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In the context of ecological protection and urban expansion, the quality of the ecological environment and ecological security are gravely at risk. A simple, effective, and comprehensive assessment method for regional environmental quality monitoring is urgently required at this time. This study proposes a comprehensive approach for evaluating regional ecological quality. Based on Landsat TM+OLI/TIRS images, indicators representing the ecological quality of land and water were constructed. Land ecological quality consists of land surface moisture (WET), normalized difference vegetation index (NDVI), normalized building bare soil index (NDBSI), and land surface temperature (LST), which represent humidity, greenness, dryness, and temperature, respectively. At the same time, the remote sensing indices of chlorophyll_a (chl_a) and suspended solids (SS) were constructed to characterize the water quality. Air quality was characterized based on aerosol optical depth (AOD) in MCD19A2. By introducing water and air quality indicators and utilizing principal component analysis, a remote sensing ecological index that improves water area assessment (WIRSEI) was established and applied to Wuhan from 2000 to 2020. The driving force of WIRSEI change was analyzed using the geographically weighted regression (GWR) model. The results revealed that (1) air quality AOD and humidity WET greatly impacted the ecological quality (WIRSEI). WIRSEIs in seven central urban areas were significantly lower than that in six remote urban regions, and the ecological quality of lakes was higher than that of rivers. (2) From 2000 to 2020, Wuhan's overall WIRSEI showed a "rising–falling–rising–stable" trend. In most regions, the degree of ecological quality change was relatively small; most grades were "no change", "slightly better", and "slightly worse", representing 88–93% of the total area. (3) The change in WIRSEI from 2000 to 2020 was closely related to urban expansion, population change, and economic development. The effects of land use and socioeconomic changes on WIRSEI were significantly different in spatial distribution. Compared to the driving factors, land use dynamics (LUCD) significantly impacted WIRSEI changes, while the effects of gross domestic product (GDP) and population (POP) were very small. This study uses WIRSEI to evaluate the regional ecological quality, providing a vital reference and basis for enhancing regional ecological quality assessment methods, promoting ecological environmental protection and restoration, regional coordination, and sustainable development. The research results show that the proposed approach is simple and effective, strongly supporting regional ecological quality and protection monitoring. [ABSTRACT FROM AUTHOR]

Construction land development suitability (CLDS) assessment holds paramount importance in contemporary urban planning and management. Previous CLDS studies have faced challenges such as insufficient evaluation indicators, model complexity, and limited interpretability. To address these gaps, this study applies three simplistic yet mature models from the field of geological hazard assessment - Weight of Evidence (WOE), Information Value (IV), and Frequency Ratio (FR) - to evaluate the CLDS in Wuhan, China, and examine their feasibility. In parallel, a comparative analysis with the Patch-generating Land Use Simulation (PLUS) model was conducted. The WOE, IV, and FR models demonstrate a gradual decrease in CLDS from the city center and the Yangtze and Han rivers towards the periphery. Conversely, the PLUS model indicates the highest suitability around the city's development boundaries, followed by the city center, with suburbs displaying lower suitability. In terms of accuracy, the PLUS model's CARS module outperforms others, particularly for micro-level urban expansion simulations. The IV and WOE models follow closely, manifesting a preference for macro-level urban planning. Additionally, this study pinpoints key drivers influencing CLDS, notably population density, distance to social service Points of Interest (POI) and proximity to road networks. The cross-validation of the WOE, IV, and FR models underscores their reliability, with their straightforward principles positioning them as valuable tools in urban development planning. This comparative study validates the application of geological hazard models in urban contexts and diversifies CLDS assessment methodologies. [Display omitted] • Transplantation and Application of Geological Hazard Models. • Comprehensive Indicator System Incorporating Multivariate Driving Factors. • Multi-Model Assessment of Construction Land Development Suitability. • Spatial Prediction of Construction Land under Quantity Constraints. [ABSTRACT FROM AUTHOR]

