GEOINT Match Strike
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A bonfire begins with a single match strike. The same rings true with novel ideas. Our first challenge highlighted the many ways that GEOINT data can be used. The results of the first Matchlight Challenge demonstrated that humanitarian issues are important to today's college students. The second challenge focused on the displacement of people based on various factors. The best submissions were able to use GEOINT data to show where the displacement was in a country of their choice and analyze the specifics of what caused the displacement for that specific region. The basic theme for the upcoming Hackathon is Food Security. During this event, teams will try to analyze various problems associated with food security for various countries. Teams will analyze these problems and seek data to support their findings. This Challenge will look at several predictors of food insecurity and provide quantitative evidence of what is the magnitude of that problem for a single area.
The Wright Brothers Institute in Dayton OH, the T-REX Innovation Center in St. Louis MO, and in conjunction with Riverside Research, have partnered to bring real-world examples to a series of university challenges. These challenges will highlight what can be done with focused geospatial datasets to shed light on current world problems.
This Matchlight Challenge series will culminate in a hackathon to be held in St. Louis on Sept 9-10th where competitors and colleagues can meet with other like-minded students to see what can be accomplished in a weekend of fun and exploration. Local companies and government agencies that work with GEOINT data, and teams from the National Geospatial Intelligence Agency will be present at the hackathon for students to talk about internships and other opportunities. Students will have access to unique databases and tools to address the problems presented. There will be a series of "lightning talks" to stimulate your thinking on how to use GEOINT data.
Based on the 1996 World Food Summit, food security is defined when all people, at all times, have physical and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life.
According to the Worldbank there are four main dimensions of food security:
- Physical availability of food
- Economic and physical access to food
- Food utilization
- Stability of the other three dimensions over time
Some datasets that could help with this challenge are:
AI and ML tools are emerging as powerful tools that can help with understanding large amounts of data. Within the last few years these tools have become available for the general public to use. Many are free to use. These tools can speed up research or challenge you to think of new approaches to old problems. How these tools are used can shed new insight unto the questions of food security. In this challenge we would like you to find out how these tools can help us get insights into the cause and effect of disruptors that may or may not affect food security. To get you started, here are just a few of the tools that have been used to summarize information, design new ways of seeing things, create videos of data, and inspire all of us to think differently. The following is just a small list of the tools that are available for free:
List of AI tools you can try for free
This challenge #3 is about how can we use any Free AI tools to analyze the impact of various factors/drivers/disruptors on food insecurity and predict how it will impact individual parts of a country. From the results of challenge #2, students have found that food scarcity is a major cause of human displacement. War causes shortages and supply disruptions. Fertilizer price hikes may cause farmers use less fertilizer and produce smaller yields leading to higher food costs. Drought and insects destroy crops leading to food scarcity, transportation disruptions and monopolies cause shortages and higher prices. The students can analyze any or all of these drivers of food scarcity( or others that you discover) that could lead to higher food prices that lead to food insecurity. Quantified relationships would be expected for the top submissions.
- Using these tools pick a country that you think these pressures on food supplies will impact the greatest number of people. Analyzing all of these factors and any other you discover for your selected country using the AI tools and your GEOINT data. Show what segments of the country will be impacted and to what extent. Is this a rich/poor divide or what factors drive the impacted areas. This can be highlighted in graphs, charts, geospatial representation, and any way that you can tell the story of the impacted populations in a clear and meaningful way. We are interested in how you are able to show that any or all of these factors will drive what percentage of the population into food insecurity.
- Explain why you picked that country as one that will have increased food insecurity.
- Explain how the tools were used to gather evidence from your databases and open sources. We are looking at what logic you used to query the AI tools and how that result gave you insight for the next query that could lead to the cause-impact projections. Tell the process that you used to get to your conclusion for why this population will be experiencing food shortages and to what extent you can predict this effect. Hypothesis can be used to predict change in the disruptor and how that affects a region or group.
Your Submission should include:
1) Top submissions will have a rationale for why they think this country will suffer from food shortages.
2) Top submissions will include the logic of the queries and how the results led to a further refined query to gain the insight needed to make these associations. It will also list the GEOINT data they found to create the quantitative data that would drive the predicted impact on the area or group. (e.g. database X shows that when the price of Rice increased over the last 5 years in area A, X number of people were driven below the poverty line{an indication of increased food insecurity})
3) Top submissions will include a detailed analysis of how the disruptor will impact their country and a graph showing what percentage of the population will be affected by each disruptor and the cumulative effect of all of the factor (e.g. a 5% increase in fertilizer cost would reduce production by x% leading to a main staple rising by X% and pushing population or group A into X% of population moving to food insecurity)
4) Top submissions will provide a summary of how they used the AI tool to gain insight into their final graph or chart.
