Search Results (1,802)

As urbanization accelerates, characteristics of urban spatial expansion play a significant role in the future utilization of land resources, the protection of the ecological environment, and the coordinated development of population and land. In this study, Yunnan and Guizhou provinces were selected as the study area, and the 2013–2021 National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light (NTL) data were utilized for spatial and temporal change analysis of urban built-up areas. Firstly, the built-up areas in Yunnan and Guizhou provinces were extracted through ENUI (Enhanced Nighttime Lighting Urban Index) indices, and then the urban expansion speed and urban center of gravity migration were constructed and used to explore and analyze the spatial and temporal change and expansion characteristics of built-up areas in Yunnan and Guizhou provinces. The results showed the following. (1) Due to the complementarity between data types, such as NTL, EVI, NDBI, and NDWI, ENUI has better performance in expressing urban characteristics. (2) Influenced by national and local policies, such as “One Belt, One Road”, transportation infrastructure construction, geographic location, the historical background, and other factors, the urban expansion rate of Yunnan and Guizhou provinces in general showed a continuous advancement from 2013 to 2021, and there were three years in which the expansion rate was positive. (3) The center of gravity migration distance of most cities in Guizhou Province shows a trend of increasing and then decreasing, while the center of gravity migration distance in Yunnan Province shows a trend of continuous decrease in general. From the perspective of migration direction, Guizhou Province has the largest number of migrations to the northeast, while Yunnan Province has the largest number of migrations to the southeast. (4) Influenced by policy, economy, population, geography, and other factors, urban compactness in Yunnan and Guizhou provinces continued to grow from 2013 to 2021. The results of this study can help us better understand urbanization in western China, reveal the urban expansion patterns and spatial characteristics of Yunnan and Guizhou provinces, and provide valuable references for development planning and policymaking in Yunnan and Guizhou provinces. Full article

As urbanization accelerates, World Heritage properties, critical conservation areas, face a growing threat of urban densification, jeopardizing their Outstanding Universal Value (OUV). States Parties, the countries that have ratified the World Heritage Convention, are responsible for submitting periodic reports on the state-of-conservation of their World Heritage properties. These reports should explicitly address any instances of urban densification that may be occurring. But do they? This research investigates the relationship between urban densification and reporting practices in World Heritage properties over time and space. Through a spatiotemporal analysis, by analyzing changes in the built-up area within the core zones of cultural World Heritage properties from 1985 to 2015. We found that urban development, including housing, infrastructure, and tourism facilities, has significantly impacted World Heritage properties and an increase in built-up area can be observed especially in properties not reporting on urban threats. Full article

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning. Full article

China’s vulnerability to fluvial floods necessitates extensive exposure studies. Previous large-scale regional analyses often relied on a limited set of assessment indicators due to challenges in data acquisition, compounded by the scarcity of corresponding large-scale flood distribution data. The integration of public datasets offers a potential solution to these challenges. In this study, we obtained four key exposure indicators—population, built-up area (BA), road length (RL), and average gross domestic product (GDP)—and conducted an innovative analysis of their correlations both overall and locally. Utilising these indicators, we developed a comprehensive exposure index employing entropy-weighting and k-means clustering methods and assessed fluvial flood exposure across multiple return periods using fluvial flood maps. The datasets used for these indicators, as well as the flood maps, are primarily derived from remote sensing products. Our findings indicate a weak correlation between the various indicators at both global and local scales, underscoring the limitations of using singular indicators for a thorough exposure assessment. Notably, we observed a significant concentration of exposure and river flooding east of the Hu Line, particularly within the eastern coastal region. As flood return periods extended from 10 to 500 years, the extent of areas with flood depths exceeding 1 m expanded markedly, encompassing 2.24% of China’s territory. This expansion heightened flood risks across 15 administrative regions with varying exposure levels, particularly in Jiangsu (JS) and Shanghai (SH). This research provides a robust framework for understanding flood risk dynamics, advocating for resource allocation towards prevention and control in high-exposure, high-flood areas. Our findings establish a solid scientific foundation for effectively mitigating river flood risks in China and promoting sustainable development. Full article

