Dong Wei’s research while affiliated with Sun Yat-sen University and other places

The impact of settlements isolation and land-use changes on poverty is often overlooked. This study explored the spatial pattern and impact of settlements isolation and land use changes on poverty in Guizhou, a mountainous province of China, based on a Pearson correlation analysis and geographically weighted regression (GWR). The results showed that the incidence of high poverty levels in the counties of Guizhou tended to move from the southwest to the southeast over the period of 2005–2015. Both settlements isolation and land use changes had an impact on poverty, and this effect displayed spatial heterogeneity. With other factors unchanged, a 1 m increase in settlements isolation was associated with a statistically significant 0.58% increase in poverty incidence. Changes in the area of crop land, water, and forest land had a significant impact on poverty. The authors suggest that in the process of resettlement, the distance between settlements should be kept less than 5000 m if possible. The government needs to further improve and implement preferential land use policies, with appropriate increases in the area of built-up land.

The commute well-being (CWB) has been associated with the mental health and depends on the positive or negative emotions that occur during the daily commute. This paper analyzes the influencing factors and discusses the structural relationship between CWB and influencing factors, based on our evaluation of the results for daily CWB between different travel modes. We based our analyses on a CWB survey conducted in the central city proper of Xi’an. In contrast to previous studies, this paper investigates two commuting phases, in the morning and evening, to better analyze daily CWB. To conduct a more comprehensive analysis, in addition to considering multi-stage combined travel, the subjective and objective aspects of factors influencing CWB were deepened and expanded. The measurement was based on the Satisfaction with Travel Scale, which was developed based on a method for measuring subjective well-being. The average CWB level of each model was compared by analyzing the variances. The influencing factors were determined by stepwise regression, and the influence mechanism was analyzed using a structural equation model (SEM). The results indicate that CWB in Xi’an was highest for walking, which was followed, in order, by motorcycle, electric bicycle, staff shuttle bus, bicycle, metro, car, taxi, and bus. The result reflects that commuting by bus is associated with more negative emotions in Xi’an. The results of SEM indicate that the built environment does not directly affect CWB, but it will act on CWB by affecting other factors. The travel attitude, commute mode choice, and other travel characteristics affect each other and affect CWB directly and indirectly. Other travel characteristics has the largest total effect on CWB, and the travel attitudes have the largest direct effect. Without considering the travel attitude, reducing traffic congestion, commuting time, and transfer times can significantly improve CWB and reduce negative emotions in the future in Xi’an.