The post-occupancy evaluation process is pivotal for assessing the performance of indoor and outdoor living environments after occupation. This evaluation involves a multifaceted analysis, encompassing energy efficiency, indoor environmental quality, outdoor spaces, and occupant satisfaction. Despite the inherent advantages and potential applicability of post-occupancy evaluation in residential buildings, the lack of uniformity in research methodologies, data collection techniques, investigative approaches, and result interpretation has impeded cross-comparisons and method replication. In a concerted effort to enhance the understanding of prevailing post-occupancy evaluation methodologies, this study undertook a comprehensive systematic literature review of post-occupancy evaluation practices within the residential domain from 2000 to 2023. The results unequivocally underscored the pervasive lack of consistency in methodological applications, tool deployment, and data reporting across diverse post-occupancy evaluation investigations. The objectives of this review aimed to examine the existing post-occupancy evaluation (POE) methods, assess occupant-centric thermal comfort, evaluate the impact of POE feedback on building design, and develop recommendations for architects, engineers, facility managers, and policymakers on leveraging POE feedback to enhance thermal comfort and energy efficiency in buildings. This study offers critical insights into advocating for a more standardized and cohesive post-occupancy evaluation approach. The findings of this review can direct the establishment of a coherent and consistently implemented post-occupancy evaluation framework within the realm of residential architecture.

One method of understanding landscape pattern changes is through an understanding of land use/land cover (LULC) changes, which are closely related to landscape pattern changes. Previous studies have monitored LULC changes across North Korea but did not consider landscape changes at a local scale. Using multiple LULC products to construct sample points, the LULC was classified using a random-forest algorithm and Landsat satellite dataset. The overall accuracy of the classification was 97.66 ± 1.36%, and the Kappa coefficient was 0.95 ± 0.03. Based on the classification results, landscape indices were used to quantify and monitor landscape pattern changes. The results showed that, from 2000 to 2020, there was an increasing trend in built-up and forest areas in Pyongyang, while cropland showed a decreasing trend, and landscape fragmentation increased. However, urban expansion was not the main factor affecting fragmentation. The main factors were forest recovery and cropland reduction, leading to an increase in landscape fragmentation in Pyongyang.

Various physical and environmental factors affect the recreational experience in national forest parks. Understanding visitors’ preferences regarding these factors is significant for promoting the physical and mental health and well-being of urban residents. This study aims to quantify residents’ usage patterns and safety perceptions of national forest parks. It focuses particularly on Santai Mountain National Forest Park in Jiangsu, China, and conducted a semi-structured questionnaire survey with 688 participants. The statistical software IBM SPSS Statistics 24 was used for data analysis. A descriptive quantitative analysis was conducted on the respondents’ demographic information. Descriptive statistics, chi-square tests, and an ordinal logistic regression model were employed to analyze the survey data. The survey results show that most visitors go to the forest park only once or twice a year, usually on weekends, holidays, and during leisure time rather than on workdays. Because the national forest park is located in the suburbs, the journey is long, and most visitors choose to drive there. Additionally, the majority of visitors go to the forest park with family and friends. Because the park is well managed and has complete safety facilities, most visitors feel safe in the national forest park.

Recently, many Chinese cities have initiated improvement projects aimed at enhancing living conditions in older residential neighborhoods. Urban improvement should be closely linked to the needs of occupants to determine “what to improve”. Governmental initiatives and the various stakeholders involved in the project influence the impact of improvement efforts. The objectives of the study are essential to identify the factors influencing occupants’ satisfaction and to evaluate whether the occupants are satisfied with the improved old residential neighborhoods. This study conducts a post-occupancy evaluation (POE) of improved outdoor spaces in old residential neighborhoods, focusing on neighborhoods in Wuxi, China. A principal component analysis (PCA) was used to evaluate residents’ efficacy and satisfaction with the enhancements implemented in outdoor spaces. The methodology involved collecting data through surveys and on-site observations, which were then analyzed to identify the pivotal factors impacting the effectiveness of these improvements. The results indicated that enhancing outdoor spaces had a substantial positive impact on residents’ quality of life, social interactions, and physical activity levels. Additionally, the PCA identified accessibility, safety, and aesthetic quality as the main factors contributing to resident satisfaction. This study offers valuable insights for urban planners and policymakers aiming to rejuvenate aging residential districts, emphasizing the importance of data-driven approaches to improve the design and functionality of outdoor spaces.

China is the world’s largest pear producer, yet its production remains constrained by structural inefficiencies and regional disparities. Clarifying the spatiotemporal evolution of pear production land and its driving mechanisms is essential for improving efficiency and supporting sustainable agricultural development. Using provincial panel data from 29 Chinese regions during 2001–2020, this study analyzes changes in pear yield, planting area, and yield per unit area by integrating the Production Concentration Index, Exploratory Spatial Data Analysis, and Comparative Advantage Analysis. A Spatial Durbin Model is applied to quantify both direct and spatial spillover effects of natural conditions, opportunity costs, infrastructure, technology, market demand, and policy. The results indicate a shift in pear production from area-driven expansion to efficiency-oriented growth, alongside a gradual westward relocation and declining spatial dependence. While core producing regions remain dominant, several western regions have enhanced their comparative advantages. Labor-related factors are crucial: expanding non-agricultural employment opportunities constrain pear production (−0.482), but agricultural mechanization indirectly increases rural labor hiring costs (0.089), whereas agricultural mechanization (0.144) and moderate increases in labor costs (0.126) contribute positively to regional production efficiency. Improved transportation infrastructure, irrigation, fertilizer input, market demand, and policy further promote pear production, with evident spatial spillover effects. These research findings provide empirical support for optimizing regional pear production layouts and formulating applicable policies.