Clarifying the complex relationships among ecosystem services (ESs) and their driving mechanisms is essential for effective ecosystem management and enhancing human welfare. Nonetheless, the current research on these issues still remains limited; therefore, further theoretical exploration is required. This study aims to quantitatively illustrate the trade-off strength of ESs and investigate the spatiotemporal heterogeneity connections between these relationships and various anthropogenic and natural factors in Baiyangdian basin, China, integrating InVEST, RMSE, geographical detector and MGWR methods. From 2000 to 2020, the total water yield (WY) and nutrient export (NE) increased, while the total carbon storage (CS) and habitat quality (HQ) decreased slightly. The trade-offs of ESs showed spatiotemporal heterogeneity. The most serious trade-off occurred between regulating services (CS and NE) and supporting services (HQ) in 2000, which was mainly distributed in the densely forested and grassed western and northern regions of the basin. The trade-off intensities of half of the pairwise ESs in 2020 increased, with the strengthened areas mainly located in the southeast of the watershed where built-up lands are concentrated. Various factors dominated the trade-offs among ESs, with the interactive effects of multiple drivers being more significant than those of individual factors. Land use type, vegetation cover and precipitation have the most pronounced effect on the trade-offs among ESs. The findings of this study may suggest and advocate for spatial ecological strategies to enhance the integrated and holistic advancement of various ESs and also serve as a reference for regional ecosystem governance and the attainment of sustainable growth. Full article

Despite various interventions in road safety work, fatal and severe road traffic accidents ($\mathrm{R}\mathrm{T}\mathrm{A}\mathrm{s}$) remain a significant challenge, leading to human suffering and economic costs. Understanding the multicausal nature of $\mathrm{R}\mathrm{T}\mathrm{A}\mathrm{s}$, where multiple conditions and factors interact, is crucial for developing effective prevention measures in road safety work. This study investigates the multivariate statistical analysis of co-occurring conditions in $\mathrm{R}\mathrm{T}\mathrm{A}\mathrm{s}$, focusing on single-vehicle accidents with single occupancy and personal injury on Austrian roads outside built-up areas from 2012 to 2019. The aim is to detect recurring combinations of accident-related variables, referred to as blackpatterns ($\mathrm{B}\mathrm{P}\mathrm{s}$), using the Austrian $\mathrm{R}\mathrm{T}\mathrm{A}$ database. This study proposes Fisher’s exact test to estimate the relationship between an accident-related variable and fatal and severe $\mathrm{R}\mathrm{T}\mathrm{A}\mathrm{s}$ (severe casualties). In terms of pattern recognition, this study develops the maximum combination value ($\mathrm{M}\mathrm{C}\mathrm{V}$) of accident-related variables, a procedure to search through all possible combinations of variables to find the one that has the highest frequency. The accident investigation proceeds with the application of pattern recognition methods, including binomial logistic regression and a newly developed method, the PATTERMAX method, created to accurately detect and analyse variable-specific $\mathrm{B}\mathrm{P}\mathrm{s}$ in $\mathrm{R}\mathrm{T}\mathrm{A}$ data. Findings indicate significant $\mathrm{B}\mathrm{P}\mathrm{s}$ contributing to severe accidents. The combination of binomial logistic regression and the PATTERMAX method appears to be a promising approach to investigate severe accidents, providing both insights into detailed variable combinations and their impact on accident severity. Full article

The design of urban systems that allow growth while also maximising ecosystem services is identified as an important priority for creating a Good Anthropocene. An ecosystem service (ES)-based approach to landscape interventions maximises the provision of ESs, and in doing so, repairs and reinforces threatened ecological planetary boundaries. As an urbanising planet, cities are critical frontiers of human interaction with these planetary boundaries, and therefore a critical arena for ES-based intervention. Globally, the predominant pattern of urbanisation is dedensification, an outwardly expanding trend where cities are growing in physical extent at a higher rate than their population growth. We therefore require spatially explicit tools capable of reconciling dedensification and Good Anthropocene visions. We propose a methodology that integrates agroecology and urbanisation and is focussed specifically on the supply of targeted regulating ESs. This ‘Agroecology for the City’ differs from conventional urban agriculture discourse and its preoccupation with food security. Our research interest is agroecological farm systems’ (AFSs) capacity to provide critical life support services in a spatially effective manner to urban systems. Our recent research introduced a new GIS-based model (ESMAX) and a spatial agroecology approach that identified AFS configurations at a 1 ha scale which maximised the supply of three regulating ESs, as well as multifunctional performance across all three ESs combined. In the present research, we apply this process at a larger scale, with 1 ha and 4 ha AFS parcels being integrated with a real-world 200 ha peri-urban residential development. The AFS parcels and built-up areas are configured differently to maximise the supply of ESs identified as critical by the local community. We found that arrangements with AFS parcels interspersed evenly with built-up areas provided the best multifunctionality across the four ESs tested. This supports pathways for a Good Anthropocene that work with the global urbanising reality of dedensification and underpin the need for a hybrid science of rural/urban systems. Full article