Dramatic land cover changes related to the accelerated urbanization process have led to habitat fragmentation and loss, resulting in biodiversity loss. Ecological Networks (ENs) have been seen as an effective solution for ecological conservation targeting habitat connectedness and ecosystem functions. The EN research is, however, generally depicted by current or historical landscape data, devoid of the potential future disturbances, which is detrimental to maintaining EN's stability and sustainability. This study combines the system dynamics (SD) model and patch-generating land use simulation (PLUS) to simulate land use patterns in Wuhan urban agglomeration (WUA), China. The simulated land use data were incorporated into EN modeling to assess the long-term dynamics of EN in WUA, considering two scenarios related to human activities and climate change. In parallel, a landscape graphs approach is used to estimate the spatial priority of EN for conservation in landscape dynamics. The results show that: (1) The grassland decreased from 2000 to 2020 and is expected to increase from 2020 to 2035. The area of construction land would reach its peak in 2035 while cultivated land would hit a low point. (2) Analysis of EN reveals habitat fragmentation and reduced connectivity from 2000 to 2020. From 2020 to 2035, an increase in EN connectivity is expected to be observed in the SSP5–8.5 scenario, while SSP2–4.5 is the reduced scenario. (3) Southern and eastern WUA exhibit high conservation priority. The hotspots of local landscape changes are mainly the corridors that traverse through human activity areas and the edges of core habitats, which is critical to conserving. (4) The impact of natural and socioeconomic factors on EN exhibits spatial heterogeneity. This paper provides new insights to protect habitats and biodiversity to mitigate the challenge of human activities and climate change. [Display omitted] • Scenario simulation evaluates the impacts of human and climate change on ecological network. • The SSP5-8.5 indicates an increase in connectivity of the ecological networks. • The impact of urban development on the ecological network varies depending on urban structures. • More emphasis should be focused on the hotspot areas where the local landscape changes. • A scenario of increased connectivity does not imply that it should be prioritized. [ABSTRACT FROM AUTHOR]

Ecological Risk Assessment (ERA) is a critical component of ecosystem management aimed at identifying potential harms caused by human activities. However, previous studies have been limited by short periods, narrow perspectives, and a focus on single-risk factors, making it difficult to comprehensively assess ecological risk. To address these issues, our study investigates ecological risk changes in Wuhan from 1996 to 2020, adopting a multi-perspective method. We then employed a unified scalar overlay approach that fuses the Landscape Ecological Risk Index (LERI) and Habitat Degradation Index (HDI) to conduct an in-depth analysis of comprehensive ecological risk. It considers the interrelationships between threat sources and receptors, as well as the morphological structure of patches, to extract spatial information of ecological risks. Our results reveal that: (1) Wuhan's cropland decreased by 1760.98km2 (−38.95%), mainly converting to construction land and woodland. Simultaneously, construction land expanded outwards from the city center (+895.72km2). At the landscape level, Wuhan's landscape patches are becoming progressively more fragmented. (2) Total Ecological Risk Index (SERI) retains the "Low-High-Low" pattern of both LERI and HDI from the inside out, with high ecological risks radiating from the central urban boundary towards the surrounding regions. The lower-risk areas of the SERI converted mainly to the low-risk areas, whereas the area of higher-risk experienced a larger increase (+1083.45km2), mainly from high-risk areas. Overall, the SERI of Wuhan tends to move towards the north and east. (3) Spatially, hot-spots of risk are predominantly concentrated in the north of Wuhan, while cold-spots are primarily located in the city center. Confidence degrees of both hot and cold spots decrease from their center to the external areas. Additionally, ecological risk showed significant spatial dependency in its distribution. Given the current global environmental crisis, ecological risk research is more important than ever, and our new ERA framework is developed to provide valuable insights for urban planners to mitigate ecological risk. • Long-term, broad perspective multi-factor ecological risk assessment. • Novel ecological risk index (SERI) by fusing LERI and HDI. • Multi-dimensional visualization of ecological risk. • Utilization of high-quality foundational data. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to present initial findings from a vulnerability assessment based on the perceptions of practitioners working in four tourism and hospitality sectors in Wuhan and Hubei Province, namely, cruise lines, hotels, travel agencies and touristic attractions. Design/methodology/approach: The research note focuses on the coronavirus (COVID-19) outbreak from January to March 2020. Using the destination sustainability framework and an "interpretation" mixed methods research design, the authors analyze phone interviews (n = 151) and subsequent online surveys (n = 370) to assess sector-specific perceptions of exposure, sensitivity and system adaptiveness. Findings: Overall, findings paint a grim picture of each sector in the short-term. All respondents reported an immediate economic loss due to COVID-19, as well as recovery concerns and uncertainties. Immediate actions for addressing these issues centered on internal cost control and governmental subsidies, while anticipated next steps focused on product adjustment, a transformation of business structures and seeking governmental guidance and policies in restoring market confidence. Findings also allude to future strategies/directions. Research limitations/implications: This study is limited in its focus on practitioner views in the immediate COVID-19 outbreak. Implications highlight a crucial strategic dependence of each sector on effective government/managerial communication and support, with smaller, local businesses needing particular attention in crisis situations. Originality/value: To the authors' knowledge, this research note is the first comprehensive study presenting vital information pertaining to the impact of COVID-19 on tourism and hospitality businesses from a large group of business leaders in the site of the initial outbreak (i.e. Wuhan and Hubei Province). With the highly infectious COVID-19 representing an ongoing threat for populations worldwide, this paper hopes this research note provides valuable insights for practitioners in other vulnerable regions, as well as for researchers examining strategies for resilience against this and future disasters. [ABSTRACT FROM AUTHOR]

