Mapping and Analyzing the Park Cooling Effect on Urban Heat Island in an Expanding City: A Case Study in Zhengzhou City, China

Using buffer analysis to determine urban park cooling intensity: Five estimation methods for Nanjing, China

Urban parks are part of the blue-green infrastructure of urban ecosystems. Although the cooling effect of urban parks has been widely recognized, the understanding of park cooling intensity (PCI) and its mechanisms remains incomplete. Applicable and accurate quantification could facilitate better design and management of urban parks. We used five methods (equal area method [EAM], equal radius method [ERM], fixed radius method [FRM], turning point method-maximum perspective [TPM-M], and turning point method-accumulation perspective [TPM-A]) to estimate PCI, and established the method selection mechanism, which we evaluated in terms of PCI amplitudes, spatial heterogeneity, and interactions with park landscape features. Using Nanjing as a case study, we employed spatial and statistical analyses to further assess the autocorrelation of PCI and its relationship with park landscape features. The results indicate the following: (1) 62.38 % of Nanjing's urban parks are located above the 90 % confidence level in cold spot areas. (2) Different methods had significant effects on the estimated PCI, were positively correlated, and had similar spatial heterogeneity. (3) All methods revealed that park area (PA), water area proportion (WAP), and the normalized difference vegetation index (NDVI) of the vegetated area (NDVI_veg) were the three dominant factors that influenced PCI; WAP and NDVI_veg that achieved more effective cooling. (4) The quantification of PCI using the ERM and TPM is recommended over other methods. These findings are essential for landscape planners to understand the formation of PCI and design cooler parks to mitigate the urban heat island (UHI) effect more systematically.

Cooling effect of the pocket park in the built-up block of a city: a case study in Xi'an, China

Pocket parks, the green infrastructures with small sizes and flexible layouts, are suitable for thermal environment improvement in the urban built-up block with limited green space. To quantify the relationship between pocket parks and the thermal environment in western China, two parks in the built-up block of Xi'an were selected. By field measurement, the cooling effect could be extended 100 m from the park boundary, connecting two parks. Furthermore, the road and greening within the block demonstrate significant influence on the cooling diffusion by regression analysis. Based on ENVI-met simulation, the ratio of the tree and the grass, the layout of the tree and the grass, and the layout of the paving were analyzed at different proportions of greening and paving of the park. Finally, a combination of the daytime physiological equivalent temperature (PET) and nighttime air temperature (AT) was proposed to choose the optimum layouts: the trees concentrated in the center and the pavement with more roads. Results can provide insights for designing pocket parks based on the thermal environment improvement.

Thermal comfort differences between urban villages and formal settlements in Chinese developing cities: A case study in Shenzhen

Rapid urbanization has changed the urban spatial form, which directly leads to the emergence of urban informal settlements, and the impact on ecological environment is manifested as the obvious deterioration of urban thermal environment. The thermal environment of informal settlements, which are called urban villages in China, is seriously deteriorated. In the process of urban renewal, we should pay attention to the thermal environment effect of urban villages and promote the sustainable development of cities. However, at present there are few studies on the differences of thermal comfort among urban settlements. Taking Shenzhen as an example city, this paper distinguished several scopes such as urban villages, formal settlements and non-urban areas, then analyzed the pattern characteristics of urban thermal comfort by using the Modified Temperature and Humidity Index (MTHI), and finally explored the spatial relationship between thermal comfort and various environmental factors through spatial regression models. The results show that (1) thermal comfort has significant spatial autocorrelation and the thermal environment centers are clustered in built-up areas of Shenzhen city. The overall MTHI of urban villages is relatively the highest, and the dominant thermal comfort level in summer is sultry and hot. (2) According to the Spatial Error Model, the green space coverage represented by NDVI has the strongest mitigation effect on urban thermal comfort, and the building density has an obvious aggravating effect on the muggy environment. Both of them have more obvious effects on the thermal comfort of informal settlements. (3) The current thermal environment of urban settlements cannot be ignored, especially in urban villages. In the process of urban renewal, heat dissipation should be considered emphatically. Increasing urban green area and decreasing building density will help to improve urban thermal environment. The study can provide suggestions for urban renewal from the perspective of improving thermal environment.

