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The visual quality and spatial distribution of architectural styles represent a city's image, influence inhabitants' living conditions, and may have positive or negative social consequences which are critical to urban sensing and designing. Conventional methods of identifying architectural styles rely on human labor and are frequently time-consuming, inefficient, and subjective in judgment. These issues significantly affect the large-scale management of urban architectural styles. Fortunately, deep learning models have robust feature expression abilities for images and have achieved highly competitive results in object detection in recent years. They provide a new approach to supporting traditional architectural style recognition. Therefore, this paper summarizes 22 architectural styles in a study area which could be used to define and describe urban architectural styles in most Chinese urban areas. Then, this paper introduced a Faster-RCNN general framework of architectural style classification with a VGG-16 backbone network, which is the first machine learning approach to identifying architectural styles in Chinese cities. Finally, this paper introduces an approach to constructing an urban architectural style dataset by mapping the identified architectural style through continuous street view imagery and vector map data from a top-down building contour map. The experimental results show that the architectural style dataset created had a precision of 57.8%, a recall rate of 80.91%, and an F1 score of 0.634. This dataset can, to a certain extent, reflect the geographical distribution characteristics of a wide variety of urban architectural styles. The proposed approach could support urban design to improve a city's image. [ABSTRACT FROM AUTHOR]

As a hot research topic in urban geography, spatiotemporal interaction analysis has been used to detect the hotspot mobility patterns of crowds and urban structures based on the origin-destination (OD) flow data, which provide useful information for urban planning and traffic management applications. However, existing methods mainly focus on the detection of explicit spatial interaction patterns (such as spatial flow clusters) in OD flow data, with less attention to the discovery of underlying crowd travel demands. Therefore, this paper proposes a framework to discover the crowd travel demands by associating the dynamic spatiotemporal interaction patterns and the contextual semantic features of the geographical environment. With urban functional zones (UFZs) as the basic units of human mobility in urban spaces, this paper gives a case study in Wuhan, China, to detect and interpret the human mobility patterns based on the characteristics of spatiotemporal interaction between UFZs. Firstly, we build the spatiotemporal interaction matrix based on the OD flows of different UFZs and analyze the characteristics of the interaction matrix. Then, hotspot poles, defined as the local areas where people gather significantly, are extracted using the Gi-statistic-based spatial hotspot detection algorithm. Next, we develop a frequent interaction pattern mining method to detect the frequent interaction patterns of the hotspot poles. Finally, based on the detected frequent interaction patterns, we discover the travel demands of crowds with semantic features of corresponding urban functional zones. The characteristics of crowd travel distance and travel time are further discussed. Experiments with floating car data, road networks, and POIs in Wuhan were conducted, and results show that the underlying travel demands can be better discovered and interpreted by the proposed framework and methods in this paper. This study helps to understand the characteristics of human movement and can provide support for applications such as urban planning and facility optimization. [ABSTRACT FROM AUTHOR]

Examining medical supply–demand imbalances, as revealed through patients' cross-boundary treatment behaviors, is vital for reducing a metropolitan area's medical supply–demand gap and furthering sustainable development goals. This study, leveraging medical supply–demand and commuting data, scrutinizes medical imbalances in the Wuhan metropolitan area core. It includes a 'People-centered' theory for elucidating patients' treatment behaviors, proposes a method for constructing a regional medical supply–demand network, and explores the problem of supply–demand imbalance. The key findings include: (1) Wuhan's central area, despite its abundance of quality medical resources, fails to adequately cover the entire metropolitan area, indicating a need for broader resource distribution. (2) The Ezhou–Huangshi–Huanggang junction shows a stark contrast to Wuhan with its limited medical services and extensive hinterland connections. Future initiatives should aim to integrate resources dispersed from Wuhan, reducing regional disparities. (3) The city's periphery, influenced by resource distribution models and geographic distance, exhibits significant variance from central urban areas in medical supply–demand connectivity, particularly around Wuhan's eastern administrative boundaries. Future urban planning is needed to reinforce this area's role as a vital medical services conduit. (4) The distinguishing differences among the nine medical service communities in terms of resource recognition, service sharing, and patient mobility provide policy guidance for the allocation of medical resources. [ABSTRACT FROM AUTHOR]

