通过遥感和数据驱动的排名算法来调查对气候变化的社会生态脆弱性
Harrison Odion Ikhumhen1, Qinhua Fang2, Shanlong Lu3
1Key Laboratory of Ministry of Education for Coastal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Fujian, 361102, China.
Journal of environmental management
|October 8, 2023
概括
福建省对气候变化的社会生态脆弱性从2000年到2020年大幅增加,特别是在沿海地区. 这项研究开发了一种灵活的,数据驱动的方法来评估和告知弹性沿海系统战略.
科学领域:
- 环境科学 环境科学
- 气候变化研究 气候变化研究
- 社会生态系统分析 社会生态系统分析
背景情况:
- 评估对气候变化的社会生态脆弱性面临着数据和权重的挑战.
- 现有研究需要完善的方法来进行全面的脆弱性评估.
研究的目的:
- 提出一种新的,灵活的,数据驱动的战略方法来研究对气候变化的社会生态脆弱性.
- 利用遥感和IPCC框架,分析2000年至2020年中国福建省的社会生态脆弱性.
主要方法:
- 在地理信息系统 (GIS) 环境中利用遥感和政府间气候变化专门委员会 (IPCC) 框架.
- 采用了全面的指标框架和数据驱动的排名算法来评估脆弱性.
- 进行空间自相关性分析以确定关键影响因素及其空间关系.
主要成果:
- 发现了适度的沿海社会生态脆弱性,具有显著的空间异质性.
- 在过去二十年中,高度脆弱区域的扩张率为6.04%,在福州和宁德大幅增加.
- 确定植被变化,降水,国内生产总值 (GDP) 和土地利用 (LULC) 是脆弱性的主要驱动因素,降水显示出强烈的相关性.
结论:
- 开发的方法提供了一个灵活,自给自足和适应性的社会生态脆弱性评估模型.
- 这些发现为决策者和利益相关者提供了可操作的见解,以制定加强沿海系统弹性战略.
- 强调了降水在加剧研究地区社会生态脆弱性的关键作用.
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