.

# data[].attributes.headline
Map of Expected Damage from a Summit Eruption of Mount Fuji

# data[].attributes.subject
Map of Expected Damage from a Summit Eruption of Mount Fuji

# data[].attributes.body
This WebGIS map simulates damage predictions for an eruption at the summit of Mount Fuji. In addition to showing hazard zones like lava and pyroclastic flows, it allows users to dynamically simulate the spread of volcanic ash in real-time by adjusting wind direction and speed sliders. The default settings are based on long-term meteorological statistics (average wind speed of 12 m/s blowing east-southeast). While these typical conditions show a low risk of ash fall for the Reitaku University area, users can adjust the sliders to simulate southwesterly winds. This makes it easy to instantly visualize and analyze worst-case scenarios where volcanic ash severely impacts the university campus.

# data[].attributes.body
We created an interactive map to help visualize the 2016 Kumamoto Earthquake.

It highlights the epicenter, the most severely affected areas, and key locations impacted by the disaster, making the scale of the damage easier to understand.

# data[].attributes.headline
Every eco energy plants all over the world

# data[].attributes.subject
Every eco energy plants all over the world

# data[].attributes.body
Starting from the conflict between Iran and the U.S., we decided to shift our perspective on the war. Considering the current situation where oil transportation is being blocked, we thought about what positive elements might emerge and realized that it could further accelerate the advancement of eco-friendly energy. Accordingly, we gathered data from power plants worldwide, specifically filtering for renewable energy data, and categorized them by type. By investigating which countries utilize which types of power generation and their respective production capacities, we explored eco-friendly power plants that could serve as substitutes for oil.

Reitaku University

HAN JUNHEE

KIM YUA

# data[].attributes.attachment_link.readable_text
Aw snap! Google Earth isn't supported on your browser. You may need to update your browser or use a different browser. Please see our system requirements for more information. Chrome is a great choice and you can download it here.

Or if you're feeling adventurous, you can try Earth anyway by choosing an option below.

Learn more about Google Earth.

# data[].attributes.attachment_link.description
Aw snap! Google Earth isn't supported on your browser. You may need to update your browser or use a different browser. Please see our system requirements for more information. Chrome is a great choice and you can download it here. Or if you're feeling adventurous, you can try Earth anyway by choosing an option below.

# data[].attributes.headline
Number of Japanese company bases in each country and companies with bases in Japan

# data[].attributes.subject
Number of Japanese company bases in each country and companies with bases in Japan

# data[].attributes.body
I created a graph to show Japan's globalization rate, based on the number of Japanese company bases in various countries and the number of companies with bases in Japan.

The red line represents the number of Japanese company bases in each country, and the blue line represents the number of foreign companies with bases in Japan.

The number of Japanese company bases in each country is 1/10 due to size constraints, and in the case of China, it's even lower, at 1/10. These maps reveal that Japan has surprisingly many global companies, more than one might imagine.

# data[].attributes.body
We created a map that can display earthquake epicenters while showing changes over time.
By observing this map, we found that in some cases, several small earthquakes occur around an area before a major earthquake.

This phenomenon may provide clues for understanding the process leading up to large earthquakes. However, not all major earthquakes are preceded by foreshocks, and small earthquakes do not always lead to a larger one, making accurate prediction difficult at this stage.

Nevertheless, visualizing seismic activity on a time-based map can help with the early detection of unusual earthquake patterns and contribute to raising awareness about disaster prevention.

# data[].attributes.headline
Number of foreign nationals employed in Japan in fiscal year 2015

# data[].attributes.subject
Number of foreign nationals employed in Japan in fiscal year 2015

# data[].attributes.body
・This graph illustrates the number of foreign workers in Japan for the 2015 fiscal year.

Most of them came from countries close to Japan, such as those in Asia and Oceania.

However, I was surprised to find that there were also many foreign workers from countries farther away, such as the United States, Canada, United Kingdom, and Brazil.