Landscape patterns and building functions are successfully used to provide the social sensing information of urban areas. However, previous studies treated ground objects equally, ignoring their size differences. Considering the different contributions of various types of ground objects in land-use classification, this paper measured nine area-weighted mean landscape-level metrics to describe landscape patterns based on the land-cover map, derived from remote sensing images. Additionally, the same idea was applied for identifying building functions. Impervious surfaces, which occupy the majority of urban areas, have a decisive impact on land-use classes. In terms of this, this paper proposed the impervious surface area-weighted building-based indexes from the building outline data. To better represent the physical structure of urban areas, the entire study was based on the analysis units delineated by the OpenStreetMap road network. Finally, a random forest model combining the landscape-level metrics and building-based indexes was adopted in Wuchang District of Wuhan city, China. The results showed that the proposed method was effective at describing landscape patterns and identifying building functions for accurate urban land-use classification, increasing the precision by 10.67%. In general, the contribution of landscape-level metrics to the urban land-use classification is slightly greater than that of building-based indexes. Moreover, different land-use types of analysis units express different landscape patterns. It is of great significance for improving urban form and guiding future urban design. The paper demonstrates that area-weighted landscape metrics and building-based indexes offer a better understanding of urban land use, which plays a vital role in urban planning, construction, and management. [ABSTRACT FROM AUTHOR]

With the increase in urban development intensity, the urban climate has become an important factor affecting sustainable development. The role of urban ventilation corridors in improving urban climate has received widespread attention. Urban ventilation identification and planning based on morphological methods have been initially applied. Traditional morphological methods do not adequately consider the dynamic process of air flow, resulting in a rough evaluation of urban ventilation patterns. This study proposes a new urban-scale ventilation corridor identification method that integrates the Lattice Boltzmann method and the K-means algorithm. Taking Wuhan, China as the research area, an empirical study in different wind directions was conducted on a 20 m grid. The results showed that three levels of ventilation corridors ( 245.47   k m 2   in   total ) and two levels of ventilation obstruction areas ( 658.09   k m 2   in   total ) were identified to depict the ventilation pattern of Wuhan's central urban area. The method proposed in this study can meet the needs of urban-scale ventilation corridor identification in terms of spatial coverage, spatial distribution rate and dynamic analysis. Compared with the classic least cumulative ventilation cost method, the method proposed in this study can provide more morphologic details of the ventilation corridors. This plays a very important role in urban planning based on urban ventilation theory. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has spurred the resurgence of the informal street vending economy. This revival has boosted the market economy but has also challenged urban governance. Recognizing street vending deregulation as both a stimulus for employment and a potential challenge to hygiene and safety, this study evaluates the suitability of street vending within Wuchang District of Wuhan, China. The methodology unfolds in four steps: constructing an indicator system based on a policy and literature review, a spatial quantitative analysis via GIS, weight allocation through expert consultation and entropy methods, and the identification of suitable areas as well as strategies. Findings reveal suitability clusters centered around key urban nodes, extending across central and mid-western zones through corridors like Zhongnan Road, demonstrating the potential for centralized management and economic permeation into surrounding areas. The analysis of land-use compatibility showed that commercial, park, and residential lands offer the highest suitability for vending activities, proposing management strategies tailored to enhance business in commercial areas, flexible configurations in residential zones, diverse development in parks, quality-oriented development in public squares, and strict control in scenic and tourist facilities. This study not only deepens our understanding of the geographical distribution of and factors influencing street vending, but also proposes integrated management strategies for vending in urban public spaces, fostering vibrant, inclusive, and sustainable urban environments. [ABSTRACT FROM AUTHOR]

Urban form is an important factor affecting urban energy. However, the design of urban form and energy mostly belong to two separate disciplines and fields, and urban energy planning research rarely considers their mutual relationship. The available space intensity (ASI) of solar energy is formed on the basis of energy planning and urban design; the objective of this research is to evaluate the impact of urban form on the ASI of solar energy and to propose strategies for planning of the space that is available for solar energy so as to improve the efficiency of urban energy utilization and achieve sustainable urban development. Methodologically, this study firstly proposes a model to quantify the ASI of solar energy using three indicators: solar radiation intensity (SRI), solar installation intensity (SII), and solar generation intensity (SEGI). Then, we quantitatively calculate the solar ASI of nine types of typical urban blocks in a sub-center of Wuhan City, Nanhu. Correlation analysis and multiple linear regression analysis are then used to analyze the correlation between the form indicators and solar ASI, as well as the degree of influence. The results show that the differences in SRI, SII, and SEGI amongst the nine types of city blocks were as high as 114.61%, 162.50%, and 61.01%. The solar ASI was mainly affected by three form indicators: the building coverage ratio, the average building height, and the volume-to-area ratio. Reducing the building coverage ratio and increasing vertical development at the same time can effectively improve the ASI of solar energy. The results of this study and the established method provide an important reference and rapid calculation tool for urban energy planning and design, reducing the data and time usually required for solar analysis at the block scale. [ABSTRACT FROM AUTHOR]

