Urban forests are more about people than trees. The positivist approach faces many obstacles in analyzing current urban forest-related issues; thus, this study adopted semantic differences and cognitive map approaches to evaluate the subjective preferences of citizens based on their spatial behavior. From December 2015 to November 2017, a three-year continuous public questionnaire was administered to a total of 450 citizens. Typical forest parks, suburban parks, and urban parks in Beijing were selected as research sites, and were analyzed respectively. This study comprehensively evaluated the perception characteristics and differences in the spatial images of urban forests by citizens in relation to different location conditions. Because these characteristics varied across individuals, the spatial cognition and familiarity of citizens with different types of urban forests were analyzed and compared. The perception of spatial images by citizens of different types of urban forests noticeably varied with respect to color and psychology. The perception of spatial images significantly varied with respect to gender, educational background, and income level, with individual characteristics being most closely related to the perception elements of urban forests in terms of space, color, style, and environment. Comparison of cognitive maps demonstrated clear differences in how citizens selected different types of urban forests. These differences were reflected in six types of cognitive maps and six familiar elements in the cognitive maps drawn by citizens.

With the transformation of the rural economy and the increasing national emphasis on forest resources, forestry management plays an increasingly important role in promoting household income growth and sustainable rural development. This study, based on a field survey of 1043 micro-level household data collected in Guizhou Province, China, empirically analyzes the impact of participation in forestry management on household income, income structure, and income inequality, as well as its underlying mechanisms. Using endogenous switching models, quantile regression models, and mediation effect models, the study reveals the following findings: First, participation in forestry management significantly enhances household income. Second, the impact of participation in forestry management on income structure varies, significantly increasing both forestry and non-forestry income, with the effect on forestry income being particularly pronounced. Third, participation in forestry management significantly alleviates income inequality, especially for low-income households. Fourth, forestry management indirectly increases household income and non-forestry income by promoting forest-based employment. Forest-based employment acts as a partial mediator in the effect of forestry management on household income and a full mediator in the increase in non-forestry income. The contribution of this study lies in its multidimensional approach to revealing the comprehensive impact of participation in forestry management on rural household income, providing important policy insights for increasing household income and achieving sustainable rural development.