・Here is the link to the map we created.

https://padlet.com/tsasao/2026-international-humanitarian-mapathon-9wu45lb9w1ctx1w4/wish/zV61Q6xnNmqbWO98

・Reitaku University

by

・Joe　Shimada

・Soichiro Kanbe

・Shion　Ogawa

・Tutti-

# data[].attributes.body
Link:https://earth.google.com/earth/d/1pu3Rw4tJ5EAuAfPpgwnIJasaO_8WkSIu?usp=sharing

We have created a map showing the damage caused by the Kumamoto Earthquake, focusing specifically on the area around Kumamoto Castle. Hover your cursor over a point to view detailed information.

# data[].attributes.attachment_link.readable_text
Aw snap! Google Earth isn't supported on your browser. You may need to update your browser or use a different browser. Please see our system requirements for more information. Chrome is a great choice and you can download it here.

Or if you're feeling adventurous, you can try Earth anyway by choosing an option below.

Learn more about Google Earth.

# data[].attributes.attachment_link.description
Aw snap! Google Earth isn't supported on your browser. You may need to update your browser or use a different browser. Please see our system requirements for more information. Chrome is a great choice and you can download it here. Or if you're feeling adventurous, you can try Earth anyway by choosing an option below.

# data[].attributes.body
This map shows earthquake activity in and around Japan from 2013 to 2026.
Each dot represents one earthquake recorded by the USGS.
The colors show the magnitude of the earthquakes: lighter colors mean weaker earthquakes, and darker colors mean stronger ones.

Most earthquakes are located along the Pacific coast of Japan.
There are fewer earthquakes on the Sea of Japan side.

This pattern is caused by the movement of tectonic plates.
Japan is located at the boundary of several plates, including the Pacific Plate and the Philippine Sea Plate.

Key Findings

Japan has many earthquakes every year.

Earthquakes are concentrated on the Pacific side.

Strong earthquakes happen less often, but they are very dangerous.

Earthquakes follow plate boundaries, not random locations.

I learned that earthquakes in Japan are not random, but happen mainly along plate boundaries. This helps us understand why Japan has many earthquakes.

# data[].attributes.body
Kazuo Flanagan submission

# data[].attributes.headline
Inequalities in access to health facilities in Morocco.

# data[].attributes.subject
Inequalities in access to health facilities in Morocco.

# data[].attributes.body
This map links the lack of health facilities per region to the indigenous background of the inhabitants.

# data[].attributes.headline
Changes in Water Deficits and Demographics in Khuzestan, Iran

# data[].attributes.subject
Changes in Water Deficits and Demographics in Khuzestan, Iran

# data[].attributes.body
I created a map showing the population growth rate and the climatic water deficit, which represents the annual cumulative evaporative demand exceeding available water. Although I could not find a clear correlation between the two, both factors indicate a relationship with the overall water situation in this region.

Datasets:

https://www.globaldamwatch.org/grand.

https://www.climatologylab.org/terraclimate.html.

by Mio from TUFS

# data[].attributes.body
This crisis map shows events that occurred in the Middle East.

# data[].attributes.wish_content.attachment_props.alternative_text
This crisis map shows events that occurred in the Middle East.

# data[].attributes.body
I’ lives in chiba funabasi city

I love ranen、peach、steak、etc…

My hobbies VideoGames、Bolling、collecting die-cast cars

I’m not good at English but i want to try my best!

# data[].attributes.body
Olinka Romano & Carmen Ortega.

We constructed a map that shows Violence in Mexico is not random or uniform, is territorially structural. The explanation for this  violence is that these are also areas with constant conflict between organized crime groups.

The reduction on homicides has been the main success metric on national security of the current government.  But the changes in the classification of murder data put this narrative into question. We homologate all the categories into four classes to draw better comparisons.

# data[].attributes.headline
Political violence in Colombia: crisis mapping in light of upcoming elections 

# data[].attributes.subject
Political violence in Colombia: crisis mapping in light of upcoming elections 

# data[].attributes.body
As Colombia approaches its presidential elections in May, we have developed a detailed map of the country that examines each department’s episodes of political violence, levels of multidimensional poverty, and the extent of organized crime infiltration to assess potential correlations. This tool can be highly valuable for local authorities, helping them identify hotspots and better understand the dynamics driving political violence. The results turned out to be quite surprising!!