With the rapid development of Chinese cities, the spatial pattern in historical districts has deteriorated due to a lack of protection measures. Indigenous communities have taken it upon themselves to expand certain spaces around the original residential buildings in order to meet the demands of modern life. However, this expansion has had a negative impact on the stylistic integrity of historical districts, leading to a conflict between cultural heritage and district protection. This study focuses on Tanhualin, a representative historical district in Wuhan. The study divides the district into 10 sub-areas, extracting a total of 4850 street views and selecting 6752 spontaneous spatial samples from them. Utilizing the Mask R-CNN model, the study uses computer-based deep learning to identify, summarize, and categorize the various forms and functions of these spontaneous spaces. The study also analyzes the negative impact of these spaces on the unity of the historical blocks' interfaces, as well as their positive impact on cultural heritage and the creation of a distinctive atmosphere. Finally, the study proposes reconstruction and renewal strategies from both urban design and architectural design perspectives. These strategies aim to improve the quality of life for indigenous communities, establish a sustainable system for preserving historical imprints, protect the cultural atmosphere of historical blocks, and enhance the adaptability of these blocks in modern cities. [ABSTRACT FROM AUTHOR]

The rapid evolution of cities has brought new challenges to urban planning and management. The accurate evaluation of urban functional structure and mixed use is critical, especially at a fine scale such as by blocks. The composition and mixing of urban spatial functions calculated by remote sensing and statistics are non-quantitative and undetailed. The text topic models are often applied to process text data, but are rarely used to mine semantic information in quantitative data. Therefore, this paper attempts to carry out research on the recognition of urban functions and mixed use using a text topic generation model based on resident mobile data. First, the area within Wuhan Third Ring Road was divided into 2451 units at a grid size of 500 m × 500 m. The histogram-latent Dirichlet allocation (H-LDA) and information entropy were applied to assign different grid units to correct the functional topics and topic information entropy (TIE). Second, the functional categories of different analysis units were calculated using the point of interest (POI), frequency density (FD) and category proportion (CP) indicators, while the functional information entropy (FIE) based on the POI was calculated. Then, the urban functions and mixtures identified by the two kinds of data were compared and analyzed. Finally, referring to the geographic information in streetscape map and applying correlation analysis, the function and mixing results obtained from the experiment were verified. Studies have shown that the H-LDA model can identify bridges, which the POI data have shown is challenging to identify without attributes such as length. The function recognition accuracy of the H-LDA model is 89.3%, which is higher than K-means algorithm and Word2vec models. The correlation coefficient between FIE and TIE is 0.587, indicating that both are highly correlated. These explain the accuracy and rationality of identifying city functions and mixtures based on the H-LDA model. The H-LDA model can be applied to functional computing and fine-scale urban mixed function planning. [ABSTRACT FROM AUTHOR]

A quantitative analysis of rural development is required to comprehend the spatial differentiation of a rural area and promote rural sustainable development under the pressure of urbanization and industrialization, especially areas with dramatic changes in rural socioeconomic development of China and other developing countries. Taking Wuhan as the case study, this paper developed an index system including rural settlement, land, industry and human settlement environment for evaluating the level of rural development. Then, using the exploratory spatial data analysis, the principal component analysis and the cluster analysis, this paper analyzes the spatial differentiation and correlation and categorizes the types of rural development. The results are as follows. (1) The spatial differentiation of the level of rural development in Wuhan City's new urban districts is obvious and the areas with a high level of rural development are mainly distributed at the intersection of the new and central urban areas and gradually decrease outward. (2) There is a significant spatial agglomeration of the developed rural areas and the structure of the spatial change in these areas resembles a certain continuity, specifically a circle of "central heat surrounding cold". (3) Rural development in the new urban areas can be divided into the following five types: the ecological leisure type, the traditional farming type, the balanced development type, the industrial-and-agricultural mixed type and the industrial promotion type. The corresponding development path is proposed in combination with different types of rural development to provide a theoretical basis and decision-making reference for rural revitalization. [ABSTRACT FROM AUTHOR]