Influencing Factors and Risk Assessment of Precipitation-Induced Flooding in Zhengzhou, China, Based on Random Forest and XGBoost Algorithms

Due to extreme weather phenomena, precipitation-induced flooding has become a frequent, widespread, and destructive natural disaster. Risk assessments of flooding have thus become a popular area of research. In this study, we studied the severe precipitation-induced flooding that occurred in Zhengzhou, Henan Province, China, in July 2021. We identified 16 basic indicators, and the random forest algorithm was used to determine the contribution of each indicator to the Zhengzhou flood. We then optimised the selected indicators and introduced the XGBoost algorithm to construct a risk index assessment model of precipitation-induced flooding. Our results identified four primary indicators for precipitation-induced flooding in the study area: total rainfall for three consecutive days, extreme daily rainfall, vegetation cover, and the river system. The Zhengzhou storm and flood risk evaluation model was constructed from 12 indicators: elevation, slope, water system index, extreme daily rainfall, total rainfall for three consecutive days, night-time light brightness, land-use type, proportion of arable land area, gross regional product, proportion of elderly population, vegetation cover, and medical rescue capacity. After streamlining the bottom four indicators in terms of contribution rate, it had the best performance, with an accuracy rate reaching 91.3%. Very high-risk and high-risk areas accounted for 11.46% and 27.50% of the total area of Zhengzhou, respectively, and their distribution was more significantly influenced by the extent of heavy rainfall, direction of river systems, and land types; the medium-risk area was the largest, accounting for 33.96% of the total area; the second-lowest-risk and low-risk areas together accounted for 27.09%. The areas with the highest risk of heavy rainfall and flooding in Zhengzhou were in the Erqi, Guanchenghui, Jinshui, Zhongyuan, and Huizi Districts and the western part of Xinmi City; these areas should be given priority attention during disaster monitoring and early warning and risk prevention and control.

Multi-domain human-oriented approach to evaluate human comfort in outdoor environments

Human comfort outdoors is widely investigated, but most studies explore the comfort domains singularly. This paper aimed to evaluate human comfort in parks, verifying the importance of using a multi-domain (simultaneously evaluating thermal, visual, acoustic, and air quality) and multi-disciplinary (combining environmental and social fields) approach. A walk through a pre-defined path from one park to another was repeated twice per day on four consecutive days in June, with three participants per walk. The two investigated parks are in central Italy and were chosen because they differ in their design and spatial characteristics. Environmental data were recorded with an innovative wearable device during the whole walk, and surveys were used to assess people's perceptions of the parks. Despite observed differences in collected physical parameters, the survey's responses were similar, and different comfort domains showed dependence on each other in the two parks. Logistic regression models were developed for each park, and they revealed that the qualitative information predicted the overall comfort level more accurately than the environmental data. In detail, the models based on environmental data resulted in R² equal to 0.126 and 0.111 in Parks 1 and 2, respectively, whereas using the survey answers increased it up to 0.820 (Park 1) and 0.806 (Park 2). This study contributes to addressing the gap in multi-domain comfort studies outdoors and confirms the importance of using multi-disciplinary and multi-domain approaches for a complete comfort analysis, supporting holistic human-biometeorology-oriented models and forecasting opportunities that can promote improvements in urban environmental quality and liveability.

Green Space Cooling Effect and Contribution to Mitigate Heat Island Effect of Surrounding Communities in Beijing Metropolitan Area

With the rapid process of urbanization and global warming, many metropolises are vulnerable to high temperatures in summer, threatening the health of residents. However, green spaces can generate a cooling effect to mitigate the urban heat island effect in big cities. They can also help to improve the living quality and wellbeing of surrounding residents. In this paper, we utilized the radiative transfer equation algorithm, k-means clustering algorithm, big data crawling, and spatial analysis to quantify and map the spatial distribution, cooling capacity, and cooling contribution for surrounding communities of 1,157 green spaces within Beijing Fifth Ring Road, a typical metropolitan area. The findings showed that (1) the area proportion of the heat island in the study area is larger than that of the cooling island. Accounting for only about 30% area in the study area, the green spaces reduce the average land surface temperature by 1.32°C. (2) The spatial features of green space, such as area and shape complexity, have a significant influence on its cooling effect. (3) Four clusters of green spaces with specific spatial features and cooling capacity were identified. And there were differences among these clusters in green space cooling contribution for the surrounding communities. (4) The differences in green space cooling contribution also existed in different urban zones. Specifically, the middle zone performed significantly better than the inner and outer zones. (5) We furthered in finding that some green spaces with medium and high cooling contributions need to improve their cooling capacity soon, and some green spaces with low cooling contributions or no contributions have a good potential for constructing new communities in the future. Our study could help planners and government understand the current cooling condition of green spaces, to improve their cooling capacity, mitigate the urban heat island effect, and create a comfortable and healthy thermal environment in summer.

Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China

The changes of land use/land cover (LULC) are important factor affecting the intensity of the urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses cellular automata (CA) and artificial neural network (ANN) to predict future changes in LULC and LST. The results show that the built-up area of Wuhan has expanded, reaching 511.51 and 545.28 km2, while the area of vegetation, water bodies and bare land will decrease to varying degrees in 2030 and 2040. If the built-up area continues to expand rapidly, the proportion of 30~35 °C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 °C will expand to 15.264 and 33.612 km2, respectively. The direction of the expansion range of the LST temperature range is obviously similar to the expansion of the built-up area. In order to control and alleviate UHI, the rapid expansion of impervious layers (built-up areas) should be avoided to the greatest extent, and the city’s “green development” strategy should be implemented.

Smart City Governance Evaluation in the Era of Internet of Things: An Empirical Analysis of Jiangsu, China

With the rapid development of smart cities all over the world, the evaluation of the smart city has become a new research hotspot in the academic circles. Nevertheless, there still exist a series of common problems in current smart city evaluation, including the cognitive deprivation, lack of experience in planning, low coordination level, etc. Therefore, it is critical to establish a new hierarchy for smart city evaluation indicators, especially in the 5G era. Based on literature review, expert consensus, and the fuzzy analytic hierarchy process, this study developed an innovative smart city evaluation framework. In the framework, an index comprising three dimensions, i.e., smart economy, smart society, and smart environmental protection, as well as several attributes for these dimensions for smart city evaluation were established. Then, taking Jiangsu Province, the fastest-growing province in China, as the research area, the development level of smart city for the cities in Jiangsu was calculated. The results have verified the effectiveness of the framework, which can provide suggestions for sustainable urbanization, and help urban decision-makers to promote the efficient development of smart cities.

Tourism Effect on the Spatiotemporal Pattern of Land Surface Temperature (LST): Babolsar and Fereydonkenar Cities (Cases Study in Iran)

The purpose of this study is to investigate the effect of tourism on Land Surface Temperature (LST), an issue which has rarely been considered in the tourism development literature. In this research, remote sensing techniques have been used to analyze the changes in the LST and spectral indices including the Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI) and Enhanced Built-Up and Bareness Index (EBBI). The data used were based on Landsat Collection 1 Surface Reflectance (SR) images taken in June and August. They were analyzed over 32 years in the years 1987, 1993, 1999, 2009, 2014 and 2019. The study area included the cities of Babolsar and Fereydonkenar and their suburbs in Mazandaran Province in the north of Iran and south of the Caspian Sea. First the tourism zones were separated from other land use zones and then the changes in land use and LST in each of the zones were studied for each year based on the trend of 32-year change. The results of Pearson correlation in the whole area for each main land use zone showed that there was a significant inverse relationship between the LST and the NDVI and MNDWI indices. This relationship was direct and significant for the EBBI index. Moreover, the results of one-way analysis of variance (ANOVA) and Tukey test showed that the LST changes in the tourism zones during the study period were significantly different from the other zones, so that the tourism zones always experienced lower LST. The findings also showed that, in the tourism zones, the values of the NDVI and MNDWI indices showed an increasing trend compared to the urban zone. Therefore, increasing the values of these indices due to the development of green space and its regular irrigation in tourism zones has led to a significant decrease in the LST. The applied results of this research in the urban planning and tourism literature indicate that any model of physical development such as urban development does not necessarily lead to an increase in the LST, and this is entirely dependent on the physical design strategies.

