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Watershed Planning within a Quantitative Scenario Analysis Framework
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一个合成的弱势人口数据集,用于微小的地理公平性分析和城市规划
Jérémy Gelb1, Philippe Apparicio2, Hamzeh Alizadeh3
1Autorité Régionale de Transport Métropolitain - équipe Recherche et Valorisation des Données, 1001 Boulevard Robert-Bourassa, Montréal, QC, H3B 4L4, Canada. jgelb@artm.quebec.
Scientific data
|August 31, 2024
概括
本研究引入了一种新方法,通过创建合成人口来评估加拿大的社会和经济脆弱性. 这种方法克服了现有指标的局限性,为环境公平和政策制定提供了一个可扩展的工具.
科学领域:
- 环境健康 环境健康
- 社会经济学研究 社会经济学研究
- 人口学分析 人口学分析
背景情况:
- 评估社会经济脆弱性对于环境公平和政策制定至关重要.
- 现有的指标面临着可比性,标准化和复合限制的挑战.
- 需要改进的方法来准确测量人口的脆弱性.
研究的目的:
- 开发一种用于估计潜在脆弱个体的新方法.
- 为社会经济脆弱性评估创建一个综合人口.
- 为加拿大环境公平研究提供可扩展和强大的数据集.
主要方法:
- 使用开放工具和数据集构建合成人口.
- 估计潜在脆弱个体的数量.
- 将方法应用于整个加拿大环境.
主要成果:
- 这种新的方法为加拿大提供了一个可扩展的解决方案.
- 生成的综合人口数据与传统指标有很强的相关性.
- 克服了现有的复合指标的局限性.
结论:
- 综合人口方法为脆弱性评估提供了一种优越的方法.
- 生成的数据集是研究人员和政策制定者的宝贵资源.
- 该方法支持基于证据的决策,以促进社会和经济的包容性.
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