Project by: Bianca Stel, José Sanchez and Myriam Farjallah

# data[].attributes.attachment_link.title
Political Violence, Organized Crime and Multidimensional Poverty in Colombia (2025–2026)

# data[].attributes.headline
Data Centers and Water Quality Impact Assessment in Japan

# data[].attributes.subject
Data Centers and Water Quality Impact Assessment in Japan

# data[].attributes.body
We chose this topic because data centers and their environmental impact, while not as dramatic as wars or natural disasters, represent a real and growing problem. Since generative AI took off in 2022, data centers have been built at a pace the world has never seen before. Japan, our case study, is one of the most data center-dense countries in Asia, and AI facilities are being built there at a rapid pace.

However, as we developed the project, we realized we could not map every environmental impact at once. We chose to focus on water because of data availability. At the same time, it is worth noting that how much water a data center consumes or what it discharges into nearby water bodies are not widely known. That invisibility is exactly what makes it worth studying.

Check out the map: bit.ly/Japandatacenterswaterquality
Created by: Charlotte, Julian, Kazuo, and Ririn from Hitotsubashi University.

# data[].attributes.attachment_link.title
Japan Data Centers and Water Quality Map.docx

# data[].attributes.headline
Gaza Post-Ceasefire: Displacement and Barriers to Humanitarian Aid Delivery

# data[].attributes.subject
Gaza Post-Ceasefire: Displacement and Barriers to Humanitarian Aid Delivery

# data[].attributes.body
Project mapping how 1.9 million displaced Gazans have been concentrated into under-resourced "safe zones," while humanitarian aid remains blocked at the border. Uses satellite imagery and UNOSAT building destruction data.

# data[].attributes.attachment_link.title
Gaza Post-Ceasefire: Displacement and Barriers to Humanitarian Aid Delivery

# data[].attributes.attachment_link.description
Crisis Spatial Analysis · Gaza Strip · 2025

# data[].attributes.headline
Powering the Margins: Decentralized Microgrid Suitability in Mindanao, Philippines

# data[].attributes.subject
Powering the Margins: Decentralized Microgrid Suitability in Mindanao, Philippines

# data[].attributes.body
In the wake of intensifying typhoons and seasonal flooding, many communities across Mindanao, Philippines, are plunged into prolonged darkness as the centralized power grid collapses under the strain of climate-induced disasters. This recurring crisis leaves geographically isolated "last-mile" communities not only without light but without the essential energy needed for healthcare, communication, and recovery.

The "Powering the Margins" map addresses this critical vulnerability by shifting the paradigm from fragile, centralized infrastructure to a decentralized resilience model. By identifying high-priority zones for community-led renewable microgrids, this serves as a data-driven roadmap to "light the way" for regions currently operating in the shadows of the main grid. Ultimately, this visualization transforms energy access from a centralized privilege into a localized, reliable right, providing a strategic blueprint for sustainable independence and equitable resilience across Mindanao.

The suitability index was developed through a Multi-Criteria Decision Matrix (MCDM) that integrates a high-resolution, open-source data stack: VIIRS Nighttime Lights to identify energy poverty (or "darkness"), scaling Global Solar and Wind Atlas data to quantify renewable potential, and calculating euclidean distance from OpenStreetMap power grid lines to measure isolation. By normalizing and weighting these layers, the analysis identifies "priority shadows" where the need for power is greatest and natural resources are most abundant. The final output is rendered in a Cyberpunk-inspired style, using a high-contrast neon heat map to visualize the transition from current darkness to future energy independence.

