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OBJECTIVE: The objective of the research is to estimate the cost of ecosystem service value (ESV) due to the Rohingya refugee influx in Ukhiya and Teknaf upazilas of Bangladesh. METHODS: Artificial neural network (ANN) supervised classification technique was used to estimate land use/land cover (LULC) dynamics between 2017 (ie, before the Rohingya refugee influx) and 2021. The ESV changes between 2017 and 2021 were assessed using the benefit transfer approach. RESULTS: (8.25%) of settlement was increased due to the need to provide shelter for Rohingya refugees in camp areas. Due to the increase in Rohingya refugee settlements, the total ESV increased from US $310.13 million in 2017 to US $332.94 million in 2021. Because of the disappearance of forest areas, the ESV for raw materials and biodiversity fell by 13.58% and 14.57%, respectively. CONCLUSION: Natural resource conservation for long-term development will benefit from the findings of this study.
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Sarkar et al. (2022) studied this question.
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