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Transit-oriented development (TOD) is a crucial way to achieve compact, livable, and sustainable urban development. The integration of shared bikes and rail transit significantly expands the service scope of public transportation and promotes the implementation of TOD planning strategies. Based on TOD planning concepts, this paper identifies the transfer flow patterns of shared bikes. Considering the semantic functions of metro stations, an interpretable machine learning model is used to explore the tidal flow patterns of shared bikes and their nonlinear correlations with the built environment in the main urban area of Wuhan. The conclusions are as follows. (1) Based on the tidal balance index of shared bikes during morning and evening peak periods, two types of tidal flow patterns are identified in the main urban area of Wuhan, namely "convergence in the morning and divergence in the evening" and "divergence in the morning and convergence in the evening". The "convergence in the morning and divergence in the evening" tidal pattern mainly occurs in residential areas at a moderate distance from the urban center and employment areas on the edge of the Hankou central activity zone, while the "divergence in the morning and convergence in the evening" tidal pattern mainly occurs in employment-dense areas near the Second Ring Road. (2) Four types of semantic functional themes and two mixed functional clusters of metro stations are identified through POI semantic information modeling and hierarchical clustering. The semantic functional types of metro stations are strongly correlated with the flow patterns of shared bikes. (3) The nonlinear effects of built environment factors are significant. The moderate supporting living facilities and road density, and the large residential scale can effectively promote the occurrence of stable connection pattern of shared bikes with high riding flow. This study can provide a basis for alleviating the tidal flow problem of shared bikes from the aspects of optimizing shared bikes scheduling and adjusting the urban built environment. [ABSTRACT FROM AUTHOR]

The dockless bike-sharing system has rapidly expanded worldwide and has been widely used as an intermodal transport to connect with public transportation. However, higher flexibility may cause an imbalance between supply and demand during daily operation, especially around the metro stations. A stable and efficient rebalancing model requires spatio-temporal usage patterns as fundamental inputs. Therefore, understanding the spatio-temporal patterns and correlates is important for optimizing and rescheduling bike-sharing systems. This study proposed a dynamic time warping distance-based two-dimensional clustering method to quantify spatio-temporal patterns of dockless shared bikes in Wuhan and further applied the multiclass explainable boosting machine to explore the main related factors of these patterns. The results found six patterns on weekdays and four patterns on weekends. Three patterns show the imbalance of arrival and departure flow in the morning and evening peak hours, while these phenomena become less intensive on weekends. Road density, living service facility density and residential density are the top influencing factors on both weekdays and weekends, which means that the comprehensive impact of built-up environment attraction, facility suitability and riding demand leads to the different usage patterns. The nonlinear influence universally exists, and the probability of a certain pattern varies in different value ranges of variables. When the densities of living facilities and roads are moderate and the relationship between job and housing is relatively balanced, it can effectively promote the balanced usage of dockless shared bikes while maintaining high riding flow. The spatio-temporal patterns can identify the associated problems such as imbalance or lack of users, which could be mitigated by corresponding solutions. The relative importance and nonlinear effects help planners prioritize strategies and identify effective ranges on different patterns to promote the usage and efficiency of the bike-sharing system. [ABSTRACT FROM AUTHOR]

Urban Green Spaces (UGSs) can provide social and ecological benefits, and the coordination of these two functions will largely advance human-nature harmony in cities. As such, we proposed a comprehensive framework to evaluate UGSs multifunctionality, i.e. the coupling coordination relationship of ecological connectivity and spatial accessibility of UGSs. Wuhan City in Central China was taken as a case study, and multiple ecosystem service values of green space patches and the disordered use of UGSs multifunctionality were explored. The results demonstrated low-level coupling coordination of UGSs multifunctionality in Wuhan. More than 70% of UGSs were imbalanced, 27.91% of which featured small sizes, low connectivity and accessibility. We suggest that planners should optimize UGSs arrangement to improve species reachability, especially for species with dispersal distance less than 4 km, and to create 15-minute community life circles for residents at the same time. Our findings are expected to support the promotion of UGSs multifunctionality and the balance of urban development and habitat conservation. [ABSTRACT FROM AUTHOR]

