Rapid Urbanization Process Research Articles

Analysing macroscopic traffic rhythms and city size in affluent cities: insights from a global panel data of 25 cities.

The world is undergoing a rapid process of urbanization. Currently, it is estimated that over 55% of the global population resides in urban areas, a figure projected to reach nearly 70% by 2050. This trend is accompanied by a spatial reorganization of human activities on a global scale, bringing about significant changes in mobility patterns and urban traffic management capabilities. Consequently, it is imperative to evaluate, on a broad scale, how city size influences traffic capacity. This study aims to analyse on-road traffic patterns using a diverse dataset comprising cities of varying population sizes, geographical extents and global locations. Specifically, we conduct an analysis encompassing 25 cities primarily situated in several European countries (France, Italy, Germany, Spain, Switzerland, and the United Kingdom), as well as in North America (Canada) and East Asia (Japan and Taiwan). Our findings shed light on how physical aspects related to urban form influence mobility patterns, offering insights for the implementation of more effective and sustainable traffic management policies.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Spatial heterogeneity analysis on distribution patterns and underlying determinants of historical rural settlements: a case study in Taihang Baxing

AbstractAs vital carriers of cultural heritage, rural areas are facing the threats of degradation and urbanization during rapid urbanization processes. In recent years, China has formulated and implemented a series of national policies, regulations, and heritage protection lists to safeguard and perpetuate the traditional patterns and historical features of rural heritage. However, these rural heritage listings exhibit significant macro-level distributional imbalances and generally lack consideration of regional characteristics. This study uses the Taihang Baxing (THBX) in China as a case study, initially employing historical local documents and maps as base data. It utilizes the stability in the evolution of Chinese characters to compare historical and contemporary village names, filtering out existing historical rural settlements (HRS) to construct a dataset. Further, a multi-scale geographically weighted regression (MGWR) model is applied to analysis the impacts of natural, economic, and social factors on the concentration of HRS (CHRS). The study reveals that the CHRS in the region is markedly characterized by clustering, with evident spatial heterogeneity in the impacts of various factors. Slope (SLP), total annual precipitation (TP), and potential crop yield (PCY) significantly influence the CHRS globally, while elevation (ELV), distance to ancient path (DAP) and surface runoff (DSR), gross domestic product (GDP), and road density (RD) have significant local impacts. This research offers a methodological framework for HRS data compilation and provides theoretical and methodological references for national and local levels of rural heritage protection, optimization of rural spatial patterns, prediction of rural evolution pathways, and implementation of China’s rural revitalization strategy.

Elite poems and mass proverbs: exploring the historic landscape in Nanchang City, China

The rapid process of urbanisation has led to the erosion of the preservation of features of urban landscape. Research on historical landscapes in ancient urban planning has predominantly concentrated on the elite class, neglecting the broader population. Nanchang, a city with a history spanning over two millennia of urban development, is the focus of this study. The study integrates elite poems and mass proverbs through GIS spatial matching and KH Coder word frequency analysis to research the historic landscape in Nanchang City. The research uncovers that the elite class focuses on the historical, literary, and aesthetic aspects of Nanchang, while the masses emphasise urban structure, functionality, and aspirations. These dual perspectives underscore Nanchang’s evolution from inception to formalisation, highlighting its ability to cater to diverse societal needs. The efforts on the distribution of landscape spots and strict modulus reflect the adaptability and sustainability of Nanchang City.

Spatial–Temporal Evolution and Driving Force Analysis of Blue–Green Space in the Chengdu–Chongqing Economic Circle, China

In the rapid process of urbanization, revealing the patterns and driving forces behind the evolution of blue–green spaces holds significant value for optimizing urban blue–green environments. This study systematically investigates the spatial–temporal evolution characteristics and driving forces of blue–green space in the Chengdu–Chongqing Economic Circle from 1990 to 2020, utilizing GIS technology, landscape pattern analysis, and geographic detectors. The research findings indicate the following: (1) The area of blue–green space in the study area exhibits a general trend of initial growth followed by decline, with significant changes occurring between 2010 and 2020. (2) The fragmentation degree of blue–green space is gradually increasing, while connectivity among landscapes is decreasing; however, there has been an increase in landscape distribution uniformity. More than 90% of blue–green spaces expanded mainly through adjacency patterns. (3) In examining driving forces, it was found that temperature, topographic relief, elevation, population density, and construction intensity are the primary driving factors. Notably, the influence of natural factors has diminished over time while human social factors have significantly intensified. This study offers solutions for optimizing the configuration of blue–green spaces within the Chengdu–Chongqing Economic Circle. It also serves as a reference case for promoting high-quality urbanization in developing countries undergoing rapid urbanization.

