Hakka traditional villages are an important segment of traditional Chinese villages. Analysis of the process of selection of a Hakka site can deepen our knowledge of Hakka culture. In this study, we selected Hakka traditional villages in Fujian, Guangdong, and Jiangxi provinces as research sites. We extracted basic data for these traditional villages using geographic information system coordinates, identified several potential influencing factors, and analyzed correlations among the factors using the R language. Finally, the degree of influence of each factor on the site selection of Hakka traditional villages in the study area was determined using a geographic probe to confirm the dominant factors. The results showed that Hakka traditional villages in Fujian, Guangdong, and Jiangxi had an overall significant clustered distribution. Distance to water, elevation, and vegetation richness were the dominant factors influencing the location of Hakka villages, while the interaction of multiple factors had a facilitating effect on the location of Hakka village foundations. This study utilized the observed distribution of Hakka villages in different regions and the differences between them resulting from the interaction of influencing factors, combined with data analysis, to provide a theoretical basis for the development and protection of Hakka traditional villages.

The assessment of landscape visual quality (LVQ) holds significant importance in the preservation and advancement of traditional villages. One challenge in measuring human perception lies in establishing a connection between public preferences and landscape characteristics. This study conducted an analysis of social media data from Anyi traditional villages in China to address this issue and identified eight human perceptions: naturalness, ancientness, colorfulness, variety, uniqueness, ingenuity, vividness, and pleasantness. A total of thirty characteristic indicators with potential explanations for LVQ were determined by research group through field investigations. A questionnaire survey was developed to assess human’s preferences using 82 traditional village photos, and scores for the eight perceptions were obtained. The logistic regression was employed to establish distinct perception models, with perceptions serving as the dependent variables and characteristic indicators as the independent variables. Nomograms were subsequently utilized to visualize regression results and display the correlation between these two factors. The findings suggest that nomograms facilitate intuitive determination of the weights assigned to characteristic indicators in perceptual models, as well as their influence on LVQ. This work provides a reference for decision-making related to the adaptive protection and development of traditional villages, thereby helping to enhance the competitiveness of tourist destinations.

Air pollution is a rising environmental concern that has detrimental effects on human health and the environment. Building environment and urban green space features play a crucial role in the dispersion and accumulation of air pollutants. This study examines the impacts of building environment and urban green space on air pollution levels in the highly urbanized city of Hong Kong, focusing on their interaction effects and potential nonlinearity. For the analysis, this paper investigates how building density, building height, building types, urban green space size, and number of urban green space clusters, as well as their interplays, impact PM_2.5 concentrations using high-resolution, satellite-based PM_2.5 grids coupled with spatial analysis techniques. The findings reveal that a unit increase in the size of urban green space and the standard deviation of building height contribute to a 0.0004 and a 0.0154 reduction in PM levels, respectively. In contrast, air pollution levels are found to be positively associated with building density (0.1117), scatteredness of urban green space (0.0003), and share of commercial buildings (1.0158). Moreover, it has been found that building height presents a U-shape relationship with PM_2.5 concentrations. Finally, the negative association between the size of urban green space and air pollution levels tends to be enlarged in districts with more low-rise buildings. This study conveys important building environment and urban green space planning implications.

The composition and configuration of landscapes are critical important to design effective approaches to mitigate urban thermal environment in the urbanization process. In this research, land use maps and land surface temperature (LST) retrieval were derived in Nanchang city of central China based on product datasets and the thermal infrared band of Landsat. The results showed that the thermal environment of Nanchang had become worse over the past two decades, that is, the proportion of area of the extremely low temperature zone (ELTZ) decreased from 4.39 to 0.77% from 2001 to 2020, and that of medium temperature zone (MTZ) reduced by 20%, whereas those of the high temperature zone (HTZ) and the extremely high temperature zone (EHTZ) increased sharply after 2001, and by 2020, the area ratio increased by 11% and 7.16%, respectively. The agricultural land (AL) area decreased from 68.44 to 49.69%, was gradually replaced by construction land (CL). The CL occupied the largest proportion in EHTZ, HTZ and slight high temperature zone (SHTZ); water landscape (WL) and green land (GL) occupied the largest proportion in ELTZ, low temperature zone (LTZ); and AL occupied the largest proportion in SHTZ, MTZ, and slight low temperature zone (SLTZ). Landscape configuration also obviously impacted on LST. The model fitting was well (R = 0.87) between land use area and LST by multiple regression analysis. The significant correlation between LST and six landscape pattern indices of CL (p < 0.01) indicated that the larger percent (PLANT, R = 0.78) and the more concentrate (LPI, R = 0.73) of CL implied the higher LST, while the more fragment (NP, R = − 0.45), dispersed and complex shape (R = − 0.35) were benefit to relieve LST. Contrastively, the larger percent and the more concentrated and complex shape distribution of AL, GL and WL, the lower LST (p < 0.01). In addition, LST had closely correlation with landscape level indices such as aggregation degree (AI, R = 0.44) and diversity (SHDI, R = − 0.60) (p < 0.01).

Traditional villages, rich in historical and cultural value, hold a high level of preservation value. In the process of urbanization, traditional villages face the crisis of decline, making it difficult to perpetuate the carried cultural heritage. The Ganjiang River Basin hosts numerous traditional villages with rich research value, making the study of their preservation and development in this region a significant topic. This paper, from the perspective of landscape ecology, employs geographic detectors to analyze the driving factors behind the emergence of traditional villages in the Ganjiang River Basin, summarizing the spatial distribution characteristics of traditional villages. A classification method based on village landscape features is adopted to categorize traditional villages in the Ganjiang River Basin, providing a reference for planning the preservation and development of traditional villages. The research results show that plain areas are more suitable for the continuation of traditional villages; a single suitable environmental element cannot provide an environment conducive to the development of traditional villages, which is the result of the combined effect of multiple suitable elements; the study has divided traditional village landscapes into nine types, with clear distribution differences among different types of villages; for different regions and types of traditional villages, it is necessary to balance development and protection tendencies and plan differently according to environmental characteristics.

Ancient villages are a unique landscape of cultural heritage with both tangible and intangible culture, which provide rich ecosystem services for human beings. Assessment of society’s perceptions on cultural heritage landscapes can improve the integration of cultural heritage values into decision-making processes that affect landscapes, thereby contributing to maximizing the benefits people receive from cultural ecosystem services. Based on this premise, a new sense-based hierarchical assessment framework for a cultural landscape of ancient villages in China from the perspectives of experts and the public was developed in this study. Field research was conducted by the experts to preliminarily extract the evaluation indicators by identifying and refining the characteristics of the landscape perception units based on the classification of village’s landscape resources. The public indicators as supplements were determined by the semantic and social networks generated with ROSTCM tool post-processing, which followed crawling public comments on the tourism platforms with Python. The findings indicated that visual stimulation (57.36%) is the strongest, while touch perception is the weakest (3.56%). The proportion of hearing, smell, and taste was 21.52%, 12.05%, and 5.53%, respectively. Furthermore, people consider variety, historicity, culture, and localism as the core themes of perception in their landscape experiences. The value and usefulness of the sensory experiences for cultural landscape assessment and for decision-making in the context of cultural ecosystem services are discussed.