Sky View Factor Research Articles

Street trees: The contribution of latent heat flux to cooling dense urban areas

Trees are the most important natural factor to alleviate the urban heat island effect and the latent heat flux (LE) they release contributes significantly to urban cooling. In this study, the model ENVI-met was used to study the influence of building geometry on the LE exchanged by trees at the block scale in compact urban areas. The building density (BD), building height (BH) and sky view factor (SVF) were used to characterize building geometry. The sensitivity of LE to building geometry was estimated by multi-linear regression analysis. The following conclusions were drawn:(1) the LE of trees is sensitive to building geometry, higher during daytime than night-time in winter and the higher during night-time than daytime in summer; (2) LE changes as expected across the seasons, with LE larger in summer; (3) The shade affects the LE of a tree by influencing the solar irradiance; (4) In winter the average LE of a single tree is larger with 0.06 than 0.12 fractional vegetation cover (FVC). This study can provide useful leads towards further research to explore latent heat exchanges by trees at the street scale.

Influence of view factors on outdoor thermal comfort of residential areas in hot-humid regions.

Sky View Factor (SVF) is commonly used to describe the impact of urban geometry on the urban thermal environment. Shading effects from plants and buildings also exert a considerable influence. To investigate the influence of view factors on outdoor thermal comfort in residential areas, we employed the Physiological Equivalent Temperature (PET) and view factors (SVF, TVF, BVF) as indicators to determine outdoor thermal comfort and the quantity of shaded spaces. Thermal measurements collected from 13 points in Guangzhou, China, Our findings revealed that high TVF points exhibited more stable air temperature throughout the daytime, with average temperature differentials ranging 0.4-1.9°C lower than other points. Air temperature demonstrated a positive correlation with SVF (R2 = 0.53), while exhibiting a negative correlation with TVF (R2 = 0.45). Additionally, shading provided by plants and buildings manifests heterogeneity. At similar SVF levels, points predominantly shaded by plants (TVF > BVF) showcased lower Mean Radiant Temperature (MRT) and PET compared to points shaded mainly by buildings (BVF > TVF). The maximum reduction in air temperature and PET reached 1.1°C and 1.2°C, respectively. BVF exerted greater influence earlier in the morning, as solar altitude angle rises, the average thermal parameters of sites with BVF > TVF escalated rapidly until eventually surpassing sites with TVF > BVF. Last, superior thermal conditions were only ensured under high shading conditions. When the effective shading ratio of plants and buildings diminished (SVF > 0.3), the microclimate of measurement points might be impacted by the long-wave radiation from the underlying surface.

Urban Heat Island Differentiation and Influencing Factors: A Local Climate Zone Perspective

With the acceleration of urbanization, the urban heat island (UHI) effect has become a major environmental challenge, severely affecting the quality of life of residents and the ecological environment. Quantitative analysis of the factors influencing urban heat island intensity (UHII) is crucial for precise urban planning. Although extensive research has investigated the causes of UHI effects and their spatial variability, most studies focus on macro-scale analyses, overlooking the spatial heterogeneity of thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, this study took the central urban area of Chengdu, constructing a LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze the spatial clustering effects of UHI across different LCZs. By constructing Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models, the study further explored the influencing factors within these climate zones. The results showed that: (1) Chengdu’s built and natural environments had comparable proportions, with the scattered building zone comprising the highest proportion at 22.12% in the built environment, and the low vegetation zone accounting for 21.8% in the natural environment. The UHII values in this study ranged from 10.2 °C to −1.58 °C, based on specific measurement conditions. Since UHII varied with meteorological conditions, time, seasons, and the selection of rural reference points, these values represented dynamic results during the study period and were not constant. (2) Chengdu’s urban spatial morphology and UHII exhibited significant spatial heterogeneity, with a global Moran’s I index of 0.734, indicating a high degree of spatial correlation. The highest local Moran’s I value was found in the proportion of impervious surfaces (0.776), while the lowest is in the floor area ratio (0.176). (3) The GWR model demonstrated greater explanatory power compared to the OLS model, with a fit of 0.827. The impact of spatial morphological factors on UHII varied significantly across different environments, with the most substantial difference observed in the sky view factor, which has a standard deviation of 13.639. The findings provide precise recommendations for ecological spatial planning, aiming to mitigate the UHI effect and enhance the quality of life for urban residents.

