Search Results (1,822)

The rapid increase in population and economy, coupled with accelerated urbanization, is placing immense pressure on the water–energy–food (WEF) system. In this context, the water–energy–food nexus framework has emerged, recognizing the interdependencies and interactions among water, energy, and food systems, with the aim of optimizing resource management through cross-sectoral collaboration to promote sustainable development. Understanding the spatio-temporal differentiation patterns of the WEF nexus and elucidating the driving mechanisms behind changes in their coupling relationships is essential. This knowledge is crucial for ensuring the security of each subsystem and enhancing the overall sustainability of interconnected systems through coordinated efforts. To address these challenges, this study first established evaluation indicators for water, energy, and food security to quantify their levels and spatio-temporal dynamics. Subsequently, the degrees of coupling coordination within the WEF nexus were calculated. Finally, the WEF nexus’s spatial correlations were analyzed by using a spatial autocorrelation model. Spatial econometric models then identified key factors affecting its coordination. The results revealed significant spatial heterogeneity in water, energy, and food security across mainland China’s provinces. From 2002 to 2022, water security improved substantially in 87% of the provinces, while energy security began to improve in the eastern regions following a phase of high consumption. Food security saw significant enhancements, particularly in Inner Mongolia and the northeastern provinces. The overall coupling coordination of the WEF nexus improved across 30 provinces, progressing toward primary coordination. However, Henan and Anhui provinces experienced fluctuations in WEF nexus coordination. Spatial correlation analysis showed upward trends and increased clustering in WEF nexus coordination. Factors such as economic development and population positively influenced coordination, while economic agglomeration, education, and effective irrigation area had negative effects. This study elucidates the complex interconnections and key influencing factors within the WEF nexus, providing a reference framework and practical recommendations for equitable resource management. Full article

Rapid urbanization entails complex problems not only in cities, but also within urban agglomerations. In modern landscape science, the greatest problems are primarily related to the ecological state of urban ecosystems. In this context, the most important task of urbanism is the interdisciplinary study of urban infrastructure in relation to the well-being of inhabitants, with a focus on the sustainable development of urban agglomerations. The aim of this study is to conduct a theoretical analysis of interdisciplinary research on the interactions between humans and the urban environment in the context of intensive urbanization, as well as to be an empirical study of the relationship between the real ecological state of the city of Astana, based on the use of geographical, environmental, cartographic, statistical, sociological, and socio-psychological research methods, aimed at identifying the mental well-being of citizens in correlation with their consumed urban ecosystem services using an associative psychological experiment, socio-psychological survey, and GIS mapping. As a result of this study, the authors have determined that the research hypothesis 1 “Spatial representations of the city’s geoecological state are interrelated with the mental well-being and satisfaction with urban ecosystem services of citizens depending on the area of residence” is confirmed. Additionally, a positive correlation has been noted among the key indicators and criteria of geoecological condition, mental well-being, and satisfaction with urban ecosystem services across different districts of the city. Full article

The accurate extraction of urban residential space (URS) is of great significance for recognizing the spatial structure of urban function, understanding the complex urban operating system, and scientific allocation and management of urban resources. The traditional URS identification process is generally conducted through statistical analysis or a manual field survey. Currently, there are also superpixel segmentation and wavelet transform (WT) processes to extract urban spatial information, but these methods have shortcomings in extraction efficiency and accuracy. The superpixel wavelet fusion (SWF) method proposed in this paper is a convenient method to extract URS by integrating multi-source data such as Point of Interest (POI) data, Nighttime Light (NTL) data, LandScan (LDS) data, and High-resolution Image (HRI) data. This method fully considers the distribution law of image information in HRI and imparts the spatial information of URS into the WT so as to obtain the recognition results of URS based on multi-source data fusion under the perception of spatial structure. The steps of this study are as follows: Firstly, the SLIC algorithm is used to segment HRI in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration. Then, the discrete cosine wavelet transform (DCWT) is applied to POI–NTL, POI–LDS, and POI–NTL–LDS data sets, and the SWF is carried out based on different superpixel scale perspectives. Finally, the OSTU adaptive threshold algorithm is used to extract URS. The results show that the extraction accuracy of the NLT–POI data set is 81.52%, that of the LDS–POI data set is 77.70%, and that of the NLT–LDS–POI data set is 90.40%. The method proposed in this paper not only improves the accuracy of the extraction of URS, but also has good practical value for the optimal layout of residential space and regional planning of urban agglomerations. Full article