The analysis identifies three critical zones where decentralized microgrids are most viable and urgent, starting with Zamboanga del Norte and Zamboanga del Sur. These provinces emerge as high-priority areas because their geographic distance from major power hubs and rugged terrain result in extreme grid isolation, yet their peak solar irradiance offers a reliable, untapped energy source for community-owned solar hubs. Moving to the island's interior, the Bukidnon and Agusan del Sur Border represents a strategic wind corridor; while the high-altitude peaks are too steep for construction, the surrounding highland communities can utilize wind energy to maintain power even when main transmission lines in the lower valleys are damaged by landslides or storms. Finally, the Davao Occidental and Sarangani Coast display the most severe energy gaps, characterized by a near-total lack of illumination despite significant populations. Their southern position guarantees peak solar yield, presenting a clear opportunity for immediate intervention to achieve energy independence.

Kepler - https://kepler.gl/demo/map?mapUrl=https://dl.dropboxusercontent.com/scl/fi/xoywxpfdyt3yj5iqrohoq/keplergl_cicwqcr.json?rlkey=kssqtp5uwjr20h4ica3fdhugh&dl=0

by:

• Prexy Dechos – University of Science and Technology of Southern Philippines (USTP)

• Patricia Anne Bacala – University of Science and Technology of Southern Philippines (USTP)

• Sophia Therese Flores – Caraga State University (CSU)

# data[].attributes.body
The map compares population distribution in Fukushima before and after the 2011 Great East Japan Earthquake and the Fukushima Daiichi nuclear disaster. Areas closest to the nuclear exclusion zone along the eastern coast experienced some of the greatest population decline due to evacuation, long-term displacement, and concerns over radiation exposure. In contrast, larger inland cities such as Fukushima City and Koriyama remained population centres and, in some cases, have absorbed displaced residents from surrounding areas.

The callout map specifically highlights the exclusion zones, which, despite gradual downsizing over the past decade, still persist in certain areas where the population has not yet fully recovered to pre-disaster levels.

The purpose of this map is not only to show the long-term demographic impact of the disaster, but also to provide a clearer understanding of where people live now. In the event of another emergency, updated population distribution maps can help planners and emergency services identify areas of higher population density, improve evacuation planning, and allocate resources more effectively. It also demonstrates the importance of continuing to map population change after disasters, as settlement patterns can shift for many years after the initial event.

Created by Yuki & Isablla & Kokona

from Hitotsubashi University

# data[].attributes.body
Hello!My name is Yuka!

I’m belong to IEC.

My hobby is listening to music.

I love ONEOKROCK and RADWINPS.

I am good at piano. I have played the piano for 15 years.

# data[].attributes.body
Hi everyone! Im Han from South Korea. This is my first time joining Mapathon. Im really grateful to have wonderful time with you guys. Thanks!

# data[].attributes.body
Hi my name is YUA!

I came from Korea.

I like spicy food.

I want to make many friends.

# data[].attributes.body
Hi! I’m Yayoi. I’m first grade in JIC.

I like to listen and sing JPOP songs.

This is my first time for joining to Mapathon. I’m nervous now so please speak to me kindly…!

# data[].attributes.body
Tokyo is one of the safest cities in the world. That said, complacency isn’t wisdom. Crimes do occur. So, our team discovered that crimes mostly occur on the streets. But it's not just location that matters; time is also important. Evenings and nights are considered the most violent periods. So, we came up with the idea of ​​creating a crisis map that not only shows crime statistics but also their connection to infrastructure, as well as solutions for avoiding such situations - Night Walk Safety Map. For details, see the attached file. To see the interactive map, click on the link: https://stellular-donut-948da4.netlify.app/

The task was completed by Dmitrii Artemev, Banri Otsuki, Shotaro Nakayama, Wang Yichen, Zhang Fan. Hitotsubashi University, 2026.

# data[].attributes.body
My name is Rui!

I'm in the business administration department

I'm the CEO of Eguino, Inc

I love AI.

I am good at building an AI agent team.

Nice to meet you!

# data[].attributes.body
hi everyone

reitaku student engineering first year

nice to meet you

# data[].attributes.body
Hi!! I’m Satoshi!

I from Niigata, But I live in Chiba!

Nice to meet you!!!!!!!!🫶

# data[].attributes.body
Hi everyone!

I belong to IEC!

I’m Takada Yui!

My hobby is listening to music!

For example,Fujii Kaze and Suchmos!