Green space-building integration for Urban Heat Island mitigation: Insights from Beijing's fifth ring road district

In this research, we delve into the complex arrangement of urban landscapes, where green spaces and buildings are not merely co-existing but are interwoven into a cohesive fabric that shapes the thermal environment. Our approach transcends the conventional methods of analysis, which typically isolate the roles of greenery or built environments. Instead, we adopt a synergistic perspective that recognizes the collective influence of these landscape constituents on the urban thermal pattern. Key insights are: (1) A linear decrease in average land surface temperature with increasing green space coverage is observed. However, substantial temperature variations (up to 8 °C) within the same coverage interval highlight the significant impact of built-up pattern on thermal conditions; (2) High Building Height and Floor Area Ratio, and low Building Coverage Ratio and Sky View Factor, are linked to cooler temperatures in areas with up to 50 % green space; (3) The study suggests that low-temperature areas can inform the adjustment of built-up patterns in high-temperature areas, offering a strategy for thermal environment optimization within specific green space coverage intervals. This research contributes insights into the integrated planning of green spaces and buildings, with implications for urban development and renewal initiatives aiming to enhance the urban thermal environment.

Thermal Comfort and Restorative Benefits of Waterfront Green Spaces for College Students in Hot and Humid Regions

Global climate change presents a serious threat to the sustainable development of human society, highlighting the urgent need to develop effective adaptation strategies to mitigate the impact of climate-related disasters. Campus waterfront green spaces, integral to the blue-green infrastructure, have been demonstrated to facilitate stress recovery. However, in hot and humid regions, severe outdoor thermal conditions may impair students’ mental and physical health and cognitive function, leading to symptoms such as increased stress, anxiety, and depression. This study examined the influence of outdoor thermal environments on health recovery by selecting three different waterfront green spaces in this climate: Space A (medium water body, sky view factor (SVF) = 0.228), Space B (large water body, SVF = 0.808), and Space C (small water body, SVF = 0.292). The volunteers’ thermal comfort and the restorative benefits of these spaces were evaluated via the perceived restorativeness scale (PRS), heart rate (HR), and electrodermal activity (EDA). We found variations in the neutral physiological equivalent temperature (PET) across the spaces, with values of 28.1 °C (A), 28.9 °C (B), and 29.1 °C (C). The lowest skin conductance recovery rate (RSC) at 0.8811 was observed in Space B, suggesting suboptimal physiological recovery, despite higher scores in psychological recovery (fascination) at 15.23. The level of thermal comfort in this hot and humid region showed a negative correlation with the overall PRS score, the “being away” dimension, and heart rate recovery (RHR). At a lightly warm stress level, where PET increased from 31.0 to 35.7 °C, RSC peaked between 1.45 and 1.53 across all spaces. These insights provide guidance for urban designers and planners in creating waterfront green space designs that can improve the urban microclimate and promote thermal health, achieving sustainable health.

The Mechanism of Street Spatial Form on Thermal Comfort from Urban Morphology and Human-Centered Perspectives: A Study Based on Multi-Source Data

