应用深度学习来管理沙特阿拉伯沙漠阿巴的城市生态系统:基于遥感的建模用于生态状况评估和决策
Saeed Alqadhi1, Ahmed Ali Bindajam2, Javed Mallick1
1Department of Civil Engineering, College of Engineering, King Khalid University, Abha, Kingdom of Saudi Arabia.
Heliyon
|February 23, 2024
概括
沙特阿拉伯阿巴的城市化呈现出快速扩张,建筑面积增加了四倍以上. 一个新的基于遥感的城市生态状况指数 (RSUSEI) 揭示了生态状况不佳的重要区域,为城市规划提供了信息.
科学领域:
- 环境科学 环境科学
- 城市生态城市生态学
- 遥感 遥感 遥感 遥感
背景情况:
- 城市化对城市生态系统产生重大影响,需要进行定量和定性评估.
- 了解土地使用变化和生态影响对于可持续城市发展至关重要.
研究的目的:
- 量化和定性地评估城市化对阿巴城市生态系统的影响.
- 开发和应用基于遥感的新型城市生态状况指数 (RSUSEI).
主要方法:
- 使用过度调节的人工神经网络 (ANN),土地覆盖面变化率 (LCCR),土地覆盖面指数 (LCI) 和景观扩展指数 (LEI).
- 使用模糊逻辑,原理组件分析 (PCA),分析层次过程 (AHP) 和模糊分析层次过程 (FAHP) 开发了RSUSEI.
- 使用深度神经网络 (DNN) 进行了敏感性和不确定性分析.
主要成果:
- 观测到快速的城市扩张,LCCR显示30年内建筑区增加了四倍以上.
- LCI显示",建筑"面积大幅增加,从3.217%上升到13.982%.
- RSUSEI确定了157250平方公里的极其恶劣的生态状况和91410平方公里的自然区域.
结论:
- 该研究强调了阿巴多层次的城市化模式,具有重大生态后果.
- 该RSUSEI模型有效地评估城市表面生态,并为干旱地区的城市管理提供信息.
- 研究结果支持改善干旱地区的城市规划,平衡发展与生态保护和生活质量.
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