High-speed rail is a high-standard railway system, which allows trains to operate at high speed. The railway play a crucial role in connecting urban agglomerations, which represents the highest form of spatial organization in the mature stage of urban development, bringing together cities of various natures, types, and scales in specific regions. This paper explores the impacts of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in the period of 2000 to 2019. We use a well-known transportation policy as a natural experiment, utilizing geographic distance data to study the effects of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in urban agglomerations. The results show that high-speed rail increases industrial concentration but leads to a reduction in macroeconomic conditions. Unlike previous studies in this field, we use distance variables to analyze how the expansion of high-speed rail affects macroeconomic conditions and industrial concentration through location advantages. The impacts of high-speed rails vary across urban and non-urban agglomeration cities, resource-based and non-resource-based cities, large and small cities, and eastern, central, and western regions. Our results are robust to the shocks from the global financial crisis, time lags, different distance dummy variables, dependent variables, and endogeneity issues. This study regards the opening up of high-speed rail as both improving air quality and reducing carbon emissions through substituting for urban and aviation transport. Compared to traditional transport methods such as urban and air travel, the efficiency and environmental benefits of high-speed rail make it an important method for reducing greenhouse gas emissions. Consequently, the expansion of high-speed rail could support both economic development and environmental concerns, and it is playing a crucial role in transportation selection for advancing low-carbon economic goals. Full article

As a model of the symbiotic wisdom between humans and nature, traditional villages carry rich historical and cultural values in their existence. However, the rapid urbanization process has led to the destruction and even disappearance of many traditional villages, and surviving villages urgently need to cope with the severe challenge of protecting their original ecology and cultural environment. To preserve the heritage of traditional villages, it is necessary to investigate their geographic distribution and influencing factors. We have conducted research and statistics on traditional villages using Geographic Information System (GIS) spatial analysis technology (GIS), described in detail the complex interrelationships among natural, social, and cultural variables in the distribution and evolution of villages, and analyzed the relevant influencing factors qualitatively and quantitatively. The results of the research show that (1) in terms of geographical distribution, traditional villages in Guizhou tend to exhibit a high degree of agglomeration and clustering, and their distribution structure is characterized by “small aggregation and scattering, with many cores and few peripheries”. (2) Most traditional villages in Guizhou appeared after the end of the Qing Dynasty. (3) Natural and cultural factors influence the design and layout of traditional settlements, and socioeconomic and historical culture influence the evolution of traditional settlements. These factors also influence the formation of traditional villages and the changes in their geographical distribution. This study provides a scientific basis for the sustainable development of traditional villages in Guizhou Province. It explores a new way to study and protect the spatial patterns of traditional villages. Full article

Arable land loss has become a critical issue in China because of rapid urbanization, industrial expansion, and unsustainable agricultural practices. While previous studies have explored the factors contributing to this loss, they often fall short in addressing the challenges of spatial heterogeneity and large-scale dataset analysis. This research introduces an innovative approach to geographically weighted regression (GWR) for assessing arable land loss in China, effectively addressing these challenges. Focusing on Chongqing, Guizhou, and Yunnan Provinces over the past two decades, it examines spatial autocorrelation with R-squared values exceeding 0.6 and residuals. Eight factors, including environmental elements (rain, evaporation, slope, digital elevation model) and human activities (distance to city, distance to roads, population, GDP), were analyzed. By visualizing and analyzing R² spatial patterns, the results reveal a clear spatial agglomeration distribution, primarily in urban areas with industries, highly urbanized cities, and flat terrains near rivers, influenced by GDP, population, rain, and slope. The novelty of this study is that it significantly enhances GWR computational capabilities for handling extensive datasets by utilizing Compute Unified Device Architecture (CUDA) on a high-performance GPU cloud server. Simultaneously, it conducts comprehensive analyses of the GWR model’s local results through visualization and spatial autocorrelation tools, enhancing the interpretability of the GWR model. Through spatial clustering analysis of local results, this study enables targeted exploration of factors influencing arable land changes in various temporal and spatial dimensions while also evaluating the reliability of the model results. 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

