Critical factors influencing visitor emotions: analysis of “restorativeness” in urban park visits in Fuzhou, China

ObjectiveTo date, a comprehensive analysis of urban green space (UGS) visitors’ emotional remains largely unexplored. In this study, we focus on how UGS environmental preferences, restorativeness, other physical factors (sound, air, and thermal environments), and individual characteristics affecting visitor emotions. Such a comprehensive analysis would allow relevant practitioners to check the environmental quality of UGSs and improve certain conditions to promote visitor emotions.MethodsA total of 904 questionnaire responses with concurrently monitored physical factors were analyzed by independent sample t-tests, one-way ANOVA and path analysis.ResultsThe thermal evaluation had the largest impact on positive emotions (β = 0.474), followed by perceived restorativeness (β = 0.297), which had β values of −0.120 and −0.158, respectively, on negative emotions. Air evaluation was more effective for increasing positive emotions (β = 0.293) than reducing negative emotions (β = −0.115). Sound evaluation also had similar results (β = 0.330 vs. β = −0.080). Environmental preference significantly influenced only positive emotions (β = 0.181) but could still indirectly impact negative emotions. Moreover, objective physical factors can indirectly affect visitors’ emotions by enhancing their evaluations..ConclusionThe influence of different UGS environmental factors on visitors’ emotions vary, as does their impacts on positive versus negative emotions. Positive emotions were generally more affected than negative emotions by UGS. Visitor emotions were mainly influenced by physical and psychological factors. Corresponding suggestions are proposed for UGS design and management in this study

Construction of Water Corridors for Mitigation of Urban Heat Island Effect

The urban heat island (UHI) effect is becoming increasingly prominent owing to accelerated urbanization in Fuzhou, affecting the lives of people. Water is an important landscape element that can effectively improve the urban thermal environment. The construction of water corridors has been proven to mitigate the intensity of the UHI effect in Fuzhou. Therefore, we obtained the distribution of a water system in Fuzhou from image data and analyzed temperature watersheds using the inversion of surface temperature to investigate the inner mechanism of the water system influencing the UHI effect. The water system was superimposed with hot spots to obtain cooling ecological nodes and construct water corridors to mitigate the UHI effect. The temperature watershed areas in Fuzhou are: Minhou County (353.77 km2), Changle (233.06 km2), Mawei (137.82 km2), Cangshan (71.25 km2), Jin’an (55.99 km2), Gulou (16.93 km2), and Taijiang (15.51 km2) Districts. Hot spots were primarily located in Changle, Cangshan, Jin’an, Gulou, and Taijiang Districts. The superposition of the water system and temperature watershed yielded 152 cooling ecological nodes, which were concentrated in the Minjiang and Wulong River watershed, with no cooling ecological nodes distributed within the central city. Twenty-five cooling ecological nodes were selected in the hot spot areas, which were primarily distributed in reservoirs, inland rivers, and park water systems. We constructed 12 water corridors, including four, three, two, one, one, and one in the Minhou County, Changle, Mawei, Jin’an, Cangshan, and the Gulou and Taijiang Districts

The Relationships between Perceived Design Intensity, Preference, Restorativeness and Eye Movements in Designed Urban Green Space

Recent research has demonstrated that landscape design intensity impacts individuals’ landscape preferences, which may influence their eye movement. Due to the close relationship between restorativeness and landscape preference, we further explore the relationships between design intensity, preference, restorativeness and eye movements. Specifically, using manipulated images as stimuli for 200 students as participants, the effect of urban green space (UGS) design intensity on landscapes’ preference, restorativeness, and eye movement was examined. The results demonstrate that landscape design intensity could contribute to preference and restorativeness and that there is a significant positive relationship between design intensity and eye-tracking metrics, including dwell time percent, fixation percent, fixation count, and visited ranking. Additionally, preference was positively related to restorativeness, dwell time percent, fixation percent, and fixation count, and there is a significant positive relationship between restorativeness and fixation percent. We obtained the most feasible regression equations between design intensity and preference, restorativeness, and eye movement. These results provide a set of guidelines for improving UGS design to achieve its greatest restorative potential and shed new light on the use of eye-tracking technology in landscape perception studies