# data[].attributes.body
Hello. My name is Takahisa.

My hobby is watching anime.

# data[].attributes.body
Wasssup my name is Ikin and I’m so glad to join this special event, I’m looking forward to get some new friends. WOW

🤩🤩🔥🔥

# data[].attributes.body
Hi!

I'm Miki.

Nice to meet you.

# data[].attributes.body
Hello, I’m Ayu.

First year student .

I’m from Philippines.

Nice to meet you

# data[].attributes.body
Hello! I’m Sakura.

My favorite food is donut.

I have a dog. He is very cute 🩷🩷

nice to meet you!

# data[].attributes.body
Hiiii! I’m Sho and I came from China.

I am easy-going and friendly.

I like playing the piano and drawing.

I am easy to talk with.

I hope I can make good friends with everyone.

Nice to meet you~

# data[].attributes.body
Engineering first year

Nice to meet you

# data[].attributes.body
We researched the frequency and locations of earthquakes in Japan and plotted them on a map.

This made it easier to identify trends.

# data[].attributes.headline
Too Hot to Handle: The Global Health Crisis due to Rising Temperatures

# data[].attributes.subject
Too Hot to Handle: The Global Health Crisis due to Rising Temperatures

# data[].attributes.body
As the increase in global temperatures have become the world's deadliest extreme weather event, rising temperatures are exacerbating global health challenges. This extra burden placed upon our healthcare systems makes it imperative that we mitigate and adapt to our changing climate. Using both historical and predictive models, this project illustrates how we can address global warming to create more resilient public health systems.

# data[].attributes.attachment_link.description
Harness the power of maps to tell stories that matter. ArcGIS StoryMaps has everything you need to create remarkable stories that give your maps meaning.

# data[].attributes.headline
Natural Flood Coastal Protection: Mapping Coral Reefs

# data[].attributes.subject
Natural Flood Coastal Protection: Mapping Coral Reefs

# data[].attributes.body
We created this project to highlight unmapped coral reef areas—ecosystems that play a crucial role in protecting coastal communities from flooding.

Our map identifies several regions in Africa and South America, and also introduces ongoing efforts working to document and map these habitats.

We believe that expanding mapping efforts can support coral reef conservation and help address challenges such as coral bleaching.

Created by Mario & Akari

Hitotsubashi University

# data[].attributes.headline
COVID-19 PATHOGEN SPREAD  Plague Inc. Style

# data[].attributes.subject
COVID-19 PATHOGEN SPREAD  Plague Inc. Style

# data[].attributes.body
This displays the cumulative number of COVID-19 cases by country, broken down by month.

The timeline display allows you to slide the time bar to see the cumulative number of cases at a given point in time.

You can view the number of cases by clicking the circle above each country.

(Please open in Google Earth)

# data[].attributes.attachment_link.title
COVID-19 PATHOGEN SPREAD  Plague Inc. Style

# data[].attributes.headline
Conflict and Nighttime Lights in Nigeria

# data[].attributes.subject
Conflict and Nighttime Lights in Nigeria

# data[].attributes.body
Hello!

This analysis examines the relationship between conflict events and economic activity in Nigeria using ACLED conflict data and nighttime light data as a proxy for economic activity.

# data[].attributes.attachment_link.title
Conflict and Nighttime Lights in Nigeria-Kokoro Furukawa

# data[].attributes.attachment_caption
We created this map because we believe it's necessary to check the safety of a country before traveling abroad.
This time, we've created safety maps for Asia and Africa.
The closer the color is to red, the more dangerous the country becomes (with the exception of North Korea).

# data[].attributes.headline
Finding the most ideal locations to get humanitarian aid into southern Lebanon StoryMap

# data[].attributes.subject
Finding the most ideal locations to get humanitarian aid into southern Lebanon StoryMap

# data[].attributes.body
Link: https://arcg.is/1PWjLL3

This project models a humanitarian logistics crisis. It assumes a "Total Outage" scenario where all permanent bridges over the Litani River in Lebanon have been destroyed, completely severing the heavy-vehicle road network and isolating the South Governorate from northern supply hubs (like Beirut). Using spatial network analysis, the project identifies the exact, mathematically optimal coordinates to deploy a limited number of temporary tactical bridges (like Bailey Bridges) to restore the highest volume of aid traffic as efficiently as possible.