Robustness is the key for strategies to protect ecological network (ENs) against external threats. In this study, we proposed a research framework for robustness testing of EN protection strategies. First, we constructed the ENs of Wuhan Metropolitan Area (WHM) based on the advantages of circuit theory in landscape ecology. We then extended complex network theory to the migration application of ENs. Five protection strategies of ENs were antagonistically combined with multiple attack modes to implement multi‐scenario simulations of attacks on ENs. The robustness parameters of the complex network were applied to measure the effectiveness of EN protection strategies under different attack efficiencies. The results showed that identifying the key performance of ENs makes hierarchical protection of ENs possible. Therefore, when focusing on maintaining the transmission efficiency and global connectivity, or preventing fragmentation of ENs in WHM, we recommend protecting the main trunks of ENs. When focusing on maintaining the backbone connectivity of ENs in WHM, we recommend protecting the main‐secondary trunks of ENs. We argue that specific protection strategies and directions can be determined according to the objectives of ecological construction and the scheme we put forward. [ABSTRACT FROM AUTHOR]

Construction and protection of ecological networks (ENs) is considered to be an effective means to curb habitat fragmentation and strengthen landscape connectivity. In this study, a complete evaluation framework of ENs based on "quality–function–structure" was proposed to support the formulation of protection strategies for ENs. First, we built the ENs of Wuhan urban agglomeration (WUA) from 2000 to 2020 based on the advantages of circuit theory and remote sensing data of land use monitoring. The results showed that land development activities are an important driving force for the temporal and spatial evolution of global ENs. Forest fragmentation, transitional urban expansion, and agricultural reclamation were important inducements for the shrinkage of ecological sources. They may also increase the resistance of species migration, which will lead to qualitative change and even fracture of ecological corridors. Second, circuit theory, centrality index, and complex network theory were applied to evaluate the quality defects, functional connectivity, and topology characteristics of ENs in WUA, respectively, from 2000 to 2020. The results showed that the antagonism between ecological corridors and land development activities led to ecological quality defects (ecological barriers and pinchpoints). Different land development models had differential effects on centrality indexes. Moreover, the main trunk in the northern Dabie Mountains and the southern Mufu mountains was developed, while the secondary trunks were abundant in the middle of WUA. Finally, we proposed protection strategies for ENs based on the coupling of the "quality–function–structure" of WUA in 2020. It is suggested that all ecological sources must be included in nature reserves to prevent natural or manmade erosion. The key areas to be repaired were determined through the quality evaluation of ecological corridors. The priority of construction and protection of ecological corridors was determined by coupling two topological structures and functions. We argue that specific protection strategies and directions can be determined according to the construction objectives of local ENs. [ABSTRACT FROM AUTHOR]

Many ecologists have demonstrated that building ecological networks (ENs) can resist habitat fragmentation. However, existing studies have not yet explored the directionality of ENs. In this study, we proposed a research framework for the construction and structural evaluation of directed ENs from the perspective of dynamic biological flows. The framework reveals the operational essence of ENs, which is that dynamic biological flows rely on static carriers for directed movement. Thus, this framework overcomes the shortcomings of previous studies that only focused on static carriers and ignored dynamic biological flows. In other words, this study will guide the research of ENs from undirected to directed. The specific research and innovations are as follows. (1) First, the MaxEnt model and InVEST model were combined to evaluate habitat suitability in Wuhan Metropolitan Area (WHM), and 180 species habitats were identified accordingly. A total of 366 potential species migration corridors were extracted based on the identified species habitats and ecological resistance surfaces. (2) Second, we constructed a new relationship function between dynamic biological flows and potential biological flows, species dispersal probability, and species dispersal attraction. The results indicate that dynamic biological flows can serve as the measurement of directionality for directed ENs, and their density and intensity exhibit significant spatial heterogeneity. (3) Finally, we introduced the Chu-Liu/Edmonds' algorithm for complex network analysis to reveal the tree-like structure of directed ENs. The results show that the backbone and branches of directed ENs in WHM are species migration pathways with maximum dynamic biological flows linking global and local habitats, respectively. Meanwhile, the implementation of hierarchical protection according to the tree-like structure of directed ENs can significantly enhance its robustness. [Display omitted] • A conceptual framework of directed ecological networks (ENs) was developed. • MaxEnt and InVEST model were combined to identify species habitats. • Directed ENs was constructed from the perspective of dynamic biological flows. • Chu-Liu/Edmonds' algorithm was applied to reveal the tree-like structure of directed ENs. • Protection priority of ENs was determined based on the structural evaluation. [ABSTRACT FROM AUTHOR]