Dynamic Landscape Fragmentation and the Driving Forces on Haitan Island, China

Island ecosystems have distinct and unique vulnerabilities that place them at risk from threats to their ecology and socioeconomics. Spatially exhibiting the fragmentation process of island landscapes and identifying their driving factors are the fundamental prerequisites for the maintenance of island ecosystems and the rational utilization of islands. Haitan Island was chosen as a case study for understanding landscape fragmentation on urbanizing Islands. Based on remote sensing technology, three Landsat images from 2000 to 2020, landscape pattern index, transect gradient analysis, and moving window method were used in this study. The results showed that from 2000 to 2020, impervious land increased by 462.57%. In 2000, the predominant landscape was cropland (46.34%), which shifted to impervious land (35.20%) and forest (32.90%) in 2020. Combining the moving window method and Semivariogram, 1050 m was considered to be the best scale to reflect the landscape fragmentation of Haitan Island. Under this scale, it was found that the landscape fragmentation of Haitan Island generally increased with time and had obvious spatial heterogeneity. We set up sampling bands along the coastline and found that the degree of landscape fragmentation, advancing from the coast inland, was decreasing. Transects analysis showed the fragmentation intensity of the coastal zone: the north-western and southern wooded zones decreased, while the concentration of urban farmland in the north-central and southern areas increased. The implementation of a comprehensive experimental area plan on Haitan Island has disturbed the landscape considerably. In 2000, landscape fragmentation was mainly influenced by topography and agricultural production. The critical infrastructure construction, reclamation and development of landscape resources have greatly contributed to the urbanisation and tourism of Haitan Island, and landscape fragmentation in 2013 was at its highest. Due to China’s “Grain for Green Project” and the Comprehensive Territorial Spatial Planning policy (especially the protection of ecological control lines), the fragmentation of Haitan Island was slowing. This study investigated the optimal spatial scale for analyzing spatiotemporal changes in landscape fragmentation on Haitan Island from 2000 to 2020, and the essential influencing factors in urban islands from the perspective of natural environment and social development, which could provide a basis for land use management and ecological planning on the island

Identification and Construction of Ecological Nodes in the Fuzhou Ecological Corridors

Ecological corridor construction is an important support of the current pursuit of high-quality urbanization. Fuzhou is a mountain–water city characterized by a unique spatial structure. However, rapid urbanization has exacerbated the rate of ecosystem fragmentation, negatively impacting the livable living environment. The construction of ecological corridors is of great significance for efforts to restore the broken landscape and form the urban ecosystem as an organic whole in Fuzhou. In the present study, Fuzhou was considered as the study area, and the water, green, and ventilation corridors, as well as surface temperature data, were analyzed using the kernel density analysis method to generate surface-temperature-based ecological nodes. The impacts of various corridors and surface temperatures on the construction of the Fuzhou ecological corridors were assessed using ecological theory, and the ecological resistance surfaces of the influencing factors were obtained. We constructed ecological corridors for the mitigation of the urban heat island in Fuzhou using the MCR model with four levels and then evaluated the network connectivity of the corridors. The results revealed the following findings: (1) The study area comprises 32 ecological nodes, including nine in Minhou County and Changle District, four in Mawei and Cangshan Districts, and two in Gulou, Taijiang, and Jin’an Districts. (2) Fuzhou contains 63 ecological corridors with a total length of approximately 494.65 km. These include 31 first-level (201.16 km), 11 second-level (98.56 km), 14 third-level (129.12 km), and 7 fourth-level (65.81 km) corridors. (3) The degree of closure (α), the point rate of lines (β), the degree of connectivity (γ), and the degree of connectivity (Cr) indexes of the network structure for the ecological corridors were 0.27, 2.03, 0.72, and 0.87, respectively. They indicate that the overall ecological effectiveness of the network is high and can provide a theoretical basis for the construction of ecological corridors in the future

Research on the Estimation of Chinese Fir Stand Volume Based on UAV-LiDAR Technology

Chinese fir (Cunninghamia lanceolata) is the main fast-growing timber species in China, and studies of its stand volume are important for evaluating the effectiveness of forest management. However, it is difficult to accurately estimate stand volume from the perspective of a single tree due to the mutual concealment among Chinese fir trees. Therefore, in this study, we propose a method for identifying different forms of Chinese fir. The specific idea is to realize the accurate identification of a single Chinese fir tree, two Chinese fir trees, and three Chinese fir trees, and construct their respective stand volume estimation models to obtain an estimate of the forest stand volume. The key results are as follows: (1) the overall accuracy of recognition of different forms of Chinese fir is 79%, and the construction of different forms of Chinese fir units is beneficial for identifying forest trees; (2) a multiunit volume equation for different forms of Chinese fir is constructed; (3) based on predictions obtained with the constructed stand volume model, the difference between the estimated stand volume and the measured stand volume is small, and the average accuracy reaches 89.19%; and (4) compared to traditional volume estimation methods based on individual tree scale, the research method in this study shows a significant improvement (about 9.96%) in overall accuracy. In summary, this method can weaken the influence of erroneous individual tree segmentation on the accuracy of stand volume estimation, and can greatly reduce the working time of single tree segmentation to achieve the fast and accurate estimation of fir plantation stand volume

