Greenness and Nighttime Light Positively Affect Human Well-being: An empirical machine learning analysis

         
Author Name LI Chao (Kyushu University) / MANAGI Shunsuke (Faculty Fellow, RIETI)
Creation Date/NO. September 2022 22-E-093
Research Project Institutional design for desirable acceptance of AI technology
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Abstract

The positive effects of greenness in living environments on human well-being are known. As a widely used proxy, the nighttime light (NTL) indicates the regional socio-economic status and development level. Higher development levels and economic status are related to more opportunity and higher income, ultimately leading to greater human well-being. However, whether simple increases in greenness and NTL always produce positive results remains inconclusive. Here, we demonstrate the complex relationships between human well-being and greenness and NTL by employing the random forest method. The accuracy of this model is 81.83%, exceeding most previous studies. According to the analysis results, the recommended ranges of greenness and NTL in living environments are 10.91% - 32.99% and 0 – 17.92 nW/cm2・sr, respectively. Moreover, the current average monetary values of greenness and NTL are 3351.96 USD/% and 658.11 USD/(nW/cm2・sr), respectively. The residential areas are far away from the abundant natural resources, which makes the main population desire more greenness in their living environments. Furthermore, high urban development density, represented by NTL, has caused adverse effects on human well-being in metropolitan areas. Therefore, retaining a moderate development intensity is an effective way to achieve a sustainable society and improve human well-being.