The correct urban building layout is an important influencing factor in urban ventilation, and the heat island effect has become an important factor affecting the quality of urban life. Optimization of the urban building layout can play a role in mitigating the heat island effect. The traditional ventilation corridor analysis method, based on a least-cost path analysis, can only generate a few main ventilation corridors. It is difficult to obtain global ventilation results covering the whole study area using this method of analysis. On the basis of urban morphology and a least-cost path analysis, this study proposes a "least cumulative ventilation cost" method for analyzing urban ventilation. Taking Wuhan downtown as a research area, the urban ventilation environment under different wind directions and seasons was analyzed. This method can effectively express the ventilation conditions throughout the whole study area and can simultaneously express the quality of the generated corridors effectively. The results show that Wuhan has three levels of ventilation corridor. Moreover, the ventilation conditions in Wuchang (Wuchang, Qingshan, and Hongshan) are better than those in Hankou (Qiaokou, Jianghan, and Jiang'an). [ABSTRACT FROM AUTHOR]

Ecologists and policymakers strive to develop and optimize ecological networks (ENs) to prevent landscape fragmentation. However, the role of the cluster structure for ENs is often overlooked. In this study, we established a cluster management mode of ENs in Wuhan Metropolis (WHM), with a focus on dividing ENs based on identified clusters and implementing differentiated optimization, protection, and strengthening measures. First, we developed an optimization method to solve the defects of layout (connectivity blind areas) and quality (barriers and pinch points) for the initially constructed ENs. The results showed that the connectivity blind areas of ENs were significantly shrunk after layout optimization. Meanwhile, ENs after quality optimization avoided rugged, redundant or obstructive corridors, while narrow corridors were also given priority protection. Second, the Infomap algorithm was applied to identify 33 clusters of optimized ENs in WHM. Finally, we evaluated EN clusters to provide guidance and bases for the cluster management mode of ENs. The results indicated that centrality indicators can be applied to evaluate the protection importance for ecological edges within clusters, and connectivity indicators can be used to evaluate the protection importance and strengthening potential for ecological edges between clusters. We assert that incorporating the cluster management mode of ENs into future ecological protection plans is essential for maintaining ecological integrity and connectivity. • A cluster management mode for ecological networks (ENs) was developed. • An optimization method was developed to solve defects for initial ENs. • The Infomap algorithm was applied to identify the cluster structure of ENs. • The protected and strengthened components between and within clusters were identified. [ABSTRACT FROM AUTHOR]

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining (GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%-70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors. [ABSTRACT FROM AUTHOR]

Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly. [ABSTRACT FROM AUTHOR]

Accurate modeling of urban growth is an extremely important component of urban geographic studies and is also vital for future urban planning. The trajectories of urban growth can be monitored and modeled by the use of geographic information system techniques, remote sensing data, and statistical analysis. In this study, we couple game theory with an integrated agent-cellular method to develop a model of the major determinants controlling urban development, which not only accounts for socioeconomic driving forces but also captures human actions. Wuhan, the largest city in central China, is undergoing rapid urbanization and is facing uncontrolled urban expansion. The city proper region of Wuhan is selected as the case study area to simulate urban growth during the period between 2003 and 2023. The results indicate that the social conflicts between the different stakeholders in urban development can be identified by utilizing a game tree. The game-theory based agent-cellular model is shown to be more effective than a pure cellular automata model in urban growth simulation. The results also show that, from 2013 to 2023, the urban area of the Wuhan city proper region is predicted to grow to 442.77 km 2 , which is almost two times the area in 2003. This research is the first study to use empirical data and game theory to analyze the decision-making process in urban development in the Wuhan area. [ABSTRACT FROM AUTHOR]