The prevention of ecological risks is a critical determinant influencing sustainable development. Driven by rapid socio-economic development, the ecosystems of mountainous cities within agro-pastoral transition zones are increasingly vulnerable to complex disturbances, constituting a significant threat to sustainable development and human well-being. To help achieve sustainable development, it is essential to conduct research on addressing and mitigating ecological risks from the perspective of collaborative management networks in mountainous cities. Taking Zhangjiakou as the study area, this paper employed the land use transfer matrix and standard deviation ellipse methods to analyze the dynamic land use changes. Additionally, using Fragstats 4,2 to calculate the landscape indices with land use data, this paper evaluated the landscape ecological risk (LER) from 2000 to 2020. Furthermore, the social network analysis (SNA) method was utilized to explore the spatial correlation characteristics of the LER. The findings indicate that: (1) Cultivated land and grassland were the predominant land use types in Zhangjiakou. During 2000–2020, Zhangjiakou experienced significant changes in land use, dominated by the transfer among cultivated land, forestland, and grassland. It indicated that the issue of unstable ecological land use continued to exist. Affected by human activities, construction land showed a consistent upward trend, primarily concentrated in the urban built-up areas and areas along the Jing-Zhang Railway. (2) The LER of Zhangjiakou was predominantly characterized by low risk, medium risk, and high risk levels. In the transitional areas and foothills, the LER was relatively higher. During 2000–2020, Zhangjiakou showed a declining trend of LER. This suggested that the ecological protection policies in Zhangjiakou were effective, leading to an improvement in the local ecological environment. (3) The LER in Zhangjiakou demonstrated a spatial clustering pattern that exhibited an upward trend, which was supported by both spatial autocorrelation and the SNA analysis. In the LER collaborative management network, Xuanhua, Qiaodong, Qiaoxi, Wanquan and Zhangbei consistently upheld pivotal roles. Based on the number of inward and outward connections, 16 counties in Zhangjiakou were classified into four categories and three zones accompanied by corresponding recommendations. The findings of this study can serve as a valuable reference for subsequent landscape pattern optimization and ecological restoration in Zhangjiakou. Full article

Taking Xining City as an example, this article analyzes the mechanism by which industrial park construction drives the expansion of urban population size and built-up area, based on a review of the process of industrial park development and urban population growth. It also discusses future urban governance models in light of urban development trends. The research finds: (1) In the process of urban development, industrial park construction is often the initial factor in the cumulative and cyclical development of a city; (2) As the level of development improves and the mode of economic growth changes, the government should timely adjust its strategies, shifting from the expansion of industrial park construction towards structural optimization and quality improvement. The most significant difference from previous research is that this paper emphasizes the importance of government planning. This study can not only demonstrate the general process of industrial parks promoting urban expansion, but more importantly, it explains the fundamental reasons for the transition of urban expansion to adjustment from a mechanism perspective, thereby eliminating the drawbacks of simply predicting urban scale evolution through data models. Full article

This study simulated the spatiotemporal changes in coastal ecosystem services (ESs) in the Jiaodong Peninsula from 2000 to 2050 and analyzed the driving mechanisms of climate change and human activities with respect to ESs, aiming to provide policy recommendations that promote regional sustainable development. Future climate change and land use were forecast based on scenarios from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was used to assess ESs such as water yield (WY), carbon storage (CS), soil retention (SR), and habitat quality (HQ). Key drivers of ESs were identified using Structural Equation Modeling (SEM). Results demonstrate the following: (1) High WY services are concentrated in coastal built-up areas, while high CS, HQ, and SR services are mainly found in the mountainous and hilly regions with extensive forests and grasslands. (2) By 2050, CS and HQ will show a gradual degradation trend, while the annual variations in WY and SR are closely related to precipitation. Among the different scenarios, the most severe ES degradation occurs under the SSP5-8.5 scenario, while the SSP1-2.6 scenario shows relatively less degradation. (3) SEM analysis indicates that urbanization leads to continuous declines in CS and HQ, with human activities and topographic factors controlling the spatial distribution of the four ESs. Climate factors can directly influence WY and SR, and their impact on ESs is stronger in scenarios with higher human activity intensity than in those with lower human activity intensity. (4) Considering the combined effects of human activities and climate change on ESs, we recommend that future development decisions be made to rationally control the intensity of human activities and give greater consideration to the impact of climate factors on ESs in the context of climate change. Full article

