Sarkar Showmitra Kumar, Saroar Md Mustafa, Chakraborty Tanmoy
Department of Urban and Regional Planning, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh.
Disaster Med Public Health Prep. 2022 Jun 27;17:e198. doi: 10.1017/dmp.2022.125.
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.
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.
According to the findings, the forest lost 54.88 km (9.58%) because of the refugee influx during the study. Around 47.26 km (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.
Natural resource conservation for long-term development will benefit from the findings of this study.
本研究的目的是估算孟加拉国乌基亚和特克纳夫县因罗兴亚难民涌入而产生的生态系统服务价值（ESV）成本。
采用人工神经网络（ANN）监督分类技术估算2017年（即罗兴亚难民涌入之前）至2021年期间的土地利用/土地覆盖（LULC）动态变化。利用效益转移法评估2017年至2021年期间的ESV变化。
根据研究结果，在研究期间，由于难民涌入，森林面积减少了54.88平方公里（9.58%）。由于需要在营地为罗兴亚难民提供住所，定居点面积增加了约47.26平方公里（8.25%）。由于罗兴亚难民定居点的增加，ESV总额从2017年的3.1013亿美元增加到2021年的3.3294亿美元。由于森林面积的消失，原材料和生物多样性的ESV分别下降了13.58%和14.57%。
本研究结果将有助于长期发展中的自然资源保护。