China has witnessed rapid urban growth over the past two decades, which has resulted in vast ecological and environmental issues, both in urban and peri-urban areas. It is therefore extremely important to explore the driving factors, and thus gain an insight into the process of urban growth, to be able to provide help for urban planning and policy making. This paper examines the features and spatial determinants of urban growth in the Wuhan urban agglomeration (WUA) from 1988 to 2011. Four landscape metrics (patch density, landscape shape index, aggregation index, and total area) were selected to characterize the urban landscape features at two scales (5 km and 10 km grid sizes). Spatial regression models were then used to explore the relationships between urban landscape change and its spatial determinants. The results showed that the urban area of the WUA increased from 4.19 × 104 ha in 1988 to 49.29 × 104 ha in 2011, with an annual growth rate of 46.75% over the past two decades. The WUA landscape has also become more fragmented and irregular. Spatial autocorrelations were common in the urban growth changes at the two different scales. Both physical and proximity factors have significantly influenced the urban landscape changes, and they have varied with time and scale. Among these variables, all the levels of road network have had a considerable effect on the shape and density changes of the urban landscape, while distance to railway and highway did not show obvious effects on the total area change of the urban growth. In addition, city center has had an increasing effect on patch density, and a decreasing impact on the total area of the urban landscape. The different land-use policies should be compromised and reconciled so that the objectives of promoting socioeconomic development and farmland protection can be balanced. These results could help us to better understand the process of urban growth, and thus have important implications for urban management and policy making in metropolitan areas in developing countries. [ABSTRACT FROM AUTHOR]

Dual clustering performs object clustering in both spatial and non-spatial domains that cannot be dealt with well by traditional clustering methods. However, recent dual clustering research has often omitted spatial outliers, subjectively determined the weights of hybrid distance measures, and produced diverse clustering results. In this study, we first redefined the dual clustering problem and related concepts to highlight the clustering criteria. We then presented a self-organizing dual clustering algorithm (SDC) based on the self-organizing feature map and certain spatial analysis operations, including the Voronoi diagram and polygon aggregation and amalgamation. The algorithm employs a hybrid distance measure that combines geometric distance and non-spatial similarity, while the clustering spectrum analysis helps to determine the weight of non-spatial similarity in the measure. A case study was conducted on a spatial database of urban land price samples in Wuhan, China. SDC detected spatial outliers and clustered the points into spatially connective and attributively homogenous sub-groups. In particular, SDC revealed zonal areas that describe the actual distribution of land prices but were not demonstrated by other methods. SDC reduced the subjectivity in dual clustering. [ABSTRACT FROM AUTHOR]

Abstract: Economic valuation of the amenities of urban open spaces will lend support to urban planning and development. In the absence of an explicit market for these amenities, the hedonic approach is often employed. Hitherto there have been a relatively limited number of studies on hedonic valuation of urban open spaces in China. This paper employs Geographic Field Model (GFM) to specify the externalities of urban open spaces with regard to their specific scale of influence, and builds a GFM-based spatial hedonic model to value the environmental amenities. The GFM quantification of open space variables overcomes the potential bias caused by traditional distance measures without influence scale limitations and the discontinuousness of the dichotomous index indicating the proximity to open space. A GFM-based spatial hedonic analysis was conducted in Wuhan, a metropolis in central China with various open spaces. Proximity to the Changjiang River recreation space and the East Lake were found to exert remarkable and positive impacts on apartment price. But proximity to other lakes and rivers were not significant in the result. The study showed that city level parks have significant amenity values, but district level parks do not. The amenity values of these urban open spaces were demonstrated by measuring the value they added to apartment prices. Some unexpected findings, such as the positive effect of noise and the powerful impact of floor height on housing price, may be common rules in densely populated cities in China. [ABSTRACT FROM AUTHOR]

Green infrastructure (GI) has become an important tool to achieve sustainability and resilience in cities because of its various benefits, including stormwater management, urban heat island mitigation, air quality improvement, and carbon storage. Most existing studies have often focused on a single aspect, while few studies have incorporated the results of GI analysis into the planning process. To address this gap, we propose a planning framework to prepare the GI intervention solutions, aimed at identifying the priority actions, hubs to extract maximum multifunctionality, and preference types at the regional scale. We applied the planning framework to Wuhan city as a case study, and found an overall significant multifunctional potential. Two-thirds of the benefit pair (including spatial autocorrelation and bivariate spatial autocorrelation for benefits) relationships were found to be positive, and block areas approximately 15% of the total area were recommended as hubs to lay out the GI. Warnings should be received for evidence, revealing that industrial areas have higher requirements for GI that can alleviate the thermal environment and improve air quality. Strong positive correlations between various benefits were found in this area, especially based on a relatively large proportion of existing natural land. Further, we classified the types of GI preference by SOM (Self-organizing map neural network), and found that differentiated GI planning and strategy formulation are required by different types of regions. The planning framework provides intuitive guidance for GI intervention solution making, which can provide planners and government officials a deeper understanding of GI discourse based on clearly explained answers of important decision-making questions. • A macro spatial planning framework of green infrastructure is constructed and applied to Wuhan. • Spatial relationships are considered to place green infrastructure for maximum multifunctionality. • The results revealed high correlations between land use types and demand types for GI benefits. • The objectives in the planning process are clearly stated and methods are flexible to be duplicated in other spatial context. [ABSTRACT FROM AUTHOR]