Urban vitality, which indicates the development level of a city and the quality of life of its residents, is a complex subject in urban research due to its diverse assessment methods and intricate impact mechanisms. This study uses multisource data to evaluate the urban vitality of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) across social, economic, cultural, and environmental dimensions. It analyzes the spatial distribution characteristics of urban vitality and examines the relationships between urban vitality and land use at both regional and city scales. The results indicate that the urban vitality in the GBA generally exhibits a spatial distribution pattern of a high central density and a low peripheral spread, where built-up areas and cropland emerge as key influencing factors. Cities with different developmental backgrounds have unique relationships between land use and urban vitality. In high-vitality cities, the role of the built-up area diminishes, and natural ecosystems, such as wetlands, enhance vitality. In contrast, in low-vitality cities, built-up areas boost urban vitality, and agriculture-related land types exert a lower negative or even positive effect. This research contributes to the understanding of the spatial structures of urban vitality related to land use at different scales and offers insights for urban planners, builders, and development managers in formulating targeted urban vitality enhancement strategies at the regional collaborative and city levels. Full article

In recent years, the socio-economic development in the Tibet region of China has experienced substantial growth. However, transportation increasingly strains the region’s fragile ecological environment. Most studies overlook the accurate measurement and analysis of factors influencing traffic carbon emissions in Tibet due to data scarcity. To address this, this paper applies an improved traffic carbon emissions model, using transportation turnover data to estimate emissions in Tibet from 2008 to 2020. Simultaneously, the estimated traffic carbon emissions in Tibet served as the predicted variable, and various machine learning algorithms, including Radial Basis Function Support Vector Machine (RBF-SVM), eXtreme Gradient Boosting (XGBoost), Random Forest, and Gradient Boosting Decision Tree (GBDT) are employed to conduct an initial comparison of the constructed prediction models using three-fold cross-validation and multiple evaluation metrics. The best-performing model undergoes further optimization using Grid Search (GS) and Real-coded Genetic Algorithm (RGA). Finally, the central difference method and Local Interpretable Model-Agnostic Explanation (LIME) algorithm are used for local sensitivity and interpretability analyses on twelve core variables. The results assess each variable’s contribution to the model’s output, enabling a comprehensive analysis of their impact on Tibet’s traffic carbon emissions. The findings demonstrate a significant upward trend in Tibet’s traffic carbon emissions, with road transportation and civil aviation being the main contributors. The RBF-SVM algorithm is most suitable for predicting traffic carbon emissions in this region. After GS optimization, the model’s R² value exceeded 0.99, indicating high predictive accuracy and stability. Key factors influencing traffic carbon emissions in Tibet include civilian vehicle numbers, transportation land-use area, transportation output value, urban green coverage areas, per capita GDP, and built-up area. This paper provides a systematic framework and empirical support for measuring, predicting, and analyzing factors influencing traffic carbon emissions in Tibet. It employs innovative measurement methods, optimized machine learning models, and detailed sensitivity and interpretability analyses. The results can guide regional carbon reduction targets and promote green sustainable development. Full article

Elevated temperatures in urban centers have become a common problem in cities around the world. However, the climate problems in suburban areas are equally severe; there is an urgent need to find zero-carbon ways to mitigate this problem. Recent studies have revealed the thermal performance of vegetation, buildings, and water surfaces. They functioned differently regarding the climate at different periods of the day. Accordingly, this study synthesizes remote sensing technology and meteorology station observation data to deeply explore the differences in the role of each climate-influencing factor in the suburban areas of Chengdu. The land surface temperature (LST) and air temperature (T_a) were used as thermal environmental indicators, while the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), and altitude were used as environmental factors. The results showed that the relevant influences of the environmental factors on the climate in the sample areas were significantly affected by the time of the day. The NDVI (R² = 0.5884), NDBI (R² = 0.3012), and altitude (R² = 0.5638) all showed strong correlations with T_a during the night (20:00–7:00), which gradually weakened after sunrise, yet the NDWI showed a poorer cooling effect during the night, which gradually strengthened after sunrise, reaching a maximum at 15:00 (R² = 0.5012). One reason for this phenomenon was the daily weather changes. These findings facilitate the advancement of the understanding of the climate in suburban areas and provide clear directions for further thermal services targeted towards people in different urban areas. Full article