The influence of street spatial form on thermal comfort from urban morphology and human-centered perspectives has been underexplored. This study, utilizing multi-source data and focusing on urban central districts, establishes a refined index system for street spatial form and a thermal comfort prediction model based on extreme gradient boosting (XGBoost) and Shapley additive explanations (SHAP). The results reveal the following: (1) Thermal comfort levels display spatial heterogeneity, with areas of thermal discomfort concentrated in commercial zones and plaza spaces. (2) Compared to the human-centered perspective, urban morphology indicators correlate strongly with thermal comfort. (3) The key factors influencing thermal comfort, in descending order of importance, are distance from green and blue infrastructure (GBI), tree visibility factor (TVF), street aspect ratio (H/W), orientation, functional diversity indices, and sky view factor. All but the TVF negatively correlates with thermal comfort. (4) In local analyses, the primary factors affecting thermal comfort vary across streets with different heat-risk levels. In high heat-risk streets, thermal comfort is mainly influenced by distance from GBI, H/W, and orientation, whereas in low heat-risk streets, vegetation-related factors dominate. These findings provide a new methodological approach for optimizing urban thermal environments from both urban and human perspectives, offering theoretical insights for creating more comfortable cities.

Exploring the regional cooling efficiency of urban residential vegetation using scenario simulation

The study of the cooling efficiency of vegetation in urban residential areas at a micro-scale is important for improving the thermal environment of those areas. The quantitative analysis of the effect of the layout of different building patterns on the cooling efficiency of green space is particularly crucial. This study takes a typical residential area with a row-column arrangement in Jiangning District, Nanjing City, Jiangsu Province, China, as the research object. Using the ENVI-MET model used for numerical simulation, 15 simulation scenarios were designed based on building orientation, height, and density. The research proposes the methodology of the regional cooling efficiency (RCE) of urban residential vegetation, reveals the daily variation characteristics of the RCE of vegetation in a residential area, and analyzes the factors influencing of regional cooling efficiency. The results showed that the daily variation in RCE for vegetation in the residential area exhibited a single-peak trend. The minimum and maximum RCE values appeared at 6:00 and 14:00, respectively. The average air temperature and building density in the residential area had a significant positive correlation with RCE, while average relative humidity had a negative correlation. Average wind speed, average building height, and average sky view factor showed nonlinear correlations with RCE, and the importance ranking of each factor's effect on RCE was air temperature > relative humidity > building density > wind speed > building height > sky view factor. This study will provide theoretical support for improving the thermal environment in urban residential areas during the urban planning process.

Is LCZ Enough? Physical Properties, Thermal Environments and Cooling Effects of Green Roofs in High-Density Urban Industrial Blocks

With rapid worldwide urbanization, the urban heat island (UHI) effect is becoming more and more serious. The UHI effect is more intense in industrial areas. Green roofs are an effective way to mitigate UHIs in high-density cities, which calls for thorough examination. This study explored the associations between the block characteristics and block thermal environment in high-density industrial areas based on the widely accepted Local Climate Zone (LCZ) scheme. The pedestrian air temperature comparisons before and after virtual green roof installations presented the cooling effects of green roofs. Thirty-six typical industrial blocks were involved in the study and the simulations were conducted utilizing ENVI-met. The results showed that (1) the air temperature in LCZ4 is significantly lower than those in LCZ2 and LCZ6, but no significant differences were identified between other pairs of LCZ types; (2) the cooling effect of green roofs significantly differs among LCZs, and is associated with sky view factor (SVF), average building area (ABA) and average building shape index (ABSI); (3) in high-density urban areas, additional functional parameters and building-volume indices should be included to better address the physical characteristics, thermal environment, and green roof cooling effect of industrial blocks. This study could improve the validity of LCZ classification for high-density industrial blocks and may provide direct implications for green roof planning.

Experimental and theoretical study on building integrated radiative cooling with a limited sky-view factor

Building integrated radiative cooling (BIRC) technology leverages the coldness of outer space through the 8–13 μm atmospheric window for cooling. While BIRC's thermal performance has been widely studied across various climates, urban areas with obstructed sky views pose unique challenges often overlooked. To address this gap, the sky-view factor (SVF) was introduced as a metric to gauge BIRC effectiveness in urban settings. The novelty of this study lies in the experimental validation of SVF's impact on radiative cooling. A novel theoretical model was developed and validated, which was then applied to calculate BIRC's hourly, monthly, and year-round cooling power under Shenzhen's varying SVF conditions. The results revealed significant temperature drops in the RC module, ranging from 4.57 °C to 0.11 °C as SVF decreased from 0.7 to 0.1. Additionally, a numerical model was created based on experimental data, further validating the findings. This comprehensive analysis of SVF's effects on BIRC in Shenzhen's climate demonstrated that RC capacity averaged 57.27 W/m2 for SVF 0.9 but dropped below 22.55 W/m2 when SVF decreased to 0.3 or lower throughout the year. These insights enhance our understanding of BIRC's potential and limitations in densely populated urban environments.

Exploring the climatic conditions effect on spatial urban photovoltaic systems development using a spatial multi-criteria decision analysis: A multi-city analysis

Identifying suitable locations for urban photovoltaic systems (UPVS) is crucial for achieving sustainable energy objectives and designing smart, eco-friendly cities. This study assesses the potential for UPVS expansion in eight cities across different climatic zones in Iran using a spatial multi-criteria decision-making method. Two scenarios were analyzed: the first compared spatial potential within each city, and the second compared potential between cities. The findings indicate that rooftops of the tallest buildings in densely populated areas, especially those with high solar energy output and sky view factor, hold the greatest potential for UPVS development. These locations are often near parks, commercial centers, and road networks. In the first scenario, Ardabil (5.70%), Gorgan (4.65%), Mashhad (5.46%), Tehran (8.10%), Kermanshah (5.76%), Shahrekord (3.41%), Kerman (8.67%), and Zahedan (8.56%) show significant potential for photovoltaic development. In the second scenario, cities in hot, dry climates like Zahedan and Kerman exhibit greater potential compared to cities in moderate, humid climates like Ardabil and Gorgan. Based on the analysis of this scenario, Ardabil (0.04%), Gorgan (1.49%), Mashhad (5.58%), Tehran (5.06%), Kermanshah (0.00%), Shaherkord (0.03%), Kerman (21.70%) and Zahedan (39.11%) showed a very high potential for UPVS development. The results of this study offer valuable insights for urban solar energy planning.

Scale effect on the relationship between urban landscape patterns and land surface temperature

Great efforts have been made to examine the linkages between land surface temperature (LST) and urban landscape patterns (ULPs), which, however, focus on a single spatial scale and linear relationships. This study aims to examine the influence range of four key ULP indicators on LST, namely sky view factor (SVF) and three indices of built-up area, greens, and blue spaces. The analyses are conducted at street block level in 38 big cities in China, and leverage a multiscalar approach to investigate change patterns of indicators within multiple buffer zones and identify the buffer distance that yields the greatest influence. Results reveal that (1) the greatest local impacts are produced within 0−150 m buffer zones in most cities for all key ULP metrics; (2) the maximum impacts of most indicators in summer are greater than other seasons; and (3) the influence magnitude of key ULP indicators increase after considering scale effect, and the influence of SVF varies significantly across cities. Results suggest that the consideration of maximum influence ranges of ULP indicators can better explain LST spatial variations. Our findings offer evidence on the local impact of ULPs on LST and contribute to urban design in urban heat mitigation.

A WRF-UCM-SOLWEIG framework for mapping thermal comfort and quantifying urban climate drivers: Advancing spatial and temporal resolutions at city scale

The capability to evaluate city-scale outdoor thermal comfort is crucial for understanding the public's experience of heat stress, especially during heat waves. Nevertheless, there remains a methodological gap in accurately mapping thermal comfort with high spatial and temporal resolutions in complex urban environment and in quantifying the contributions of various urban climate drivers, such as sky view factors and tree canopy fraction. To bridge this gap, we propose an innovative WRF-UCM-SOLWEIG framework that couples a mesoscale model with an urban microclimate model. Specifically, it integrates the Weather Research and Forecasting model coupled with the urban canopy model (WRF-UCM) and the Solar and Longwave Environmental Irradiance Geometry model (SOLWEIG). This framework is then applied to a densely populated tropical city in China, to quantify the impact of urban climate drivers on the Universal Thermal Climate Index (UTCI). The results reveal a significant diurnal variation in the impact of urban morphology. Notably, the most significant drivers affecting daytime UTCI are the impervious surface fraction and the tree canopy fraction, with maximum Pearson's correlation coefficients of 0.80 and -0.70, respectively. These findings suggest that urban heat mitigation strategies should prioritize on reducing impervious surfaces and enhancing shade management, alongside expanding urban forestry measures.