USC SC Mappers Club

# data[].attributes.attachment_link.description
Identifying Crossing Sites for Humanitarian Aid Access in Southern Lebanon

# data[].attributes.body
Hi guys!! My name is Brendan, and I'm a student studying international studies and economics at UCI. I'm planning to study abroad in Japan next year, so please tell me what life in Japan is like!

# data[].attributes.headline
Israel-Lebanon conflicts impact on Lebanese healthcare

# data[].attributes.subject
Israel-Lebanon conflicts impact on Lebanese healthcare

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Interactive map link: https://felt.com/map/Clinics-at-the-Frontline-How-the-2023-2024-Israel-Lebanon-Conflict-is-Decimating-Healthcare-4I57FOlSQrm0xxaDViefTB?share=1&loc=34.5872,35.0357,8.93z

Map made by Khairin & Emmie from Tokyo University of Foreign Studies

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Clinics at the Frontline How the 2023-2024 Israel-Lebanon Conflict is Decimating Healthcare

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amazing work everyone! sending love from los angeles!

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Emery Nathaniel, University of Southern California

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This is an infographic on the famine in the Gaza Strip. The featured map details the state of agricultural land, health facilities, and food distribution site damages which impact the nutrition and public health of Palestine. Serving as a general overview of the state of the Gaza Strip, the infographic provides commentary on how the destruction of these features by what many human rights organizations have characterized as genocide has contributed to this famine and ongoing humanitarian crisis.

Emery Nathaniel, USC 2029

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Hi Everyone!!!!!! I'm Yengkai Yang from the University of California, Irvine and I'm excited to work on this map challenge :)

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Enhancing Evacuation Awareness through Tsunami Risk Visualization

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Enhancing Evacuation Awareness through Tsunami Risk Visualization

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We created this project to visualize tsunami inundation risk in Kanagawa Prefecture in the event of a major earthquake and to raise evacuation awareness among residents. On the map, areas expected to be flooded are color-coded by depth, ranging from 0.3 meters to over 10 meters, so that dangerous areas can be identified at a glance.

As a result, we found that the coastal areas of Miura City are particularly at risk. As a solution, we believe that residential development in these coastal areas should be restricted. Since evacuation requires moving to higher ground, it is also important to provide information on the nearest evacuation site from the user’s current location.

For future development, we would like to implement a function that automatically displays the nearest high ground when a location with a large inundation depth (especially 3–10 meters or more) is selected. We believe this will help evolve the hazard map into one that contributes more effectively to reducing casualties.

Also, I would like to collect data from Chile and Indonesia to create a more global map.

My map

https://silly-mochi-79651e.netlify.app/

References

https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-A40.html

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Thanks to Kristi!

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The Structure of Villages with Similar Social and Cultural Backgrounds in the Northern Part of Zambia

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Four Decades of Change in the Cagayan de Oro River

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Four Decades of Change in the Cagayan de Oro River

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This timelapse of the Cagayan de Oro River (1984–2026), created using Landsat imagery and QGIS, reveals decades of gradual but critical landscape change. Using a SWIR–NIR–Red composite, shifts in vegetation, water, and exposed land become clear—highlighting how natural systems respond to human pressure and environmental stress.

More than a visualization, this map tells a story of change over time, one that can inform better river management, disaster preparedness, and sustainable planning.

By understanding the past, we can better design a more resilient future.

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conflict in the democratic republic of Congo. areas marked are seriously affected by the ongoing conflict.

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Pakistan's flood risk & power distribution

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Pakistan's flood risk & power distribution

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Mappers:

Mirka Tapiala

Jesse Sivonen

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This video is about the crisis mapping of Emergency water resources in Koganei City especially for use in fire safety, showing the allocation location and density of the water resources in the certain area by visualise through Kepler.gl.