Example of logic flow using AI and data sources to connect the dots to food insecurity: using ChatGPT a single query on fertilizer prices produced this
ChatGPT summary:
Nitrogen: Brazil, India, and Egypt are currently among the countries with the highest nitrogen fertilizer costs.
Conclusion:
India is being impacted by high nitrogen costs which affect rice production.
User Query:
as more and more people are moving to cities in India what is the impact on poverty
ChatGPT summary:
34% of the total population lives in urban areas, with the number projected to increase to 40% by 2030.
Conclusion:
Food supplies affect rural populations more than urban and we have a relationship to projected population in rural areas over time.
Next User Query:
what major foods in india are labor intensive and are mostly grown on small farms
In addition to providing a significant portion of daily calories, rice and wheat are often combined with other foods to form a variety of dishes, such as lentil stews, vegetable curries, and meat dishes. The combination of rice or wheat with other foods provides a balanced diet, allowing for the consumption of necessary nutrients such as protein, vitamins, and minerals.
ChatGPT summary:
with this I learned that Rice and Wheat are widely grown by small farmers who are impacted by rising cost. If too high they will not grow as much or they could lose their farms if not profitable.
Further query on what portion of Rice and Wheat are in the average Indian diet produced:
According to data from the National Sample Survey (NSS), the average per capita consumption of rice in India is around 70-75kg per year, while that of wheat is around 55-60kg per year. These figures can vary across different regions, with rice being more commonly consumed in the southern and eastern regions while wheat is more commonly consumed in northern India.
Further analysis:
Using further queries one could find our %of people that are food insecure in india, who is impacted and where they live. Then you can find information on disposable income in these groups and what an increase may do. No one query will find these answers but a series of inquiries may help to quantify the impacts. What queries you use and how you found the information and the quality of the final displays of what is found is what we are looking for.
Datasets to be used as a starting point for this challenge:
- World Bank and Geospatial Data - GIS Lounge
- Census Mapping Files
- World Bank Water Data
- Socioeconomic Data and Applications Center
- Food Security Datasets
- Food and Agriculture Organization of the United Nations
**NOTE**
The intent of this competition is to advertise how GEOINT can make the world better, enhance their dataset access, and find candidates who have enthusiasm for careers in Geospatial Intelligence. These challenges may be used for the subsequent challenges or for problems for the Hackathon to be held in the in St. Louis, MO on Sept 9-10, 2023 at the T-REX Innovation Center.
This challenge is not restricted to US citizens, but to receive an award for this challenge the winner(s) must be a full time student at a US University.
However, the Hackathon at the T-REX center will be restricted to teams that have at least one “U.S. Person(s)”. To receive an award for the Hackathon on 9-10 Sept 2023, the winner(s) will provide proof of status as “U.S. Persons(s)" as defined by the federal statue.
About T-REX: T-REX is a non-profit innovation and entrepreneur development center dedicated to strengthening the economic vitality of St. Louis through entrepreneurism, innovation activities and workforce development. T-REX's programs, collaborative community, and flexible startup and conference space are key elements in the St. Louis technology innovation ecosystem. T-REX, located in a historic building in downtown St. Louis, is a founder of the Downtown North Urban Insight District. T-REX boasts a one-of-a-kind 16,000 square foot Geospatial Innovation Center, an Extended Reality and Simulation Lab, and is home to the National Geospatial Intelligence Agency’s "Moonshot Labs,” as well as nearly 200 startup and established technology-focused companies and innovation support organizations.
About WBI: Wright Brothers Institute is a cutting-edge innovation and technology commercialization center for the Air Force Research Laboratory, with facilities located just outside of WPAFB in Dayton, OH. We drive fast, agile innovation that enables successful technology development to solve the Air Force’s most complex challenges by leveraging resident experts, unique facilities, disruptive innovation processes, and extensive networks. We leverage subject matter experts and intellectual property from AFRL and SBIR companies to unlock the right problem, connect to new partners and synchronize transition pathways through our commercialization partners.
About Riverside Research: Riverside Research is an independent nonprofit focused on our nation’s security. Our nonprofit structure allows us to design solutions that follow where the science leads, and our collaborative innovation model produces accelerated results. Our independent research and development is in the public interest and for the benefit and furtherance of the U.S. government's mission-related work.
Evaluation Criteria
30% Graph or tables showing impact of food disruptors to increased food insecurity for your country or region of study.
20% number of disruptors you can relate to food security.
40% logic path of how you used AI and public databases to get to your solution.
10% Use of AI to create your final presentation.
Reason for selection of the country or region of interest:
Top solutions have a presentation that will show impact from each disruptor impact on region or populations that you have chosen:
Document on how AI and Databases were used to draw quantitative relationships between disruptors and food insecurity: