Urban Climate Mapping Based on Structural Landscape Features: The Case of Ankara

Urban areas are particularly affected by climate change due to continuing urban development and an increased occurrence of extreme weather events like heat waves that lead to increasing heat stress on urban population. Furthermore, the occurrence of heavy rain events and dry periods are expected to rise, posing additional challenges to cities because sealed surfaces inhibit the infiltration of water into the soil and thus increase storm water runoff and reduce the water availability for plants. The project GreenAdaptation, funded by the Austrian Climate Research Program (ACRP), examines crucial steps necessary to support climate change adaptation and to develop urban planning recommendation and climate analysis maps for cities and municipalities, as they provide an important tool to support urban planners and local administrations towards decision making and to facilitate future urban planning processes. Urban climate analyses represent an essential component in the development of urban planning recommendation maps. Here, we focus on already existing climatological datasets as well as urban climate modelling tools. To gather pre-existing knowledge regarding temperature and precipitation change, a set of climate indices with respect to heat, heavy rainfall and drought are selected together with practitioners implementing adaptation measures. The climate indices are calculated using available observational datasets from the Austrian semi-automatic meteorological station network (TAWES) and Austrian climate scenarios (OEKS15) to assess the past and indicate future development for the chosen municipality. Urban climate simulations carried out by the urban climate model MUKLIMO_3, developed by DWD (German Meteorological Service), are used to analyze overheating and to identify areas particularly affected by heat, taking into account city-specific structures and land use information, as well as meteorological conditions. Furthermore, a digital elevation model is analyzed to identify areas potentially prone to flooding. Merging the derived maps will indicate critical zones prone to extreme weather impacts, but also areas with a high synergy potential for climate adaptation. The methodological framework for the consolidation and integration of the analyses into urban planning recommendation maps will be demonstrated and results of the urban climate analysis will be shown for the Municipality of Perchtoldsdorf, Lower Austria.

Urban climate modified short-term association of air pollution with pneumonia mortality in Hong Kong

The rapid urbanization of Jaipur has profoundly altered its urban climate, driven by anthropogenic heat flux (AF) and shifts in surface energy dynamics. This study leverages remote sensing techniques, utilizing Landsat data, to quantify AF and assess its influence on the city’s climate. The findings reveal a striking paradox; despite a significant rise in AF from 127.31 W/m2 in 1993 to 201.82 W/m2 in 2020, Jaipur exhibits an anomalous urban cool island (UCI) effect during the daytime. In this phenomenon, surrounding fallow lands experience higher land surface temperatures (LSTs) than the urban core, defying the typical urban heat island (UHI) effect observed in most cities worldwide. This paradox is especially pronounced in semi-arid urban environments, where factors such as limited vegetation, arid conditions, and water scarcity intricately shape peculiar thermal behaviour. This study further highlights the role of urban expansion, with built-up areas growing from 11.95% in 1993 to 19% in 2020, intensifying AF. Notably, the latent heat flux was highest in vegetated areas, significantly reducing LSTs by facilitating evapotranspiration. Daytime surface temperatures have surged significantly, with temperatures ranging from 26–46.9 °C in 1993 to 31–56.5 °C in 2020, indicating an overall increase in surface heat intensity. Despite these increases, the UCI effect remains observable, further illustrating the cooling potential of urban vegetation. This study offers novel insights into the intricate dynamics of urban heat in semi-arid cities, providing refined perspectives on urban heat mitigation strategies and climate adaptation, with implications for future sustainable urban planning and environmental management.