The human spatial perception of urban streets has a high complexity and traditional research methods often focus on access surveys of human perception. Urban streets serve as both a direct conduit for pedestrians' impressions of a city and a reflection of the spatial quality of that city. Street-view images can provide a large amount of primary data for the image semantic segmentation technique. Deep learning techniques were used in this study to collect the boring, beautiful, depressing, lively, safe, and wealthy perception scores of street spaces based on these images. Then, the spatial pattern of urban street-space quality perception was analyzed by global Moran's I and GIS hotspot analyses. The findings demonstrate that various urban facilities affect street quality perception in different ways and that the strength of an influencing factor's influence varies depending on its geographical location. The results of the influencing factors reveal the difference in the degree of influence of positive and negative influencing factors on various perceptions of the visual dimension of pedestrians. The primary contribution of this study is that it reduces the potential bias of a single data source by using multi-dimensional impact analysis to explain the relationship between urban street perception and urban facilities and visual elements. The study's findings offer direction for high-quality urban development as well as advice for urban planning and enhanced design. [ABSTRACT FROM AUTHOR]

Urban spatial elements present agglomeration and dispersion geographic processes in the urban development. Identifying the characteristics of their distribution changes and accurately capturing the evolution of the urban spatial structure is of great significance to urban construction and management. This study takes Wuhan as a case study and focuses on the spatial agglomeration distribution of urban elements. Point of Interest (POI) data from 2017 to 2021 were collected, and the Block2Vec model was employed to extract the comprehensive geographic information from various elements within the traffic analysis zones (TAZs). Subsequently, identification and division were carried out to access the level of urban spatial element agglomeration. Finally, the spatial–temporal evolution characteristics of urban aggregated elements in the Wuhan metropolitan development area over five years were compared and analyzed. The results indicate the following: (1) urban elements present an obvious circle structure in their spatial agglomeration, with distinct differences observed among different element types; (2) from 2017 to 2021, the Wuhan urban development zone experienced obvious expansion in urban space; (3) increased agglomeration of spatial elements mainly occurred in the surrounding areas of the city, while some areas in the city center displayed weaker element agglomeration and a reduction in various service facilities. The results demonstrate that the method used in this study could effectively identify the spatial agglomeration distribution of urban elements, as well as accurately distinguishing regions with distinct development characteristics. This approach could provide robust support for optimizing land use and urban spatial planning. [ABSTRACT FROM AUTHOR]

Rapid urbanization development and construction has seriously threatened the connectivity of habitat patches in cities and hindered the construction of ecological networks in highly urbanized areas. Among them, China is affected by early compressed urbanization, and the broken ecological space in cities and towns has attracted the extensive interest of researchers. To avoid the subjective randomness and single analysis of ecological space in urbanization areas, this paper takes the central urban area of Wuhan as the main research area. It comprehensively evaluates the ecological network space by combining the MSPA-MCR model. The main conclusions are as follows: (1) Identifying the ecological landscape types with important ecological significance in the study area: Core (88.29%), Islet (0.25%), Perf (0.63%), Edge (9.74%), Loop (0.22%), and Bridge (0.14%). Through the dPC landscape index, seven important ecological sources south of the middle reaches of the Yangtze River were identified. (2) According to the comprehensive factors of natural and human factors constructed by the MCR model, the minimum cumulative ecological resistance surface was established, with an average value of 2.65, a maximum value of 4.70, and a minimum value of 1.00, showing a trend that the ecological resistance values in the central and eastern parts are lower than those in the western part. (3) According to the standard deviation ellipse, the distribution direction of NE–SW in ecological sources was analyzed. The ecological sources distributed in the north were less, and the spatial distribution was scattered on the whole. The strong global positive correlation and local spatial aggregation characteristics of ecological resistance surface were evaluated according to spatial autocorrelation. Based on the gravity model, the interaction intensity of ecological corridors between source areas was evaluated, and the importance of ecological corridor protection and restoration was quantitatively analyzed. The research results provide scientific and reasonable references and a basis for ecological planning of Wuhan central city. [ABSTRACT FROM AUTHOR]

