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Climate Action- Peace, Justice and Strong Institutions
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- Brief created: 2022
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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
Brief about:
Journal Article (2021)
Written by:
Other researchers:
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.
What it means
This research has yielded a couple of findings:
First, we found that the methodology we used still needed to be developed, especially in terms of the kind of indicators that can be used to draw conclusions. Many indicators can be used to estimate the social, environmental and economic situations of the areas, and it is important to know which to use where (for instance, one can estimate the economic state of an area by looking at the state of roofs on houses). It is important that future research explores in more detail these indicators and finds new ones.
Second, we found that the economic, social and environmental situation has largely worsened. Our indicators showed that the range of household income is lower, and deforestation has strongly increased. What we concluded was that the main driver of these tendencies was the 2017 conflict, which has led to impoverishment, deforestation and an overall worsening of the situation in those regions.
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.What it means
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
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.
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Acknowledgements
Thank you to ASEAN
These insights were made available thanks to the support of ASEAN, who are committed to the dissemination of knowledge for all.
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.
Extra:
This research has yielded a couple of findings:
First, we found that the methodology we used still needed to be developed, especially in terms of the kind of indicators that can be used to draw conclusions. Many indicators can be used to estimate the social, environmental and economic situations of the areas, and it is important to know which to use where (for instance, one can estimate the economic state of an area by looking at the state of roofs on houses). It is important that future research explores in more detail these indicators and finds new ones.
Second, we found that the economic, social and environmental situation has largely worsened. Our indicators showed that the range of household income is lower, and deforestation has strongly increased. What we concluded was that the main driver of these tendencies was the 2017 conflict, which has led to impoverishment, deforestation and an overall worsening of the situation in those regions.