• An urban CA modelling framework was proposed to simulate urban growth. • A Gaussian-based model was applied to represent the wave-shaped diffusion of urban development. • A patch-based allocation engine was employed to spatialize urban demand. • Urban development suitability was estimated using a cutting-edge deep forest model. Cellular automata (CA) has become one of the most prevalent approaches for spatially explicit urban growth modeling. Previous studies have investigated how the key components of CA models are defined, structured, and coupled to represent the top-down and bottom-up processes of urban growth. However, the spatiotemporal heterogeneity of urban demand at the macro level and its coupling with micro-level urban land configurations have not been fully explored in existing CA models. This study proposes a new urban CA modeling framework to simulate urban expansion by using a spatiotemporally explicit urban demand modeling scheme that guides the patch-based allocation of urban land at the micro level. In this framework, spatiotemporal Gaussian-based models were applied to represent the spatiotemporal heterogeneity of urban demand within a set of concentric rings in terms of the fraction of new urban land and frequency of new urban development. An application of the modeling framework to the metropolitan city of Wuhan, China demonstrates that the demand of new urban land in the study area exhibits an outgoing wave-shaped propagation pattern, which can be well fitted by the spatiotemporal Gaussian-based models, with R2 values exceeding 0.8. The proposed spatiotemporally explicit representation of urban demand can improve model performance in capturing urban dynamics at both macro and micro levels, as revealed by pattern-level similarity and cell-level agreement of simulation results. [ABSTRACT FROM AUTHOR]

[Display omitted] • Heat source and sink landscapes have opposing influences on the UHI effect. • The new metric can be employed in temperature prediction. • Heterogeneous impact of landscape on temperature varies with landscape level. • A clearly defined threshold of landscape indices can help to control the UHI effect. Studies on the interactions between landscape patterns and land surface temperature (LST) are critical to mitigate urban heat islands (UHIs). However, integrated spatial indices combining both composition and configuration to quantify this relationship requires further development. We present an index of spatial connectivity between patches of the heat source and sink (SCSS) to assess the heterogeneity impact of landscape patterns on LST in Wuhan, China. We examined the relationship between LST and SCSS at the urban (within the urban growth boundaries, UGBs) and city levels, using spatial regression analyses. Results show that: (1) the SCSS and LST presented a significant negative correlation, and the SCSS can explain 76% and 81% of the variability in LST at city level and urban level, respectively; (2) for every 0.1 increase in SCSS, the LST will decrease by 0.96 °C at city level, and 1.67 °C at urban level; (3) the percentage of the source landscape area should be no more than 62% and the SCSS should not fall below 0.18 to control the UHI effect; (4) maintaining the percentage of the source landscape area at below 18%, and the value of SCSS at over 0.43, will help to bring about a significant cooling effect. Our findings allow a better understanding of the interactions between the spatial heterogeneity and the thermal regulation function of landscapes and provide insights for urban planners to mitigate the UHI effect. [ABSTRACT FROM AUTHOR]

Rapid urbanization significantly affects the productivity of the terrestrial ecosystem and the foundation of regional ecosystem services, thereby detrimentally influencing the ecological environment and urban ecological security. The United Nations' Sustainable Development Goals (SDGs) also require accurate and timely assessments of where people live in order to develop, implement and monitor sustainable development policies. Sustainable development also emphasizes the process of protecting the ecological environment for future generations while maintaining the current needs of mankind. We propose a comprehensive evaluation method for urban ecological quality (UEQ) using Landsat TM/ETM+/OLI/TIRS images to extract remote sensing information representing four ecological elements, namely humidity, greenness, heat and dryness. An improved comprehensive remote sensing ecological index (IRSEI) evaluation model is constructed by combining the entropy weight method and principal component analysis. This modeling is applied to the city of Wuhan, China, from 1995 to 2020. Spatial autocorrelation analysis was conducted on the geographic clusters of the IRSEI. The results show that (1) from 1995 to 2015, the mean IRSEI of Wuhan city decreased from 0.60 to 0.47, indicating that environmental deterioration overwhelmed improvements; (2) the global Moran's I for IRSEI ranged from 0.535 to 0.592 from 1995 to 2020, indicating significant heterogeneity in its spatial distribution, highlighting that high and low clusters gradually developed at the edge of the city and at the city center, respectively; (3) the high clusters are mainly distributed in the Huangpi and Jiangxia districts, and the low clusters at the city center, which exhibits a dense population and intense human activity. This paper uses remote sensing index methods to evaluate UEQ as a scientific theoretical basis for the improvement of UEQ, the control of UEQ and the formulation of urban sustainable development strategies in the future. Our results show that the UEQ method is a low-cost, feasible and simple technique that can be used for territorial spatial control and spatiotemporal urban sustainable development. [ABSTRACT FROM AUTHOR]