Assuming that settlement morphologies and landscape structures are the result of economic transformations, the present study illustrates a statistical framework investigating metropolitan growth due to the inherent changes in landscape configurations vis à vis socio-demographic functions. Focusing on the evolution of their spatial drivers over time, metropolitan development was studied by adopting land parcels (or ‘patches’, as they are referred to in the ecological literature) as the elementary analysis unit—with the individual surface area and a specific shape indicator as the dependent variables and background socioeconomic attributes as predictors of landscape change over time. We specifically ran a Multiscale Geographically Weighted Regression (MGWR) testing the spatial dependence of the size and shape of landscape parcels on a vast ensemble of socioeconomic factors in a dense region (metropolitan Athens, Greece) with natural landscapes exposed to increasing human pressure. To investigate the spatial direction and intensity of the settlement expansion and landscape change, local regressions using the parcel area and fractal index (perimeter-to-area ratio) as the dependent variables and the elevation, distance from selected economic nodes, transport infrastructures, and natural amenities as the predictors were run separately for 1990 and 2018, representative of, respectively, a mono-centric configuration and a moderately polycentric organization of economic spaces. In a strictly mono-centric setting (1990), the parcel size showed a linear dependence on the distance from business districts, elevation, and wealth. Changes in the relationship between the parcel size and spatial (economic and non-economic) drivers may suggest a latent process of settlement de-concentration, and a possible shift toward polycentric development (2018), as documented in earlier studies. By integrating socioeconomic and ecological dimensions of landscape analysis and land evaluation, the empirical results of this study outline the increased complexity of dispersed landscape structures within dense metropolitan regions and along urban–rural gradients in Europe. Full article

The contradiction between ecological resource protection and urban sprawl in urban agglomeration areas is becoming more and more prominent, facing a serious imbalance between the supply and demand of ecosystem services. To analyze the impact of urban agglomeration expansion on regional ecosystem services, based on multi-source data, an assessment model of supply and demand of ecosystem services for water conservation, carbon sequestration, soil conservation and crop production was constructed. With the help of value transformation model and spatial analysis method, this paper explores the risk of ecosystem service supply and demand imbalance faced by the Yangtze River Delta urban agglomeration in the process of expansion. This study found that the supply capacity of ecosystem services in the YRDUA has continued to decline at the spatial pixel scale; ecosystem service value deficits are a common problem in the YRDUA, with cities around Taihu Lake, such as Shanghai and Suzhou, being the most serious; the value surplus areas are concentrated in the southern cities, such as Xuancheng and Chizhou, but the balance between the supply of and demand for ecosystem services in these cities is also facing a challenge as the cities are expanding. This study analyzed the spatial pattern changes in the Yangtze River Delta region in the context of urban sprawl from the perspective of ecosystem service supply and demand, which helps to clarify the changing ecosystem service dynamics of the region and guide the formulation of urban planning policies and to achieve a balance between ecological supply and demand as well as sustainable development. Full article

Economic development often results in significant greenhouse gas emissions, contributing to global climate change, which demands immediate attention. Despite implementing various low-carbon policies to promote sustainable economic and environmental progress, current evaluations reveal limitations and deficiencies. Therefore, this study utilizes a dataset detailing policy intensity at a prefecture-level city in China to investigate the impacts of these policies on carbon emission reduction from 2007 to 2022 in 334 prefecture-level cities, employing a fixed-effects model. Additionally, it assesses the policies’ efficacy. The findings indicate a significant negative correlation between China’s low-carbon policies and carbon emissions, supported robustly by multiple tests. Specifically, a one-unit increase in China’s policy intensity correlates with a 0.53-unit reduction in carbon emissions. Furthermore, the heterogeneity analysis shows that variations in urban agglomerations, environmental resource endowments, pollution levels, and low-carbon policy intensities influence the effectiveness of these policies in reducing carbon emissions. This analysis underscores that policy intensity achieves emission reductions through technological innovation, industrial transformation, welfare crowding out, and pollution transfer, with varying impacts across different environmental contexts, pollution levels, and policy intensities. Based on this analysis, we recommend several policies: formulating low-carbon strategies tailored to local conditions, enhancing regional low-carbon policies, establishing cross-regional coordination mechanisms, and so on. These recommendations not only offer valuable policy insights for China but also serve as useful references for the green and sustainable development of other developing countries. Full article