• A diagnostic framework for degradation risks of ecosystem services was developed. • The differentiated risk sources and multiple risk receptors were identified. • The intensity index for degradation risks of ecosystem services was developed. • The regulatory factors were identified via a multiscale-GWR (MGWR) model. • The degradation risks can be reduced by optimizing the land development pattern. Diagnosing degradation risks of ecosystem services (ESs) is a cornerstone for achieving sustainable development of the ecosystem and promote human well-being. In this study, we constructed and applied a diagnostic framework for degradation risks of ecosystem services (ESDRs) in Wuhan City, China. First, the risk receptors and risk sources were spatially overlaid to identify and measure the ESDRs. Second, a multiscale geographically weighted regression (MGWR) model was applied to identify land development factors that could be used to regulate ESDRs. Finally, the high value areas of ESDRs were clustered and the regression results were used to propose regulatory measures for each clustered zone. Our study showed that the uncontrolled expansion of construction land in Wuhan might weaken the functions of water retention, habitat maintenance and carbon sequestration services, while the functions of habitat maintenance and soil conservation services might be weakened by the expansion of farmland. The five ESDRs identified based on the above results had significant spatial clustering characteristics and spatial heterogeneity. The visual results of the MGWR model suggested that factors of land development could effectively mitigate conflicts between construction or farming activities and ESs. Ultimately, the spatial clusters of ESDRs were scientifically delimited and differentiated regulatory measures were developed simultaneously. Therefore, we argue that land use planning and environmental management in rapidly urbanizing areas should take into account the diagnostic framework of ESDRs in order to protect natural ecosystems. [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]

Previous studies have mostly focused on using visible-to-near-infrared spectral technique to quantitatively estimate soil cadmium (Cd) content, whereas little attention has been paid to identifying soil Cd contamination from a perspective of spectral classification. Here, we developed a framework to compare the potential of two spectral transformations (i.e., raw reflectance and continuum removal [CR]), three optimization strategies (i.e., full-spectrum, Boruta feature selection, and synthetic minority over-sampling technique [SMOTE]), and three classification algorithms (i.e., partial least squares discriminant analysis, random forest [RF], and support vector machine) for diagnosing soil Cd contamination. A total of 536 soil samples were collected from urban and suburban areas located in Wuhan City, China. Specifically, Boruta and SMOTE strategies were aimed at selecting the most informative predictors and obtaining balanced training datasets, respectively. Results indicated that soils contaminated by Cd induced decrease in spectral reflectance magnitude. Classification models developed after Boruta and SMOTE strategies out-performed to those from full-spectrum. A diagnose model combining CR preprocessing, SMOTE strategy, and RF algorithm achieved the highest validation accuracy for soil Cd (Kappa = 0.74). This study provides a theoretical reference for rapid identification of and monitoring of soil Cd contamination in urban and suburban areas. This study developed a framework for the use of the Vis–NIR spectroscopy to diagnose soil Cd contamination in urban and suburban soils. [ABSTRACT FROM AUTHOR]

Ecologically constrained urban expansion simulation (EC-UES) is an effective means to plan sustainable urban landscapes. Current studies typically set ecological constraints using Boolean logic while dismissing the spatially continuous and gradual features of ecological substrates. They also overlook the multiple ecosystem services (MESs) that an ecosystem provides and correlations among MESs. This study aggregated MESs (i.e., food productivity, water yield, carbon storage, biodiversity potential, erosion prevention, and outdoor recreation), based on an ordered weighted averaging (OWA) operator. An EC-UES was conducted for Wuhan, China by integrating the aggregation result as a constraint into a cellular automata (CA)-Markov chain model. By varying the β coefficient of the OWA, multiple scenarios of MESs constraint were designed and used to generate urban land patterns in different scenarios. We compared spatial patterns, quantities, and ecological effects of urban expansion in four typical scenarios. The results show that the incorporation of MESs constraint is beneficial for ecological conservation. However, the intensity of the constraint is not linearly proportional to benefit; very strong constraints from MESs may lead to the excessive loss of farmland and the irregularity and fragmentation of urban patterns. Compared to the conventional constraint strategy, a relatively soft constraint strategy was considered optimal. This study provides a reference for a win–win simulation between urban expansion and ecological conservation. • Multiple scenarios of urban expansion simulation under the MESs constraint are designed. • Spatial patterns, quantities and ecological effects of urban expansion in four typical scenarios are compared. • Compared with the traditional scenario, the "moderate MESs constraint" scenario is identified as the optimal. • This study provides a reference for the win-win simulation between urban expansion and ecological conservation. [ABSTRACT FROM AUTHOR]