Urban Growth Boundaries (UGBs) are a tool to control urban sprawl. However, the way to optimize future urban land uses and fix their boundaries is not clear. This paper presents a new framework to delimit UGBs while accounting for ecological, economic, and carbon storage benefits. Aggregate land-use constraints are included in a multi-objective optimization algorithm to capture non-inferior solutions on the Pareto Surface (PS) under different objective scenarios. A patch-level cellular automata simulation model is then used to spatially allocate these land uses, followed by a new two-step adjustment method to delineate the UGBs. This modeling is applied to Wuhan, China. The results show that: (1) One district (Caidian) will have a strong economic growth under low-carbon development. (2) The maximization of carbon storage reduces losses in ecological benefits, suggesting that carbon storage be considered in urban growth planning. (3) The combined model framework and two-step boundary adjustment method can help urban planners define different UGB scenarios and make science-based policy decisions. [Display omitted] • Modeling methodology to delineate urban growth boundaries (UGBs). • Combining Multi-objective Programming (MOP) and land-use simulation. • Objectives include economic, ecological and carbon storage benefits. • MOP captures land allocations on the Pareto Surface. • Low-carbon urban development maximizes land-use carbon storage. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comparative study of urban expansion and WESs in two megacities was conducted. • In Chengdu, urban expansion had an edge-based pattern that encompassed city-wide. • In Wuhan, suburban expansion is growing rapidly due to leapfrogging development. • Urban expansion has larger negative effects on WY and WP in Wuhan's suburbs. • Ecological land in the megacities' center suffered from indirect loss of WESs. The megacity expansion that continues to occur in developing countries is an unavoidable trend at this stage, yet there exists a dearth of knowledge regarding the comprehensive impacts of urban expansion on water-related ecosystem services (WESs) within these areas. Taking Chengdu and Wuhan, two megacities in the upper and middle Yangtze River Economic Belt in China as the study area, this study first compare the magnitude, rate, spatial divergence, and the mode of urban expansion; then evaluate its impact on three typical types of WESs, i.e., water yield (WY), water purification (WP), and habitat quality (HQ) using spatial econometric models and bivariate Moran's I. The research findings show that Chengdu's suburbs tend to experience edge-based expansion along rivers, while Wuhan's city center also spreads outward in edge-based from the river junctions of the Yangtze and Han rivers. Urban expansion negatively impacts all three types of WESs, and its effect in Chengdu is greater than in Wuhan. WY in the suburbs of Wuhan is severely impacted by urban expansion, while WP in the suburbs of Chengdu is as well. HQ in Chengdu's city center suffers the largest negative impact. The study also reveals a spatial spillover effect of urban expansion, with extensive negative externalities on all WESs in the city centers of both cities and positive externalities on WY and WP in the southwestern suburbs of Chengdu. Based on these results, we suggest that megacities in developing countries should focus on protecting HQ in the city center and limiting cross-regional edge-based expansion in suburbs. Attention should be paid to the water-ecological protection of the suburb rivers. City managers should consider ecological zoning geared toward the conservation of WESs to address the adverse impacts of expansion. [ABSTRACT FROM AUTHOR]

Data and skill gaps are common in exploring future urban growth scenarios, especially in developing countries. This study demonstrates how to use distance-related laws regarding process and pattern of urban development to bypass the heavy data and skills required in traditional urban expansion models that rely on various driving factors and machine-learning algorithms. We proposed an urban simulation model that uses three distance-driven components alone to simulate urban expansion by regulating urban morphology at multiple levels. The landscape-level component discriminates the spatiotemporal distribution of urban demand based on rules linked to distance to city centers. The class-level component applies an exponential model with the distance to pre-urbanized patches to control where new urban development may expand. The patch-level component creates urban patches of given sizes with shapes controlled by their distances to the initial patch seeds. Application of the model in Wuhan, China confirms the efficacy of the model and its distance-driven components, as supported by both cell-level agreement and pattern-level similarity. The overarching contribution of DisUSIM lies in providing a distance-driven framework for convenient exploration of urban dynamics in situations where datasets and skills on processing and analyzing driving factors and mechanisms of urban expansion are not readily available. • A distance-driven CA model was proposed for simulation of urban growth. • The model uses three distance-driven components to regulate urban morphology at the landscape-, class- and patch-level. • The model enables modelers to explore future urban growth scenarios of various spatial morphologies. • The model is convenient for rapid urban simulation in situations where information on driving factors is unknown in advance. [ABSTRACT FROM AUTHOR]