Within the scope of ecological development planning in China, afforestation is highly valued. However, the scientific planning of afforestation still has inadequacies. There are few studies on the spatial distribution of urban forests targeted at air quality improvement. Here, we implemented a virtual experiment to evaluate whether different tree planting distribution plans with the same afforestation scale would have a significant effect on fine particulate matter (PM2.5) removal. As a case study of Wuhan, this paper identified the statistical regularity between PM2.5 concentration and adsorption of representative trees through field sampling and measurement, simulated the influence of different afforestation plans on PM2.5 concentration based on Geographic Information System (GIS), judged the significance of the difference of the plans, and proposed a greening distribution strategy. The results show that different forest layouts had no significant impact on PM2.5 in the administrative region, and the concentration reduction rate was only 1–2%. Targeted planting of trees in heavily polluted areas in the city center would have achieved better air quality improvement, with a reduction rate of 3–5%. In Wuhan construction areas, trees should be planted to increase the forest coverage rate to 30%. The edge of the urban metropolitan development zone needs to be strengthened with trees to form a forest belt 10 km–20 km wide, with a forest coverage rate of at least 60%. In general, the capability of trees to reduce PM2.5 concentration is weak. The fundamental way to improve air quality is to reduce emissions; planting trees is only an auxiliary measure. More ecological forest functions should be considered in city-wide afforestation distribution. [ABSTRACT FROM AUTHOR]

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran's I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran's I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran's I and GWR models for land subsidence and urbanization indicators, a "best" spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning. [ABSTRACT FROM AUTHOR]

Urban sprawl in China presents unique characteristics that differ from those commonly studied in Western contexts, an aspect not fully explored in previous studies. Therefore, taking Wuhan, Hubei as an example and integrating population data, remote sensing data, and POI data, this research offers a perspective on sprawl development in urban China. By incorporating population, urban land use, and urban amenities, this study measures their dynamics to classify urban spaces and employs spatial regression models to identify the characteristics of sprawl development with spatial effects controlled. It further applies geographically weighted regression to examine the underlying spatial heterogeneity. The findings indicate that population growth and urban land expansion do not align perfectly, and further exploration identifies the various trends of sprawl development in urban core and periphery areas. On the other hand, some suburban areas show compact development trends, but the growth of local amenities may be limited due to the historical sprawl development legacies. Regression results reveal specific characteristics of this sprawl development. Key findings include the following: (1) shaped by the triple process of sprawl development of urban renewal, suburbanization, and rural revitalization, Wuhan shows a significant core-periphery structure with the trend of polycentricity; (2) overcrowding in central urban districts is the primary driver of sprawl development; (3) most traditional suburbs in Wuhan have emerged as a consequence of rapid urbanization with a legacy of sprawl development; (4) spatial heterogeneity across urban spaces highlights the necessity for locally tailored approaches to regulating sprawl development. [ABSTRACT FROM AUTHOR]

Heterogeneous land development opportunities induced by spatial regulation produce different advantages in areas, which undoubtedly differentiates farmers' employment. The aim of this study was to quantitatively examine its impact. We selected Moshui Lake City Park (urban development planning area), Sino-French Eco-City (industrial development planning area), and Chenhu International Wetland (ecological protection planning area) as its principal research areas. These regions are all located in Wuhan city, Hubei province, China. After obtaining 907 valid responses from rural households, the Tobit model was adopted to identify the impact of land development opportunities on farmers' nonfarm employment. The results show that, first, industrial development opportunity (IDO) and urban development opportunity (UDO) provide more job security than the reference group, which is ecological development opportunity (EDO), with the estimated coefficients of IDO and UDO being 0.325 and 0.944, respectively. However, a negative correlation was found between UDO and farmers' employment selection and income. Second, heterogeneity analysis reveals that the promotion effect of land development opportunities on farmers' employment is more significant for low- and middle-income, low-quantity, and high-quality households. Finally, further analysis shows that IDO can promote employment for all age groups, but UDO inhibits the elderly labor force from getting employed. These findings provide evidence-based insights which can enable the government to formulate land value-added distribution systems that promote balanced development between regions and stakeholders. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to drastic land-use/cover changes (LUCCs) and urban heat islands (UHIs), negatively altering the urban climate and air quality. LUCC's significant impacts on human health and energy consumption have inspired researchers to develop nature-based solutions to mitigate UHIs and improve air quality. However, integrating GIS-CFD modeling for urban heat mitigation towards climate change adaptation was largely neglected for eco-sustainable urban design in rapidly urbanizing areas. In this study, (1) long-term LUCC and meteorological analysis were conducted in the Wuhan metropolitan area from 1980 to 2016; (2) to mitigate the adverse effects of LUCC under a speedy development process, the role and relevance of optimizing building morphology and urban block configuration were discussed; (3) and particular design attention in strategy towards climate change adaptation for environmental performance improvement was paid in Wuhan's fast-growing zones. The results show that UHII in 1980 was less severe than in 2016. Air temperature (Ta) increased by 0.4 °C on average per decade in developing areas. This increases the severity of UHII in urban fringes. It is found obligatory for a nature-based design to adopt urban morphology indicators (UMIs) such as average building height (μBH), sky view factors (ψSVF), and building density (BD/λp = % of built area) towards these changes. Further, on-site measurement revealed that λp is the most effective indicator for increasing urban heat around the buildings and boosting UHII. Using UMIs and a combined three-in-one regulation strategy based on μBH of common building types of high-rise (BHA), mid-rise (BHB), and low-rise (BHC) buildings can effectively contribute to regulating Ta and air movement within block configuration. As a result of this study's strategy, urban heat is mitigated via reinforcing wind in order to adapt to climate change, which impacts the quality of life directly in developing areas. [ABSTRACT FROM AUTHOR]