Limited studies focus on educational equity from the spatial accessibility perspective. This study combines survey data and big data and proposes a multi-mode Huff two-step floating catchment area (MMH2SFCA) method to calculate accessibility while considering multiple travel modes and school attractiveness. This method can also calculate education quality by extending the accessibility in each community. Results show that our proposed method can reliably identify the accessibility differences of schools across communities. The case study indicates an inequitable distribution of educational accessibility and quality. The communities with high accessibility are concentrated in the urban center and exurban zones surrounding schools, whereas high-quality areas are mainly concentrated in the urban center. Correlation analysis suggests that the educational quality of communities with high accessibility is not always high. The findings of this study can provide improvement for accessibility measurements and help explore a new research perspective for educational equity research. [ABSTRACT FROM AUTHOR]

• Urban simulation aims for carbon emission reduction and sequestration conservation. • The integrated Markov-BRL-CA is feasible to simulate constrained urban expansion. • Four simulation scenarios based on different low-carbon strategies are designed. • Low-carbon strategies benefit compact and sustainable urban development. Rapid urbanization causes great changes of carbon metabolism. Current research mainly focuses on carbon consequences of urban expansion projections, but rarely explores how carbon management strategies affect future urban growth trajectories. Here, we propose a hierarchy of low-carbon management strategies and incorporate it into an integrated cellular automata model to obtain sustainable urban development plans. In the hierarchy, a top-down strategy regarding carbon emission reduction is used to adjust future urban land demand, while a bottom-up strategy regarding carbon sequestration conservation of land patches is used to constrain land use conversions. We design four expansion scenarios based on different combinations of the two low-carbon strategies for Wuhan in 2025, including business as usual (BAU), the scenario with top-town strategy (T-UES), the scenario with bottom-up strategy (B-UES), and the scenario with both two strategies (TB-UES). Our results demonstrate that the proposed method can generate promising urban expansion plans with less ecological loss, and promote compact and infilling urban development. [ABSTRACT FROM AUTHOR]

• Urban ventilation corridor recognition using circuit theory is proposed. • The method is based on numerical simulation of ventilation corridor analysis. • Wuhan urban area is analyzed using three-dimensional building data of 2015. • The method can identify ventilation corridor and analyze ventilation environment. • Complex aerodynamics calculations can be avoided in the proposed method. With the continuous development of global urbanization, the urban heat island effect has increasingly become one of the important factors that reduces the quality of urban life. Among the many factors affecting the formation of urban heat islands, urban canopy ventilation is considered to have great potential for improving urban heat islands. Based on the traditional numerical simulation of ventilation corridor analysis, this paper proposes a new approach for ventilation corridor recognition based on circuit theory. The connotations of resistance, current, and voltage in the simulation of urban ventilation environment were explained separately. Taking Wuhan as the research area, local three-dimensional building data were used as the data source, and a simulation experiment of the urban ventilation environment with different winds was carried out on the 100-m grid scale. Unlike the method based on the least-cost path analysis by which only a few main ventilation corridors can be generated, the results of the method proposed in this paper cover all grid cells in the study area. The simulation results were represented by probabilistic values, which can effectively reflect the ventilation corridor and ventilation barriers. In addition to identifying the ventilation corridors, the tuyeres were also well identified. [ABSTRACT FROM AUTHOR]