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Description

Russia’s invasion of Ukraine has evolved from a territorial assault into a campaign affecting civilians and daily life. As strike patterns shift over time towards civilian infrastructure, understanding where and how violence impacts populations becomes critical as Ukraine is increasingly dependent on external support for recovery. Our Ukraine Crisis Map transforms publicly available conflict data into a spatial tool designed to support humanitarian analysis and strategic decision making in the ongoing war. It maps over 38,000 recorded Russian strikes across Ukraine from February 2022 to April 2026, integrating data from the Armed Conflict Location & Event Data Project (ACLED) and the International Organization for Migration (IOM).

We layer incidents of strikes (sized by its fatality and colored by estimated target) and oblast level density and displacement counts in order to show how strikes have shifted. The sliding timeline allows humanitarian organizations, policy analysts, and researchers to visualize the spread of violence geographically.

Beyond visualization, the platform provides a tool for humanitarian workers to create spatial strategies for response, identify priority evacuation corridors, high-need aid zones, and optimal locations for medical and refugee infrastructure. Our goal is not only to document the crisis, but to inform where resources, protection, and intervention are most urgently needed.

Hitotsubashi University: Hitot-Mappers

Neil Dewan

Clara Wei

Yutaka Yamada

Natalie Ly

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Sending love from the Philippines! 😇😇😇😇😇

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Hello! Feye and Erika here from UPRI YouthMappers 🇵🇭

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Hello! Feye and Erika here from UPRI YouthMappers 🇵🇭

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South Sudan mapping crisis (Conflict and Flooding)

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South Sudan mapping crisis (Conflict and Flooding)

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Hello, the attached doc about the cases in South Sudan

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Hi, call me taka.

Im robotician.

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We undertook an initiative to visualize the current state of desertification. The impact of desertification is currently severe, and we aimed to raise public awareness by making its effects visible.

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I'm Kazuki.

I like play soccer!

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Department of Robotics, Faculty of Engineering, Reisawa University

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Hi !! I’m Hayori Sato and I’m a first-year student in the IEC!

I’m from Yamagata ⛰️🍒

Please call me “HAYO” !!

Nice to meet you!😽🌟

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My name is Nakamura Yurino, and I’m majoring in Information Student. I’d love it if you called me Rayu!

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I'm Taiga

I'm from ibaraki

I wanted to speak english so i came here

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Hi! My name is Keitaro Taka hashi. I'm learning about robotics at university! I just started, but snowboarding is my hobby!

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Hi, I’m a university student in Japan. I’m interested in learning new things and improving my skills every day.

I often listen to music.

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Hello my name is Yuna. Nice to meet you

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I'm Ayaka Ogura.

nice to meet you!!

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my name is Manaka Nikaido

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My name is Hinata Tanaka

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Hello, my name is Zuniga Chasti.

I like watching movies.

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My name is MomokaYamauchi.

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Hi! I'm Haruka! I'm Reitaku University Student Grade 1! I have a pen.

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my name is toyoda shuma

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hello my name is Hayato Hokari

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My name is Ishii Haruki.

Recently,I like walking

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My name is Daisuke

I like Aburasoba and Go to Sauna

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私の名前らいむです！マップ作りでたくさんの人を笑顔にしていきたいです！おねがいします！

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Conflict Events in Burkina Faso from 2016 to Today

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Conflict Events in Burkina Faso from 2016 to Today

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Conflict Events in Burkina Faso from 2016 to Today

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Hi,I’m Ryusei.Nice to meet you.

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Hi! My name is Keisuke Sato. I'm student at Tokyo university of foreign studies.

This is one of my favorite photo. After taking this, I was fined on the bus. Nice to meet you!

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Hi everyone! I'm Nha-Thinh Nguyen from the University of California, Irvine, and I'm really excited this year's map entries!

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Hello I am Mayuresh a graduate student from UCI👋👋

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Hi. I'm Ryo. I am student and also work at UCI transportation and distribution services. Nice to meet you guys!

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Saying hello from UC Irvine Transport Department 

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Saying hello from UC Irvine Transport Department 

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Hello, I am Christopher, a graduate student at the University of California Irvine.