Urban "blue-green" space is the basic element of urban natural ecological space. The rapid urbanization process has a significant impact on the pattern of urban blue-green space and seriously threatens the urban ecological environment. It is of great significance for urban ecological protection and sustainable development to study the change in characteristics of blue and green space during urban expansion. In this paper, a comprehensive method of remote sensing image, landscape pattern analysis, sector analysis, and coupling analysis is applied to analyze the spatio-temporal evolution characteristics and coordinated development level of the blue-green space and built-up area in central Wuhan from 1987 to 2018. The results showed that the land use and landscape pattern in the central city of Wuhan underwent a drastic change process, and the dominant change was the occupation of blue-green space by urban built-up areas, which led to the increase of landscape fragmentation and the decrease of heterogeneity. Urban green space is gradually marginalized and concentrated in local areas. The blue space has an obvious blocking effect on the expansion of the built-up area, and its spatial pattern tends to be stable gradually. In addition, the coupling degree between urban blue-green space and urban built area presents an inverted U-shape, and the coordinated development level among the three has entered a stage of moderate imbalance. It is urgent to strengthen the protection of blue-green space, curb the disorderly expansion of cities, and improve the quality of urban development. [ABSTRACT FROM AUTHOR]

Accessibility is the ease of reaching opportunities (goods, services, activities, and destinations). Accessibility of desirable locations such as households and commercial locations, is typically scaffolded by land use patterns and transportation infrastructure. It can reflect people's travel convenience, cities' viability, sustainability, and mitigate the negative effects on the environment and public safety. Consequently, it is recognized as a fundamental principle in urban sustainable development policies worldwide. In the literature, most of the studies have used a static or partially dynamic approach with a single mode such as a car or public transportation by using conventional models. These "static" models assume that household locations are static and that transportation supply and opportunities for social practice activities are fixed in time and space, which can lead to biased or even misleading assumptions in accessibility models. Therefore, the aim of this study is to evaluate the impact of dynamic spatial accessibility through Mode-Dependent Accessibility (MDA) on the location choice behaviors of urban activities such as households and commercialin the City of Wuhan, China. This study employed the Mode-Dependent Travel Demand Model (M-TDM) to measure the impact of short-term MDA on household and commercial activities for the years 2012 and 2015. Additionally, an integrated spatial economic (ISE) model such as PECAS (Production, Exchange, Consumption, Allocation, System) in order to investigate location preferences of urban activities over space and time. Regarding household and commercial location choice, the ISE modeling results revealed that households and commercial activities are sensitive to MDA, especially using transit. The ISE method predicted that the R2 for household and commercial location choice models was 0.84 to 0.90 for transit-based accessibility, whereas the R2 for logsum-based static models was 0.48 to 0.72. In addition, their findings suggest that highly accessible locations that are well served by auto are more appealing for household and commercial activities. The findings of this study will help urban planners, transportation planners, and policymakers take into account the dynamic nature of short-term MDA when zoning and allocating urban activities and public amenities, instead of using static accessibility. [ABSTRACT FROM AUTHOR]