Assessing the Cooling Effect of Four Urban Parks of Different Sizes in a Temperate Continental Climate Zone: Wroclaw (Poland)

Urban parks have been known to form park cooling islands (PCI), which can effectively alleviate the effect of urban heat islands (UHI) in cities. This paper presents results obtained for four different size parks in the city of Wroclaw, which is located in a temperate continental climate. The number of publications for urban areas located in this type of climate and cities is low compared to sites in hot and humid areas. Land surface temperature (LST) maps were developed from Landsat 8 Thermal Infrared Sensor (TIRS) data acquired during three hottest weather periods between 2017 and 2019. Metrics and spatial statistics characterising the four parks selected for the analysis based on their size were calculated. These included: perimeter, area, landscape shape index (LSI) and PLC (forest area) park metrics, and Park Cooling Area (PCA), Park Cooling Efficiency (PCE), Park Cooling Gradient (PCG), Park Cooling Island (PCI) and Extended Park Cooling Island (PCIe) spatial indexes. The averaged PCIe values ranged from 2.0 to 3.6 °C, PCI from 1.9 to 3.6 °C, PCG from 0.7 to 2.2 °C, PCE from 5.3 to 11.5, and PCA from 78.8 to 691.8 ha depending on the park. The cooling distance varied from 110 m to 925 m depending on park size, forest area and land use type in the park’s vicinity. The study provides new insight into urban park cooling effects in a medium sized city located in a temperate continental climate, and the role of parks in regulation of urban temperature to mitigate the UHI effect.

Analyzing the Characteristics of UHI (Urban Heat Island) in Summer Daytime Based on Observations on 50 Sites in 11 LCZ (Local Climate Zone) Types in Xi’an, China

Urbanization has induced significant changes on local climate in urban areas. For sustainable urban planning, it is necessary to identify the distribution characteristics of urban heat island (UHI) and the effects of land cover properties. In situ measurements are frequently carried out to obtain critical data in urban climate studies. However, long-time continuous observations on multiple sites are still rare, even though they would be useful in mapping the distribution of UHI intensity. In the current work, three observation campaigns were carried out in Xi’an, China. Pedestrian- level air temperatures (PLAT) were measured with potable micro-environment stations on 50 sites in 11 local climate zone (LCZ) types. The normalized PLAT was used to investigate the canopy layer UHI characteristics and the effects of LCZ types. Results revealed that the land coverage type and the surface structure have significant influence on the local climate. The PLAT in high-surface-fraction building covered areas was higher than that in low-surface-fraction building covered areas. In areas with similar building surface fraction, building height influences the UHI magnitude as well, as tall buildings would provide more shielding on the pedestrian level. The average UHI magnitude and the standard deviation within each LCZ type were calculated by statistical analysis of the observed results, which proved to be useful for UHI mapping based on the LCZ classification results in urban areas.

Conceptual Planning of Urban–Rural Green Space from a Multidimensional Perspective: A Case Study of Zhengzhou, China

The structure and function of green-space system is an eternal subject of landscape architecture, especially due to limited land and a need for the coordinated development of PLEs (production, living, and ecological spaces). To make planning more scientific, this paper explored green-space structure planning via multidimensional perspectives and methods using a case study of Zhengzhou. The paper applies theories (from landscape architecture and landscape ecology) and technologies (like remote sensing, GIS—geographic information system, graph theory, and aerography) from different disciplines to analyze current green-space structure and relevant physical factors to identify and exemplify different green-space planning strategies. Overall, our analysis reveals that multiple green-space structures should be considered together and that planners and designers should have multidisciplinary knowledge. For specific strategies, the analysis finds (i) that green complexes enhance various public spaces and guide comprehensive development of urban spaces; (ii) that green ecological corridors play a critical role in regional ecological stability through maintaining good connectivity and high node degree (Dg) and betweenness centrality index (BC) green spaces; (iii) that greenway networks can integrate all landscape resources to provide more secured spaces for animals and beautiful public spaces for humans; (iv) that blue-green ecological networks can help rainwater and urban flooding disaster management; and (v) that green ventilation corridors provide air cleaning and urban cooling benefits, which can help ensure healthy and comfortable urban–rural environments. In our view, this integrated framework for planning and design green-space structure helps make the process scientific and relevant for guiding future regional green-space structure.