Dynamic Landscape Fragmentation and the Driving Forces on Haitan Island, China

Island ecosystems have distinct and unique vulnerabilities that place them at risk from threats to their ecology and socioeconomics. Spatially exhibiting the fragmentation process of island landscapes and identifying their driving factors are the fundamental prerequisites for the maintenance of island ecosystems and the rational utilization of islands. Haitan Island was chosen as a case study for understanding landscape fragmentation on urbanizing Islands. Based on remote sensing technology, three Landsat images from 2000 to 2020, landscape pattern index, transect gradient analysis, and moving window method were used in this study. The results showed that from 2000 to 2020, impervious land increased by 462.57%. In 2000, the predominant landscape was cropland (46.34%), which shifted to impervious land (35.20%) and forest (32.90%) in 2020. Combining the moving window method and Semivariogram, 1050 m was considered to be the best scale to reflect the landscape fragmentation of Haitan Island. Under this scale, it was found that the landscape fragmentation of Haitan Island generally increased with time and had obvious spatial heterogeneity. We set up sampling bands along the coastline and found that the degree of landscape fragmentation, advancing from the coast inland, was decreasing. Transects analysis showed the fragmentation intensity of the coastal zone: the north-western and southern wooded zones decreased, while the concentration of urban farmland in the north-central and southern areas increased. The implementation of a comprehensive experimental area plan on Haitan Island has disturbed the landscape considerably. In 2000, landscape fragmentation was mainly influenced by topography and agricultural production. The critical infrastructure construction, reclamation and development of landscape resources have greatly contributed to the urbanisation and tourism of Haitan Island, and landscape fragmentation in 2013 was at its highest. Due to China’s “Grain for Green Project” and the Comprehensive Territorial Spatial Planning policy (especially the protection of ecological control lines), the fragmentation of Haitan Island was slowing. This study investigated the optimal spatial scale for analyzing spatiotemporal changes in landscape fragmentation on Haitan Island from 2000 to 2020, and the essential influencing factors in urban islands from the perspective of natural environment and social development, which could provide a basis for land use management and ecological planning on the island

Estimation of Pinus massoniana Leaf Area Using Terrestrial Laser Scanning

The accurate estimation of leaf area is of great importance for the acquisition of information on the forest canopy structure. Currently, direct harvesting is used to obtain leaf area; however, it is difficult to quickly and effectively extract the leaf area of a forest. Although remote sensing technology can obtain leaf area by using a wide range of leaf area estimates, such technology cannot accurately estimate leaf area at small spatial scales. The purpose of this study is to examine the use of terrestrial laser scanning data to achieve a fast, accurate, and non-destructive estimation of individual tree leaf area. We use terrestrial laser scanning data to obtain 3D point cloud data for individual tree canopies of Pinus massoniana. Using voxel conversion, we develop a model for the number of voxels and canopy leaf area and then apply it to the 3D data. The results show significant positive correlations between reference leaf area and mass (R2 = 0.8603; p < 0.01). Our findings demonstrate that using terrestrial laser point cloud data with a layer thickness of 0.1 m and voxel size of 0.05 m can effectively improve leaf area estimations. We verify the suitability of the voxel-based method for estimating the leaf area of P. massoniana and confirmed the effectiveness of this non-destructive method

Dominant Factors and Spatial Heterogeneity of Land Surface Temperatures in Urban Areas: A Case Study in Fuzhou, China

The urban heat island (UHI) phenomenon caused by rapid urbanization has become an important global ecological and environmental problem that cannot be ignored. In this study, the UHI effect was quantified using Landsat 8 image inversion land surface temperatures (LSTs). With the spatial scale of street units in Fuzhou City, China, using ordinary least squares (OLS) regression, geographically weighted regression (GWR) models, and multi-scale geographically weighted regression (MGWR), we explored the spatial heterogeneities of the influencing factors and LST. The results indicated that, compared with traditional OLS models, GWR improved the model fit by considering spatial heterogeneity, whereas MGWR outperformed OLS and GWR in terms of goodness of fit by considering the effects of different bandwidths on LST. Building density (BD), normalized difference impervious surface index (NDISI), and the sky view factor (SVF) were important influences on elevated LST, while building height (BH), forest land percentage (Forest_per), and waterbody percentage (Water_per) were negatively correlated with LST. In addition, built-up percentage (Built_per) and population density (Pop_Den) showed significant spatial non-stationary characteristics. These findings suggest the need to consider spatial heterogeneity in analyses of impact factors. This study can be used to provide guidance on mitigation strategies for UHIs in different regions

Study on Single-Tree Segmentation of Chinese Fir Plantations Using Coupled Local Maximum and Height-Weighted Improved K-Means Algorithm

Chinese fir (Cunninghamia lanceolata) is a major timber species in China, and obtaining and monitoring the parameters of Chinese fir plantations is of great practical significance. With the help of the K-means algorithm and UAV-LiDAR data, the efficiency of forestry surveys can be greatly improved. Considering that the traditional K-means algorithm is susceptible to the influence of initial cluster centers and outliers during the process of individual tree segmentation, it may result in incorrect segmentation. Therefore, this study proposes an improved K-means algorithm that uses the methods of local maxima and height weighting to optimize and improve the algorithm. The research results are as follows: (1) Compared to the traditional K-means algorithm, the producer accuracy and user accuracy of this research algorithm have imsproved by 10.72% and 11.46%, respectively, with significant differences (p < 0.05). (2) The research algorithm proposed in this study can adapt to Chinese fir plantations of different age groups, with average producer accuracy and user accuracy reaching 78.48% and 83.72%, respectively. In summary, this algorithm can be effectively applied to the forest parameter estimation of Chinese fir plantations and is of great significance for sustainable forest management