To alleviate the urban heat island effect and reduce the consumption of electricity and expenditure caused by active cooling devices on hot days, many cities in tropical and subtropical areas emphasize the utilization of urban greening areas in current and future urban planning. We utilized the weather research and forecasting model (WRF) to simulate and study the impact of different greening area rates on the urban microclimate in business, residential, and industrial areas in Wuhan city. Meanwhile, we proposed two efficiency coefficients to evaluate the variable cooling benefit of the improvement of the greening area. The results show that greening areas and water bodies are the cooling sources of cities and that industrial areas benefit the most from improvements in the greening rate, with the average temperature declining by 1.06 °C with a 20% increase in the greening rate, while the corresponding values of residential and industrial areas were 0.98 °C and 0.92 °C, respectively. This research provides a reference for the future planning of tropical and subtropical areas to help improve the urban microclimate, thermal environment, and environmental comfort on hot days. [ABSTRACT FROM AUTHOR]

Urban green space (UGS) provides a wide range of ecosystem services for human beings. The fairness of UGS distribution has important implications for sustainable urban development and human well-being. However, many current studies on green space fairness are limited to within specific cities, and UGS fairness in rapidly developing metropolitan areas is still largely neglected. This study quantifies the change in green space fairness in the Wuhan metropolitan area from 2000 to 2020 based on a long time series of land cover and population spatial distribution products. We incorporated green space types and population distribution into the fairness evaluation framework, quantified the value of green space ecosystem services available to people through nested buffers, and analyzed the spatial and temporal variation of green space fairness in the study area based on the Gini coefficient of each city. The results show that the supply of green space services in most cities has shown a trend of "decreasing and then increasing" in the past 20 years. The fairness of green space in three cities has shown an improving trend, and the Gini coefficient in four cities is still above 0.50 in 2020. Based on the current green space and related indicators in each city, we propose future greening policies for each city. The methodology and conclusions of this study will help improve future green space planning recommendations in metropolitan areas and urban agglomerations, thus promoting regional public infrastructure coproduction and sharing. [ABSTRACT FROM AUTHOR]

The benefits of the natural environment in urban space have been explored in numerous studies. However, only a few statistics and studies have been conducted on the correlation between emotion and urban waterfront space, especially considering gender differences. Taking Wuhan city as an example, this study puts forward a new approach and perspective. Text emotion analysis is combined with the spatial analysis technique based on big data of social media. Based on the emotions of the public of different genders in urban space, suggestions are provided for urban planning and development from the perspective of POI (Point of Interest). The main steps are: (1) Analyzing the emotional score of Weibo texts published by citizens in the waterfront area of 21 lakes in Wuhan City; (2) exploring the public emotion characteristics of different genders in the urban waterfront; (3) classifying the waterfront according to the emotional response (score) of the public of different genders; (4) exploring the relationship between different POI types and waterfront types and proposing planning suggestions. The results of this study provide evidence for gender differences and spatial distribution of public emotions in the Wuhan waterfront area. It can help decision-makers to judge the prior protection and development direction of waterfront space, thus demonstrating the feasibility of this approach. [ABSTRACT FROM AUTHOR]

The commute of residents in a big city often brings tidal traffic pressure or congestions. Understanding the causes behind this phenomenon is of great significance for urban space optimization. Various spatial big data make the fine description of urban residents' travel behaviors possible, and bring new approaches to related studies. The present study focuses on two aspects: one is to obtain relatively accurate features of commuting behaviors by using mobile phone data, and the other is to simulate commuting behaviors of residents through the agent-based model and inducing backward the causes of congestion. Taking the Baishazhou area of Wuhan, a local area of a mega city in China, as a case study, we simulated the travel behaviors of commuters: the spatial context of the model is set up using the existing urban road network and by dividing the area into space units. Then, using the mobile phone call detail records of a month, statistics of residents' travel during the four time slots in working day mornings are acquired and then used to generate the Origin-Destination matrix of travels at different time slots, and the data are imported into the model for simulation. Under the preset rules of congestion, the agent-based model can effectively simulate the traffic conditions of each traffic intersection, and can induce backward the causes of traffic congestion using the simulation results and the Origin-Destination matrix. Finally, the model is used for the evaluation of road network optimization, which shows evident effects of the optimizing measures adopted in relieving congestion, and thus also proves the value of this method in urban studies. [ABSTRACT FROM AUTHOR]