Using Satellite Data and Machine Learning to Study Conflict-Induced Environmental and Socioeconomic Destruction in Data-Poor Conflict Areas: The Case of the Rakhine Conflict
Based on:
Journal Article (2021)
The idea behind this article was to apply new, digital technologies in order to study some of the least accessible places in the world, namely neighbouring regions of Bangladesh and Myanmar. We studied changes over time in environmental, social and economic domains, and explored the causes of these changes (2012-2019).
Brief by:

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The purpose of this research was to find new ways to do research in areas that are difficult to reach, and therefore research with traditional methods such as interviews, survey, field work.
In our case, we looked at regions where the Rakhine people are located. The Rakhine people are an ethnic group with whom the central government in Myanmar has had a series of conflicts and tensions, and what little we knew based on some individual accounts of people who had been there and some limited journalistic accounts. This was not enough to make reliable conclusions about what has been happening in the area, and we wanted to explore the change over time in environmental, social and economic domains.
Key findings
While there are many indicators used to estimate the social, environmental and economic situations of areas, we need new indicators to analyse satellite imagery.
The 2017 conflict has led to impoverishment, deforestation and an overall worsening of the situation in those regions.
Our indicators showed that the range of household income is lower, and deforestation has strongly increased.
From 2012 to 2019, the size of forests in the bordering regions on the side of Myanmar and Bangladesh decreased by 20% and 13% respectively.
Proposed action
The international aid community that works on Myanmar can use the evidence we've found in negotiations, in designing development aid projects, in gaining a better understanding of the situation on the ground
Our study encourages researchers to expand their methodological tools and to try to do research with a larger variety of methods, with more innovative tools, in order to gain a more nuanced understanding of complex situations
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Acknowledgements
Special thanks to Antoine Germain for preparation assistance
We would like to extend a special thank you to Antoine Germain, for their invaluable contribution in assisting the preparation of this research summary.
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Using Satellite Data and Machine Learning to Study Conflict-Induced Environmental and Socioeconomic Destruction in Data-Poor Conflict Areas: The Case of the Rakhine Conflict
Cite this brief: Vakulchuk, Roman. 'Using Satellite Data and Machine Learning to Study Conflict-Induced Environmental and Socioeconomic Destruction in Data-Poor Conflict Areas: The Case of the Rakhine Conflict'. Acume. https://www.acume.org/r/using-satellite-data-and-machine-learning-to-study-conflict-induced-environmental-and-socioeconomic-destruction-in-data-poor-conflict-areas-the-case-of-the-rakhine-conflict/
Brief created by: Dr Roman Vakulchuk | Year brief made: 2022
Original research:
- T. S. A., Vakulchuk, R., & et al., ‘Using Satellite Data and Machine Learning to Study Conflict-Induced Environmental and Socioeconomic Destruction in Data-Poor Conflict Areas: The Case of the Rakhine Conflict’ 3 (pp. 1–18) https://iopscience.iop.org/article/10.1088/2515-7620/abedd9. – https://iopscience.iop.org/article/10.1088/2515-7620/abedd9
Research brief:
The idea behind this article was to apply new, digital technologies in order to study some of the least accessible places in the world, namely neighbouring regions of Bangladesh and Myanmar. We studied changes over time in environmental, social and economic domains, and explored the causes of these changes (2012-2019).
The purpose of this research was to find new ways to do research in areas that are difficult to reach, and therefore research with traditional methods such as interviews, survey, field work.
In our case, we looked at regions where the Rakhine people are located. The Rakhine people are an ethnic group with whom the central government in Myanmar has had a series of conflicts and tensions, and what little we knew based on some individual accounts of people who had been there and some limited journalistic accounts. This was not enough to make reliable conclusions about what has been happening in the area, and we wanted to explore the change over time in environmental, social and economic domains.
Findings:
While there are many indicators used to estimate the social, environmental and economic situations of areas, we need new indicators to analyse satellite imagery.
The 2017 conflict has led to impoverishment, deforestation and an overall worsening of the situation in those regions.
Our indicators showed that the range of household income is lower, and deforestation has strongly increased.
From 2012 to 2019, the size of forests in the bordering regions on the side of Myanmar and Bangladesh decreased by 20% and 13% respectively.
Advice:
The international aid community that works on Myanmar can use the evidence we’ve found in negotiations, in designing development aid projects, in gaining a better understanding of the situation on the ground
Our study encourages researchers to expand their methodological tools and to try to do research with a larger variety of methods, with more innovative tools, in order to gain a more nuanced understanding of complex situations
- Researchers can sometimes tend to do research the way they’ve been taught, but academic research would benefit from more risks being taken and more innovative techniques being used.