• This article examines the interaction between land use and commuting flows from mobile phone data based on the moderated multiple regression model. • The results reveal that urban land-use types of commuters' origins and destinations significantly influence commuting flows. • This study indicates that urban land-use types moderate the relationship between the distance and commuting flows as well. Commuting is an essential part of our urban daily life. Understanding of commuting flows is crucial for urban and traffic planning. Urban land use plays a fundamental role of urban studies, given that its verified impact on commuting pattern in previous studies. This paper explores whether urban land use influences the commuting flows and how it impacts the relationship between commuting flows and origin-destination distances (i.e., the accessibility). In this study, the basic gravity model is extended with land use variables. And both multiple regression and moderated multiple regression models are applied to analyze the relationship between commuting flows and land use (i.e., industrial, commercial, residential, educational land etc.), as well as the interaction effect between land use variables and the accessible distance. Commuting data is extracted from Wuhan's mobile phone signaling data in 2016, particularly incorporated in the empirical analysis. The results show that industrial and residential origins are likely to send more commuters while industrial and commercial destinations attract more. An interaction effect between land use and distance is revealed that commuting flows with industrial origins (destinations) decrease fastest with distance increasing while those with commercial origins (destinations) decrease slowest. These findings imply that: 1) Urban land use of commuters' origins and destinations significantly influences commuting flows; and 2) Urban land use moderates the relationship between the distance and commuting flows as well. This study contributes to policies-makings of urban and traffic planning through understanding commuting flows from the mobile phone signaling data perspective [ABSTRACT FROM AUTHOR]

• Absorption peak around 2310 nm was identified as the most important for SIC. • An urban SSL with 3492 samples was developed for SIC prediction. • CWT scale 1 showed the optimal performance in predicting SIC. • Performance of CNN was superior to other common machine learning models. • Stratifying SSL by LULC in more homogeneous classes achieved better SIC prediction. Urban soils and cultural layers may accumulate carbon over a long period, so certain carbon stocks may be stored beneath cities. Studies have shown that the turnover rate of soil inorganic carbon (SIC) is also fast, and its role in global carbon pool and regulation of atmospheric CO 2 should be noticed. Visible and near infrared (vis–NIR) spectroscopy, as a rapid and cost-effective approach, has demonstrated its huge potential for soil characterization. However, little has been reported on the potential of vis–NIR spectra for estimating SIC in urban and suburban areas that are greatly affected by human activities. Here, an urban soil spectral library (SSL) with 3492 samples in Wuhan City, China was established. Our main objective was to evaluate whether stratification of an urban SSL by land-use/land-cover (LULC) strategy can generate better estimation, compared with non-stratified (global) model for predicting SIC. Five modeling approaches were developed for SIC prediction: linear regression using an optimal spectral ratio index, and partial least squares regression, Cubist, convolutional neural network (CNN), and autoencoder-based residual deep network using full-spectrum. Raw absorbance was processed by continuous wavelet transform (CWT), thus decomposing spectral data at six scales. Results demonstrated that in almost all cases, CWT scale 1 obtained better performances in predicting SIC than raw absorbance and other five CWT scales. Stratification by LULC resulted in improved accuracy, compared with non-stratified model, with CWT scale 1 obtaining the highest validation R 2 of 0.73. Among the non-stratified modeling, CNN based on CWT scale 1 generated the optimal validation result with an R 2 value of 0.69. The most important spectral absorption for SIC was peaked around 2310 nm. This study confirms that vis–NIR technique combined with LULC stratification and machine/deep learning has a huge potential for SIC prediction in urban soils. [ABSTRACT FROM AUTHOR]

• Environmental variables have threshold and interaction effects on Pb concentration. • Gradient boosting decision tree is used to explore the two effects. • Threshold effects exhibit the effective ranges of covariates on Pb accumulation. • The two-way and three-way interaction effects of covariates on Pb are visualized. • Industrialization and urbanization are the most important sources of Pb contamination. Understanding the spatial distribution of soil lead concentration in peri-urban soil and its underlying mechanism is critical to controlling lead contamination, ensuring food safety, and maintaining sustainable urban development. Although the linear and nonlinear relationships between Pb and environmental variables have been extensively studied, the threshold and interaction effects of environmental factors on Pb content are often ignored. This study aims to investigate the threshold and interaction effects and obtain the spatial distribution of Pb content via gradient boosting decision tree. The peri-urban area of Wuhan City, China, was selected as the study area, where soil health was threatened by agricultural production and urbanization and industrialization process. Results showed that the 14 covariates can explain 61.9 % variation of Pb content, in which anthropogenic factors played a major role. Specifically, the Pb content was mainly affected by distance from the industrial enterprises and gasoline stations, population density, elevation, and total nitrogen, which denoted that Pb contamination was mainly originated from industrial production, gasoline stations, urbanized population, and fertilization. All environmental variables had threshold effects on Pb, and the relationship between Pb and these variables mutated when the threshold was exceeded. The results of threshold effects exhibited that Pb was elevated in locations near industrial enterprises (<4 km) or gasoline stations (<1.5 km), with a dense population (>5 person/hectare), and with low elevation (<25 and 45–65 m). The two-way and three-way interaction effects of covariates on Pb content was determined, indicating that the influence of environmental variables on Pb concentration is a complex interaction rather than a simple superposition. These findings highlight the consideration of threshold and interaction effects to understand the underlying processes that lead to Pb contamination, and have important implications for sustainable urban development. [ABSTRACT FROM AUTHOR]

