孟加拉国罗兴亚难民危机:通过机器学习评估对土地使用模式和土地表面温度的影响
Faishal Ahmed1, Siam Alam2, Ovi Ranjan Saha1
1Department of Water Resources Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
Environmental monitoring and assessment
|May 17, 2024
概括
孟加拉国罗兴亚难民危机导致定居地的土地使用和土地表面温度急剧增加. 预计环境变化将恶化,影响该地区.
科学领域:
- 环境科学 环境科学
- 地理空间分析的研究.
- 气候研究 气候研究
背景情况:
- 孟加拉国因缅甸的罗兴亚难民而面临人道主义危机.
- 在2017-2020年期间,超过一百万难民获得庇护.
- 大量的森林被改造成难民营,造成了环境破坏.
研究的目的:
- 从1997年到2022年,分析罗兴亚难民营地区的土地使用和土地表面温度变化.
- 预测Teknaf和Ukhiya的未来土地使用和温度模式.
- 评估难民安置对环境的影响.
主要方法:
- 在5年间隔 (1997-2022) 分析土地使用和土地表面温度模式.
- 机器学习算法的应用用于未来的预测 (2028年,2034年).
- 对Teknaf和Ukhiya地区的地理空间数据分析.
主要成果:
- 营地地区的定居地使用率从5.28% (1997年) 升至70.09% (2022年).
- 1月份陆地表面平均温度从1997年的18.86°C上升到2022年的25.94°C.
- 未来的预测表明,土地使用和温度上升将继续.
结论:
- 罗兴亚难民的涌入造成了迅速而严重的环境退化.
- 迫切需要可持续的解决方案,以减轻当前和未来的环境影响.
- 该研究强调了人道主义危机与环境变化之间的关键联系.
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