The Rapid expansion of the Lanzhou–Xining (Lanxi) urban cluster in China during recent decades poses a threat to the fragile arid environment. Quantitatively assessing the impact of urban expansion on vegetation in the Lanxi urban cluster has profound implications for future sustainable urban planning. This study investigated the urban expansion dynamics of the Lanxi urban cluster and its impacts on regional vegetation between 2001 and 2021 based on time series land cover data and auxiliary remote sensing data, such as digital elevation model (DEM) data, nighttime light data, and administrative boundary data. Thereinto, urban expansion dynamics were evaluated using the annual China Land Cover Dataset (CLCD, 2001–2021). Urban expansion impacts on regional vegetation were assessed via the Vegetation Disturbance Index (VDI), an index capable of quantitatively assessing the positive and negative impacts of urban expansion at the pixel level, which can be obtained by overlaying the Enhanced Vegetation Index (EVI) and rainfall data. The major findings indicate that: (1) Over the past two decades, the Lanxi region has experienced rapid urban expansion, with the built-up area expanding from 183.50 km² to 294.30 km², which is an average annual expansion rate of 2.39%. Notably, Lanzhou, Baiyin, and Xining dominated the expansion. (2) Urban expansion negatively affected approximately 53.50 km² of vegetation, while about 39.56 km² saw positive impacts. The negative effects were mainly due to the loss of cropland and grassland. Therefore, cities in drylands should balance urban development and vegetation conservation by strictly controlling cropland and grassland occupancy and promoting intelligent urban growth. Full article

Land use/cover change (LUCC) can either enhance the areal carbon reserve capacity or exacerbate carbon emission issues, thereby significantly influencing global climate change. Comprehending the impact of LUCC on regional carbon reserve variation holds great significance for regional ecosystem preservation and socioeconomic sustainable development. This study focuses on Liaoning Province, leveraging land use remote sensing data from three periods from 2000 to 2020, natural environmental data and socioeconomic data in conjunction with the Integrated Valuation of Environmental Services and Trade-offs (InVEST) model, and patch-generating land use simulation (PLUS) models. It analyzes the interactive relationship between LUCC and carbon reserves in Liaoning Province between 2000 and 2020 and forecasts the trajectory of carbon reserve changes in Liaoning Province under various scenarios: business as usual, urban development, cropland protection, and ecological protection, all based on LUCC simulations. The findings indicate the following: (1) Over the study period, Liaoning Province experienced significant LUCC characterized primarily by the transformation of farmland to built-up land. Carbon reserves initially declined and later increased due to LUCC changes, resulting in a cumulative increase of 30.52 Tg C. The spatial distribution of carbon reserves was influenced by LUCC, displaying a pattern of spatial aggregation, with higher values in the east and lower values in the west. (2) Across the four simulation scenarios, the spatial pattern of carbon reserves in Liaoning Province continued to exhibit the characteristic spatial aggregation of higher values in the east and lower values in the west. Under the urban development scenario, carbon reserves decreased by 34.56 Tg C tons, representing a 2.45% decrease compared to 2020. Conversely, under the business-as-usual, cultivated land protection, and ecological protection scenarios, carbon reserves displayed a growing tendency, reaching 1449.35 Tg C, 1450.39 Tg C, and 1471.80 Tg C, respectively, with changes of 0.09%, 0.16% and 1.63% compared to 2020. The substantial increase in carbon reserves under the ecological protection scenario primarily stemmed from the significant expansion of woodland and other ecological land areas. In light of these findings, Liaoning Province may consider laying down and strictly executing spatial policies for ecological protection in future land projecting. The PLUS model and InVEST model can help curb the uncontrolled expansion of built-up land, facilitate the increment of ecological land areas, and with effect augment carbon reserves, thereby ensuring the achievement of the “double carbon” target of carbon peak and carbon neutralization. Full article