• Patch prioritization is achieved by incorporating spatio-temporal connectivity. • Extended betweenness centrality metric is promising for habitat priority ranking. • Patch prioritization in dynamic landscapes better maintain habitat connectivity. • Targeted strategies are developed for biodiversity conservation in urban fringes. Habitat fragmentation has largely reduced biodiversity in the urban fringe. The prioritization of individual habitat patches can provide spatially explicit guidance for ecological conservation and restoration. Numerous studies discussed the effectiveness of purely spatial connectivity metrics to rank the conservation priority of habitats, but hardly resolved this issue in a dynamic landscape context. Meanwhile, spatio-temporal connectivity metrics were usually applied at the landscape scale, but are rarely extended to determine habitat priority at the patch scale. As such, we extend a generalized betweenness centrality metric into spatio-temporal connectivity networks to evaluate conservation priorities of individual habitat patches from a dynamic landscape perspective. The contribution rates of spatio-temporal connectivity metrics are examined at varying dispersal distances of the target species. Caidian District, the fringe of Wuhan City in central China, is taken as a case study. The results illustrate that a net decrease in habitat amounts and quality from 2005 to 2015 was mainly caused by urban expansion and agricultural production. The positive contribution rates of spatio-temporal connectivity metrics are observed at distance thresholds exceeding 200 m at the landscape scale, which allows us to capture the response of habitat priority to landscape dynamics. Accordingly, we develop a balanced conservation strategy for multiple species and the targeted conservation measures based on the coupled analysis of quality and conservation priority of habitat patches. Our findings are expected to provide solid support for biodiversity conservation in urban growth. [ABSTRACT FROM AUTHOR]

The regular monitoring of soil cadmium (Cd) in peri-urban agricultural soils is critical in maintaining soil security and balancing the local environment and ecosystem. Visible and near-infrared (Vis–NIR) spectroscopy provides an alternative to soil Cd estimation. Previous studies found a mild to moderate correlation of soil Cd against soil auxiliary information, including soil organic matter (SOM), Fe, and pH. This study aimed to determine whether the combination of spectral data and soil covariates would improve the model accuracy for soil Cd estimation. We collected 93 samples from a peri-urban agricultural area of Wuhan City, Central China. The reflectance spectra, Cd concentration, and soil properties, including SOM, Fe, and pH, were measured. In addition to the original spectra, the first (FDR) and second derivative reflectance were compared to process the spectra. Estimation models were developed using random forest. In particular, we tested two spectral reduction methods, namely, principle component analysis (PCA) and optimal band combination algorithm, to derive the spectral parameters. We compared three modeling strategies for soil Cd estimation as follows: strategy I with spectral data as input variables, strategy II with soil covariates as predictors, and strategy III with the combination of strategies I and II as predictors. Results indicated that the optimal band combination algorithm outperformed PCA regardless of the spectral transformations used. The inclusion of soil covariates into the spectral data improved the model prediction for soil Cd (validation r 2, 0.70–0.83) compared with the individual application of either spectral data (validation r 2, 0.55–0.68) or soil covariates (validation r 2 = 0.62) for modeling. The most successful prediction for soil Cd was achieved (validation r 2 = 0.83) using the combination of the optimal band combination algorithm on the basis of the FDR and additional soil information, for which the sum index, difference index, product index, and SOM were identified as important predictor variables. In summary, the proposed strategy of combining Vis–NIR spectroscopy with soil auxiliary information will increase the model performance for soil Cd and can be extended to other study sites. • Organic matter is the major spectral prediction mechanism for Cd. • The optimal band combination algorithm is useful in extracting spectral parameters. • Combinational use of spectral data and soil covariates improves the model accuracy. • Sum, difference, product indices, and organic matter are the important predictors. [ABSTRACT FROM AUTHOR]