Understanding the spatial growth of cities is crucial for proactive planning and sustainable urbanization. The largest and most densely inhabited megapolis of Pakistan, Karachi, has experienced massive spatial growth not only in the core areas of the city, but also in the city’s suburbs and outskirts over the past decades. In this study, the land use/land cover (LULC) in Karachi was classified using Landsat data and the random forest algorithm from the Google Earth Engine cloud platform for the years 1990, 2000, 2010, and 2020. Land use/land cover classification maps as well as an urban sprawl matrix technique were used to analyze the geographical patterns and trends of urban sprawl. Six urban classes, namely, the primary urban core, secondary urban core, sub-urban fringe, scatter settlement, urban open space, and non-urban area, were determined for the exploration of urban landscape changes. Future scenarios of LULC for 2030 were predicted using a CA–Markov model. The study found that the built-up area had expanded in a considerably unpredictable manner, primarily at the expense of agricultural land. The increase in mangroves and grassland and shrub land proved the effectiveness of afforestation programs in improving vegetation coverage in the study area. The investigation of urban landscape alteration revealed that the primary urban core expanded from the core districts, namely, the Central, South, and East districts, and a new urban secondary core emerged in Malir in 2020. The CA–Markov model showed that the total urban built-up area could potentially increase from 584.78 km2 in 2020 to 652.59 km2 in 2030. The integrated method combining remote sensing, GIS, and an urban sprawl matrix has proven invaluable for the investigation of urban sprawl in a rapidly growing city.

The aim of this research paper is to examine ways to integrated impact of the natural environment and typical urban morphological features on the thermal load into urban climate planning using spatially distributed information of local atmospheric zones (LAZs). To achieve this, the form and morphology of urban planning and their contents concerning urban heat island issues were examined in the 2557 BE summer season in Chiang Mai city area. Spatially distributed information on local atmospheric zones and their homogeneity of thermally-stabilized surface in the study area was generated using the spatial-multivariate analysis, which is an approach of urban climate analysis and evaluation tool suitable for planning purposes. The results found that the downtown-suburb continuum of local atmospheric zones with a hierarchy of 8 zones and an urban heat island intensity (UHII) can often exceed 4.35 Celsius in summer. An urban core of 20.88 square kilometer as the highly temperature-sensitive urban area is very densely built with a very high thermal load with the mean land surface temperature of 34.49 Celsius. Remedial measures and mitigation actions are urgently needed. Excessive development and construction should be strictly prohibited along the potential ventilation paths. Reasonable planning and reconstruction should improve severe urban climatic problems if possible. Building height imitations, rational spatial distribution, and controlling the aspect ratio of building height to canyon width and orientation in streets should be considered to avoid further urban environmental damage. Additional greenery and tree planting in open spaces and streets in this planning zone are strongly recommended. Moreover, greenery should be largely introduced around existing buildings, which can alleviate the thermal load and promote cool air exchange among buildings. Widening streets and preserving open space are long-term and effective measures.

Assessment of climate classification methodologies used in building energy efficiency sector

This study compares the results of air temperature model simulations with real temperature measurements in an urban environment. The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three different days was modelled which characterising the radiation-driven weather conditions with high temperature that occurred during the summer of 2015. This analysis demonstrates that the model is able to reproduce the spatial distribution of the air temperature during the day. Statistical tests were applied to establish whether significant differences exist between the modelled and measured air temperatures. Verification of the model results against real temperature measurements was performed at five meteorological stations. The mean absolute differences between the simulated and measured daily mean temperatures were 0.7 °C (4 July), 0.6 °C (18 July) and 0.5 °C (28 August), respectively. This demonstrates that the model overestimated the real values, however, not all the differences were statistically significant. Moreover, there were no significant differences in the variability of the temperatures that were compared. This study also shows that the proper definition of Local Climate Zones and their parameters is critical for more precise model performance.

5 - WRF/UCM simulation for city-scale UHI modeling

Background and Objectives: Urbanization refers to the change of both physical and human landscape structures within an area in response to socio-economic development. This transformation leads to a reduction in urban open spaces, alongside the expansion of diverse land uses into peri-urban areas, contributing to the decline of green spaces in both urban and rural environments. This research aims to assess the changes in landscape ecological structures during the period from 2011 to 2022 by monitoring the diversity of land cover types using the Landscape Mosaic (LM) model and the LM-Anthropic model to describe the main structures and continuity of landscape components, including developed areas, agricultural areas, natural areas, and mixed-use areas, in order to evaluate the condition of green spaces in Mueang District, Amnat Charoen Province. Methodology: This study applies geo-information technology to classify green and non-green areas based on Sentinel-2A satellite imagery, in conjunction with various indices, including the Normalized Difference Vegetation Index (NDVI), Bare Soil Index (NDBSI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI), using a hybrid classification method. The accuracy of the classification results was validated against ground truth points using real-time data collection via a Global Navigation Satellite System (GNSS). A confusion matrix was used to calculate overall classification accuracy and the Kappa coefficient, with the confidence level set at 80% and a minimum acceptance threshold of substantial agreement.The resulting data were further analyzed to examine landscape structure, patterns, and changes in order to assess spatial distribution, configuration, and component changes in relation to the intensity levels of human activities, following the principles of landscape ecology. Results: The land cover classification results for Mueang Amnat Charoen District in 2022 revealed an overall accuracy of 80.21% and a Kappa coefficient of 0.73, indicating substantial agreement. Agricultural land was the most dominant category, accounting for 60.46% of the area, followed by forest, barren land, perennial crops, community and built-up areas, and water bodies, at 8.59%, 6.85%, 4.72%, 1.85%, and 0.66%, respectively. These results characterize Mueang District’s core landscape structure as an agricultural matrix. Between 2011 and 2022, significant landscape changes were observed. The proportions of agricultural and natural landscape mosaics declined from 72.93% and 16.56% to 66.72% and 12.63%, respectively. In contrast, developed, mixed-use, and water landscape mosaics increased from 5.43%, 3.23%, and 1.84% to 8.93%, 9.83%, and 1.89%, respectively. Net changes in mosaic types revealed a transformation from uniqueness toward areas of dominance and presence. Specifically, dominant agricultural, natural, and developed mosaic types declined by 30.13%, 5.76%, and 1.48%, respectively, anrd were replaced by mixed-use mosaics influenced by the convergence of all three components.This pattern corresponds with the intensity levels of human activities. Areas of extreme activity intensity were concentrated in dense urban cores, covering 4.17% of the district. Moving outward from the urban center, the spatial pattern took on linear and dispersed forms, with decreasing levels of intensity and an increase in agricultural landscapes. Areas with very high and high levels of activity intensity accounted for 6.10% and 61.15%, respectively. Sparsely developed agricultural zones were categorized as moderate-intensity areas, comprising 13.59%. Low and very low-intensity areas —primarily undisturbed natural areas such as small and large forest patches and riparian woodlands—were scattered across urban and peri-urban areas, comprising 13.59% and 8.03% of the total area, respectively. Results: This study demonstrates the effective application of geo-information technology for quantitatively assessing green space conditions through Sentinel satellite imagery classification, integrated with multiple indices. The approach is further enhanced by incorporating landscape mosaic modeling and human activity intensity analysis to evaluate landscape structure. These models support spatial interpretation of interactions among developed urban areas, natural green spaces, agricultural land, and mixed-use areas—revealing patterns of uniqueness, dominance, and presence. The results highlight the directions and trends of landscape structural change, which potentially affect urban and community environments, particularly the loss of natural green space and open areas, and the ongoing expansion of urban zones characterized by increasingly complex land use. It offers essential spatial information to support planners in conserving and managing target areas for long-term sustainable environmental development.

Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India

基于“风感”的紧凑型城市开放空间风环境实测和CFD模拟比对研究

چکیده گسترش شهرنشینی و افزایش جمعیت در کلان شهرها از یک سو و رشد فعالیتهای صنعتی بزرگ از سوی دیگر باعث ایجاد تغییراتی بر خرداقلیم مناطق شهری شده است. یکی از عوامل عمده این تغییرات را می‌توان تبدیل شدن کلانشهرها به جزایر گرمایی دانست. بررسی تغییرات پارامتر‌های اقلیمی در شهرها با در نظر گرفتن شرایط مطلوب زیستی برای انسان از اهمیت زیادی برخوردار است. در این میان مطالعه تغییرات بارندگی که نقش مهمی در تعدیل آب و هوا و کاهش آلودگی شهرها دارد، ضرورت پژوهش‌های بیشتر را در این خصوص نمایان می‌کند. در این پژوهش، تغییرات بارندگی برای بررسی تغییرات خرداقلیم منطقه مورد مطالعه قرار گرفته است. بمنظور مطالعه این پدیده از نمایه UHI استفاده شد. این نمایه که بر اساس تفاوت دمای شهر با منطقه همجوار که تحت تأثیر افزایش دمای شهر نمی باشد است، امکان مطالعه تغییرات دمایی شهر را فراهم می‌نماید. نتایج حاصل از این پژوهش نشان می‌دهد که در ایستگاه مشهد تغییرات دمایی ناشی از جزیره گرمایی با روند تغییرات بارندگی همبستگی معنی داری داشته و با اطمینان قابل قبولی می‌توان تأثیر جزیره گرمایی را بر روی بارندگی پذیرفت. بر اساس این پژوهش پدیده جزیره گرمایی مشهد در فصل‌های سرد باعث کاهش بارندگی و در فصل‌های گرم باعث افزایش آن شده است. واژه‌های کلیدی: جزیره گرمایی، آلودگی هوا، خرد اقلیم، تغییر اقلیم

ABSTRACTSpring rainfall in Taiwan during February–April (FMA) shows a profound decreasing trend in the period 1980–2022. This decreasing trend is found to be jointly modulated by the trend components of global warming and interdecadal evolutions of the Pacific Decadal Oscillation (PDO) from its positive to negative phase over the past four decades. In contrast, interdecadal oscillation components of the PDO weakly impact interdecadal decreases in Taiwan's spring rainfall. Both global warming and interdecadal PDO variability cause moderate warming in the tropical western North Pacific and strong warming over the northern North Pacific. The former causes height fields over the tropical western Pacific to shift northward to result in an anomalous cyclone in association with the weakening of the subtropical high to the south of Taiwan. This anomalous cyclone is also affected by a Matsuno‐Gill‐type response to sea surface temperature warming and an anomalous convergent centre over the tropical western Pacific around 150° E. In the northern North Pacific, strong SST warming displaces height fields northward to make an anomalous anticyclone via the weakening of the Aleutian Low. Taiwan is meridionally embedded by the above anomalous cyclone and anticyclone. This circulation pair induces anomalous easterly moisture flux to pass over Taiwan, which then turns southward into the South China Sea. Moisture transport from the tropical region toward Taiwan is suppressed, resulting in an evident decrease in spring rainfall.

Structure of the urban open spaces and the effect it imposes on the body and mental health increases the importance of attention to the quality of such places. The thermal comfort is the environmental factors affecting the reactive behavior of people in urban open spaces. In the present study, aiming at investigating the relationship between psychic components and landscape structure and its effect on the thermal assessment of individuals, three methods are used; the descriptive method for explaining the psychic components and landscape structure as well as the survey method for determining the relation and correlation between research variables along with the experimental method for testing the variables using certain tools. Thermal analysis done by computer simulation method in ENVI-met software in the Karoon river area in Ahvaz city. The index used for assessing the thermal comfort is UTCI. In order to find the relationship between the research variables, the field data collections were accomplished by arranging questionnaires and in a random way by Cochran formula. The findings demonstrated the existence of a relationship between landscape structure and different psychic states in individuals. In fact, the moods of the individuals in open spaces affect their landscape qualification and thermal assessment. Eventually, and based on the findings of the study, it could be stated that the mental condition and psychic state of the individuals in different situations has definitely affected their qualification of the landscape structure, landscape quality as well as their reactive behavior while it would overshadow their thermal assessment.

Background: The urban open spaces and their effects on the physical and mental health highlights the attention on the quality of such spaces. Thermal comfort is an environmental component affecting the reactionary behavior of people in these spaces. The present study aimed to investigate the relationship between mental components and landscape structure and its effects on the thermal assessment of individuals. Methods: In this study, we used the descriptive method for explaining the mental components and landscape structure. Then, the survey method was employed for determining the correlations between research variables. Finally, we used the experimental method for testing the variables using specific tools. Thermal analysis was done by computer simulation method using ENVI-met software in the Karoon river area in Ahvaz City, Iran. UTCI (universal thermal climate index) is the index used for assessing thermal comfort. To find out the relationship between the research variables, the field data were randomly collected by questionnaires using the Cochran formula. Results: The findings demonstrated the existence of a relationship between landscape structure and different mental states in individuals. The moods of the individuals in open spaces affect their perceptions of the landscape and thermal assessment of the environment. Conclusions: Eventually, and based on the study findings, it was found that people’s mental states in different situations affect their perception of the landscape’s quality and structure and reactionary behavior. It also influences their thermal assessment.