Forest change affects local and global climate by altering the physical properties of the land surface. Accurately assessing urban forest changes in local land surface temperature (LST) is a scientific and crucial strategy for mitigating regional climate change. Despite this, few studies have attempted to accurately characterize the spatial and temporal pattern of afforestation, reforestation, and deforestation to optimize their effects on surface temperature. We used the China Land Cover Dataset and knowledge criterion-based spatial analysis model to map urban forestation (e.g., afforestation and reforestation) and deforestation. We then analyzed the impacts of these activities on LST from 2010 to 2020 based on the moving window strategy and the spatial–temporal pattern change analysis method in the urban agglomerations of the Yangtze River Delta (YRD) and Pearl River Delta (PRD), China. The results showed that forest areas declined in both regions. Most years, the annual deforestation area is greater than the yearly afforestation areas. Afforestation and reforestation had cooling effects of −0.24 ± 0.19 °C and −0.47 ± 0.15 °C in YRD and −0.46 ± 0.10 °C and −0.86 ± 0.11 °C in PRD. Deforestation and conversion of afforestation to non-forests led to cooling effects in YRD and warming effects of 1.08 ± 0.08 °C and 0.43 ± 0.19 °C in PRD. The cooling effect of forests is more evident in PRD than in YRD, and it is predominantly caused by reforestation. Moreover, forests demonstrated a significant seasonal cooling effect, except for December in YRD. Two deforestation activities exhibited seasonal warming impacts in PRD, mainly induced by deforestation, while there were inconsistent effects in YRD. Overall, this study provides practical data and decision-making support for rational urban forest management and climate benefit maximization, empowering policymakers and urban planners to make informed decisions for the benefit of their communities. Full article

Green hydrogen production is expected to play a major role in the context of the shift towards sustainable energy stipulated in the Fit for 55 package. Green hydrogen and its derivatives have the capacity to act as effective energy storage vectors, while fuel cell-powered vehicles will foster net-zero emission mobility. This study evaluates the potential of green hydrogen production in Power-to-Gas (P2G) systems operated in former mining sites where sand and gravel aggregate has been extracted from lakes and rivers under wet conditions (below the water table). The potential of hydrogen production was assessed for the selected administrative unit in Poland, the West Pomerania province. Attention is given to the legal and organisational aspects of operating mining companies to identify the sites suitable for the installation of floating photovoltaic facilities by 2050. The method relies on the use of GIS tools, which utilise geospatial data to identify potential sites for investments. Basing on the geospatial model and considering technical and organisational constraints, the schedule was developed, showing the potential availability of the site over time. Knowing the surface area of the water reservoir, the installed power of the floating photovoltaic plant, and the production capacity of the power generation facility and electrolysers, the capacity of hydrogen production in the P2G system can be evaluated. It appears that by 2050 it should be feasible to produce green fuel in the P2G system to support a fleet of city buses for two of the largest urban agglomerations in the West Pomerania province. Simulations revealed that with a water coverage ratio increase and the planned growth of green hydrogen generation, it should be feasible to produce fuel for net-zero emission urban mobility systems to power 200 buses by 2030, 550 buses by 2040, and 900 buses by 2050 (for the bus models Maxi (40 seats) and Mega (60 seats)). The results of the research can significantly contribute to the development of projects focused on the production of green hydrogen in a decentralised system. The disclosure of potential and available locations over time can be compared with competitive solutions in terms of spatial planning, environmental and societal impact, and the economics of the undertaking. Full article