Multi-dimensional distribution prediction of PM2.5 concentration in urban residential areas based on CNN

Air pollution has been one of the major environmental health issues in urban residential areas. Enhancing the air quality of the human environment has become a relevant research topic, but the study of the distribution characteristics of air pollutants under the influence of multi-dimensional indicators of residential building design is rarely considered. Herein, the PM2.5 spatial distribution of residential environment in Hefei, China, was simulated using ENVI-met. This research explored the influence mechanism of different design indexes on PM2.5 in the residential environment. A fast prediction method was proposed for PM2.5 based on the convolutional neural network (CNN). Furthermore, 4183 test points in the residential environment were selected to explore the influence of design indexes on PM2.5. The morphological features around the test points were transform to the images as input datasets for CNN model training. Results indicated that the PM2.5 mass concentration in the residential area decreases with the increase in height, and it is correlated with the sky viewfactor, the average height of the building and the density of the building. The accuracy of the CNN prediction model exceeds that of the ANN prediction model by 14.2 %, and the results can effectively predict the multi-dimensional distribution of the PM2.5 mass concentration in the residential environment, which could provide an effective reference and analytical tool for the creation of a healthy environment in residential areas.

Urban surface-emitted longwave radiation estimation from high spatial resolution thermal infrared images using a hybrid method

Accurate estimation of the surface-emitted longwave radiation (SELR) has important scientific value in understanding its spatiotemporal dynamics and surface thermal environment. Thermal infrared (TIR) images with high spatial resolution offer enhanced data support for studying SELR of complex surfaces, such as urban surface. This study proposes a new urban-oriented hybrid (UoHy) method, which considers multiple scattering and adjacent effects of urban pixel using the term sky view factor, to estimate urban SELR from the top-of-atmosphere radiance of TIR images with high spatial resolution, and performs sensitivity analysis and application. The experimental results for the thermal images of GF-5/VIMS as an example showed that the UoHy method has relatively high accuracy, and obtains SELR errors of less than 12.0 W/m2 under low atmospheric water vapor conditions and less than 17.0 W/m2 under high atmospheric water vapor conditions. The application of the method during daytime and nighttime also demonstrated the method's validity and effectiveness. Compared with the natural surface-oriented hybrid method, the UoHy method obtains an improvement of about 7.0–10.0 W/m2 in SELR estimation, which indicates that it has the potential for practical SELR estimation over urban surface with TIR images of high spatial resolution.

The effect of urban form parameters on annual and diurnal cycles of land surface temperature with 30-meter hourly resolution

Understanding dynamic changes in urban land surface temperature (U-LST) is vital for improving urban thermal environment. Previous studies noted a close association between two/three-dimensional (2D/3D) urban form parameters (UFPs) and U-LST, but divergent conclusions emerged due to study scale and data spatiotemporal resolution. This study investigated the effect of 2D/3D UFPs on multi-temporal (hourly, diurnal, and annual) U-LSTs with 30-m spatial resolution, which is the first exploration of such dynamics at this fine scale. In addition, the influence of local climate zones (LCZs) was considered. Results showed that 2D/3D vegetation UFPs have the greatest summer cooling effect at 21:00, while 3D building UFP sky view factor (SVF) impacts minimum nighttime temperature more (5:00). The independently total explained variances (R2) of 2D UFPs (0.2–0.7) on seasonal average U-LSTs were higher than that of 3D UFPs (0.1–0.4) in most LCZs. LCZ 3 and LCZ 2 had the highest seasonal and daytime U-LST, respectively. Interestingly, SVF replaced normalized difference vegetation index as the dominant factor in LCZs 4–6 and LCZs A-C after summer. Findings of this study are useful for guiding urban planning, formulating urban heat island mitigation policies, and promoting sustainable development goals (SDGs 11, 13, 15) of cities and communities.