The rapid increase in population and economic activities has greatly influenced land use and spatial development. In urban agglomerations where socioeconomic activities are densely concentrated, the clash between ecological protection and economic growth is becoming more evident. Therefore, a thorough quantitative assessment of spatial changes driven by land use dynamics, alongside an examination of temporal and spatial driving factors, is crucial in offering scientific backing for the long-term and sustainable growth of urban agglomerations. This paper focuses on the major urban agglomerations in China’s Yangtze River Delta region, examining the spatiotemporal evolution of land use and landscape patterns from 2000 to 2020. By employing the standard deviation ellipse technique, coupled with multiple linear regression and the geographical detector model, we conduct a quantitative assessment of the directional trends in urban construction land expansion as well as the diverse impacts of temporal and spatial factors on this expansion across various periods and regions. The findings indicate that over the past 20 years, construction land in the Yangtze River Delta Urban Agglomeration expanded in concentrated patches, showing significant scale effects with relatively intact farmland and forest land being increasingly encroached upon. Landscape-type transitions predominantly occurred in cities around Taihu Lake and Hangzhou Bay, with the most significant transition being farmland converted to construction land, resulting in a greater number of patches and more pronounced land fragmentation. Throughout the 20 years, the standard deviation ellipse of construction land in the Yangtze River Delta Urban Agglomeration expanded and shifted, with the predominant expansion trending from the northwest toward the southeast, and the EN orientation being the most intense expansion area, covering 1641.24 km². The influence of temporal and spatial driving factors on the expansion of urban construction land differed across various periods and regions. This study thoroughly examines the driving factors that affect the evolution of urban construction land in the region, offering valuable scientific evidence and references for future planning and development of the Yangtze River Delta Urban Agglomeration, aiding in the formulation of more precise and efficient urban management and land use strategies. Full article

The high-quality development paradigm, which emphasizes the organic unity of efficiency, equity, and sustainability, has gained increasing global recognition as an extension of the concept of sustainable green development. In this study, we use green development efficiency as a metric of high-quality development and employ a three-stage Stacks-based Measure Model (SBM) in order to assess the true green development efficiency (GDE) levels of urban agglomerations in China’s Yellow River Basin (YRB) from 2011 to 2020. The results indicate that external environmental factors significantly impacted the green development efficiency levels of these urban agglomerations; after removing these factors, their green development efficiency shifted from trendless fluctuations to more consistent upward trends. Additionally, the disparities between different urban agglomerations are the primary sources of overall differences in green development efficiency in the YRB. Influenced by economic development levels and administrative divisions, the degree of internal development imbalance varies among urban agglomerations; however, regional disparities show a decreasing trend, indicating a catch-up effect. Based on these findings, we further propose relevant policy recommendations in this paper. The results of this study help us to understand the current status and trends of high-quality development in the urban agglomerations of the YRB, providing empirical evidence for policy formulation. Full article

China’s accelerating pace of urbanization has placed severe pressure on its ecosystems. Hence, the monitoring and assessment of eco-environmental quality has significant implications for sustainable urban development. By introducing a pollution index, a modified remote sensing ecological index (MRSEI) was constructed to more comprehensively evaluate the spatiotemporal distribution of the eco-environment quality in the middle reaches of the Yangtze River where urbanization has been developing rapidly. Future trends in eco-environmental quality were analyzed using Theil–Sen trend analysis, the Mann–Kendall test, and the Hurst exponent. Environmental influencing factors were also analyzed. Our results show that: (1) The impact of pollution factors on urban agglomerations cannot be overlooked. The MRSEI model introduces a pollution indicator to better assess the eco-environmental quality of urban agglomeration areas. (2) The eco-environmental quality is high in the south and east and low in the north and west, with overall levels ranging between moderate and good. (3) The eco-environmental quality remained stable, improved, and degraded in 86.3%, 3.1%, and 10.7% of the study area, respectively. (4) The land use and land cover type are directly related to the eco-environment. Climate factors indirectly affect the eco-environment. Human activities in cities and urban peripheries lead to land use changes and industrial pollution, which significantly affect environmental quality. Full article