A panorama-based technique to estimate sky view factor and solar irradiance considering transmittance of tree canopies

Street-view-based techniques for assessing the sky view factor (SVF) and solar irradiance under trees are gaining attention as tools for evaluating trees as nature-based solutions to mitigate urban heat risks. Although these metrics significantly depend on the morphology of trees and resulting canopy transmittance, an existing approach, termed the Solid Canopy Method (SCM), assumes zero transmission and has not accounted for these variations. This paper advances the computation of both metrics, improving their accuracy and application — we developed the Transmissive Canopy Method (TCM), a panorama-based approach that integrates semantic segmentation and binarization to evaluate SVF and solar irradiance while accounting for transmittance of tree canopies. Using a study area on a university campus in Singapore, we collected data on solar irradiance and 360°imagery to validate our method. The results indicated improved accuracy with MAE, RMSE, and R2 values of 77.8 Wm−2, 105.0 Wm−2 and 0.90, respectively — significantly outperforming the SCM. We showcased two use cases of our method: (1) high-resolution mapping of SVF and solar irradiance in a field with trees, and (2) walking route optimization considering sunlight exposure. Our findings highlight the strong capability of our TCM to evaluate the effects of trees in mitigating urban heat more accurately than the existing method. Additionally, the TCM has potential applications in urban planning and management, enabling strategic tree planting prioritizing areas lacking sufficient shading and developing tools for optimizing walking routes to minimize sunlight exposure.

Examining the suitability of the local climate zones (LCZ) framework in informal urban settlements: Insights from Kabul, Afghanistan

To better investigate the Urban Heat Island (UHI) effect, a standardized framework known as Local Climate Zones (LCZ) has been developed and widely applied to numerous cities. However, cities from least-developed countries with heterogeneous typologies are underrepresented in the LCZ literature. This study assesses the applicability of the LCZ framework in the slum-dominant built-up environment of Kabul. Using a combined method involving GIS and remote sensing, we classified natural and built-type LCZs and analyzed LCZ-LST fluctuations. The analysis revealed that four new subclasses cover 23 % of the built type LCZs: LCZ 35 (mid/high-rise buildings within compact lowrise layouts) and LCZ 65 (midrise buildings among open lowrise areas) have the lowest LSTs at 34.36 °C and 34.42 °C in July, respectively. In contrast, LCZ 73 (two/three-story buildings in lightweight configurations), and LCZ 9F (sparse buildings on bare soil or sand) have higher LSTs at 37.2 °C and 38.6 °C in July, respectively. These subclasses showed distinct zone parameter thresholds compared to standard LCZs. In most built-type LCZs, Average Building Height (ABH) and Pervious Surface Fraction (PSF) negatively influenced LST, while impervious surfaces and Sky View Factor contributed to higher LST. Based on the findings, LCZ-specified strategies (Vegetation, urban form, and using high-albedo materials) for LST mitigation are proposed. Furthermore, we provide planning, design, and policy recommendations aimed at mitigating urban heat, with potential applicability to other cities facing rapid urbanization and growth of informal settlements. The findings can inform action toward urban climate change adaptation.

Role of Urban Trees in Enhancing the Thermal Comfort of Rapidly Urbanizing Cities: An Analysis of Tropical Asian Tree Species Based on Physiological Equivalent Temperature (PET)

AbstractBackgroundThermal comfort significantly influences well-being, productivity, and living conditions in outdoor environments, particularly in rapidly urbanizing, warm, humid tropical climates. This study assessed the influence of 5 five common urban tree species (Cassia fistula,Tectona grandis,Plumeria obtusa,Mangifera indica, andTerminalia catappa) on outdoor thermal comfort, using the physiological equivalent temperature (PET) index in Colombo, Sri Lanka, as a case study for a tropical humid city.MethodsField data collection encompassed measuring air and surface temperature, relative humidity, wind velocity, solar radiation, cloud cover, and sky view factor under tree canopies and adjacent exposed areas. The RayMan model was employed to estimate PET in both areas.ResultsOur findings indicated that PET was consistently higher in exposed areas compared to under the tree canopy, with an average difference of 5.61 °C. Among tree parameters, sky view factor (SVF) demonstrated the most significant correlation with thermal comfort, followed by crown diameter and tree height. Furthermore, notable variations in thermal comfort were observed among tree species, withTerminalia catappaoutperformingPlumeria obtusa, particularly on sunny days.ConclusionRegression analysis highlighted the importance of integrating trees with large crowns and low SVF to create thermally comfortable outdoor spaces. Consequently,Terminalia catappaemerged as the most suitable tree species for enhancing thermal comfort in Colombo’s outdoor urban areas out of the 5 selected species. These insights will aid in selecting appropriate tree species and parameters, fostering improved outdoor thermal comfort in tropical humid cities, and facilitating sustainable urban planning and design strategies.

Identification of Urban Ventilation Corridor System Using Meteorology and GIS Technology: A Case Study in Zhengzhou, China

Urban ventilation corridors are designed to enhance air quality, alleviate urban thermal conditions, reduce pollution and energy consumption, as well as improve human comfort within cities. They play a pivotal role in mitigating environmental impacts, particularly in densely populated urban areas. Based on satellite remote sensing data, meteorological observations, basic geographic information of Zhengzhou City and its surroundings, and urban planning data, we analyzed the urban wind environment, urban heat island, ecological cold sources, and ventilation potential. The findings reveal several key insights: (1) Dominant winds in Zhengzhou City predominantly originate from the northwest, northeast, and south, influenced by topography and the monsoon climate, with seasonal variations. These wind patterns are crucial considerations for designing primary ventilation corridors. (2) The urban heat island exhibits a polycentric spatial distribution, with intensity decreasing from the city center towards the periphery. Ecological cold sources, primarily situated in the city outskirts, act as reservoirs of fresh air that mitigate the urban heat island effect through designated corridors. (3) A preliminary corridor system, termed “eight primary and thirteen secondary corridors”, is proposed for Zhengzhou City based on an integrated assessment of ventilation potential, urban surface roughness, and sky view factor. This research contributes to advancing the understanding of urban ventilation systems and provides practical insights for policymakers, urban planners, and researchers seeking sustainable solutions to mitigate climate impacts in rapidly urbanizing environments in the region.

Sky-view factor enhanced doline delineation: A comparative methodological review based on case studies in Slovenia

This study presents a novel method for the accurate delineation of dolines in karst areas. The method is based on the use of hydrological tools and sky-view Factor in ArcGIS Pro and was implemented using a digital elevation model with a resolution of 1 m in four study areas in Slovenia. We manually delineated dolines at four test areas and compared them with the results of the new method, as well as the results of the most commonly used method of hydrological filling and the results of U-Net segmentation. We calculated the average deviation of the perimeter and the differences in the basic morphometric properties. The hydrological filling method cannot be accepted as a suitable method for doline delineation and should only be used for doline identification. The method based on the U-Net segmentation performed better, but the results contain landforms that are not enclosed depressions and therefore cannot be considered as dolines. The new method utilizes the advantages of hydrological filling and at the same time improves the doline delineation. We conclude that the presented method is the most suitable for automatic doline identification and delineation among the automatic methods discussed in this paper. This study further quantifies the enhancements achieved with the new method, highlighting the specific improvements in perimeter accuracy and the reliability of morphometric measurements.