Urban and rural disparities in general hospital accessibility within a Chinese metropolis

Accessibility is one of the crucial criteria for measuring the ease of access to public services in a region. Given China’s historical rural–urban dualism and rapid urbanization process, there exist significant disparities in public services within metropolises. This study selects Nanjing as a representative metropolis and employs the Gaussian two-step floating catchment area method and an improved potential model to calculate the accessibility of comprehensive hospitals. Spatial autocorrelation and urban–rural disparities are analyzed, confirming spatial variations in healthcare service equity. The results show that: ①The spatial variability of accessibility to comprehensive hospitals is significant. The Gaussian two-step floating catchment method overestimates overall accessibility, and for Nanjing, the improved potential model with β = 1.5 proves more suitable. ②Accessibility exhibits pronounced clustering characteristics. Healthcare conditions for residents in the northern part of Liuhe District, eastern part of Qixia District, western part of Pukou District, peripheral areas of Jiangning District, eastern part of Gaochun District, and residents in Lishui District need improvement. ③Comprehensive healthcare services are relatively lacking in nearly 60% of rural areas. Our research findings provide valuable insights for improving spatial justice in public infrastructure in metropolises of developing countries.

How does new-type urbanization promote green development efficiency in China? The mediating role of governments, enterprises, and residents

New-type urbanization (NTU) is proposed by China to solve unsustainable issues and improve green development efficiency (GDE) during the process of rapid urbanization. However, the impact mechanism of NTU on GDE is unclear. Using panel data of 282 prefecture-level cities in China from 2010 to 2019, we measured NTU and GDE to describe their spatiotemporal pattern and relationship evolution. The fixed effects panel model and mediating effect panel model were further utilized to analyze the benchmark impact, mediating mechanism and spatiotemporal heterogeneity of NTU on GDE. The results showed that NTU improved whose level in eastern region was the highest, while GDE increased in fluctuations whose level in eastern and western regions performed better. With the proportion of double-high cities increasing from 13.83% to 43.62%, the NTU-GDE relationship was upgraded. Overall, every 1% improvement in NTU increased GDE by 0.3111%, and the enterprise effect, resident effect and government effect played a positive mediating role from high to low. During the later stage of NTU, it improved GDE more strongly and the mediating role of governments was optimized. The eastern region was the only region with three positive mediating roles of governments, enterprises and residents. These findings will facilitate GDE through NTU in China and have reference significance for the sustainability of global urbanization.

Study on the spatial distribution characteristics of traditional villages and their response to the water network system in the lower yangtze river basin

Traditional villages hold significant historical and cultural value as the precious heritage of China’s agricultural civilization. Currently, against the backdrop of increasing urbanization and rapid expansion of urban construction land, the spatial patterns of traditional villages across various regions in China are being encroached upon and damaged, with protection pressures growing daily. As one of the important cradles of Chinese civilization, the Lower Yangtze River Basin (LYRB) has traditional villages closely linked with its water systems, forming a unique human-land relationship and spatial distribution pattern. However, influenced by the rapid urbanization process, the spatial patterns of traditional villages in this region also face a crisis, and the contradiction between protection and development is becoming increasingly prominent. How to balance this contradiction and ensure the reasonable protection and sustainable development of traditional villages has become an urgent issue to address. Therefore, this study focuses on the LYRB. Using ArcGIS tools and combined with mathematical analysis methods, the spatial distribution characteristics and essential influencing factors of traditional villages in this area were screened and analyzed. The objective was to examine the spatial structural relationship between traditional villages, four water system types, and nine sub-basin units, intending to reveal the unique interdependence between the water system and traditional villages in this area. This would provide scientific support for the formulation of scientific conservation strategies. The research results show that: (1) Traditional villages in The LYRB form two core clusters spatially and exhibit substantial spatial accumulation; (2) Water system characteristics are the main factors affecting the distribution of traditional villages; (3) In the LYRB, the spatial distribution of the nine sub-basins is closely related to the spatial distribution of traditional villages, resulting in typical regional spatial differentiation of traditional villages in this area. This study is based on a watershed perspective, and the results highlight the importance of the water system network in the development of traditional villages, revealing a unique spatial dependency relationship between traditional villages and the water network in the LYRB. In order to ensure the comprehensive protection of the traditional village system in this region, it is essential to adhere to the fundamental principles that govern its spatial configuration. A tripartite collaborative protection system based on the watershed should be formulated from the perspective of the overall distribution relationship between the water network and the traditional villages. This system would serve to protect the overall landscape, the water network pattern, and the traditional villages. Establishing an overall pattern view of integrating the water system network and the traditional villages is essential.

Promoting Mental Health of City Residents: Stress Management and The Role of Salutogenic Design

Introduction. Salutogenic, or health-promoting design, suggests that the designed environment should not only provide comfortable living space but also support the health and well-being of individuals. However, the rapid process of urbanization is accompanied by significant changes in people's lifestyles and negatively affects mental health. Thus, it is necessary to study the impact of urban environment on the citizens mental health, as well as to summarize and analyze technologies of health-promoting design in urban environment. Objective. To justify the problem of high prevalence of chronic stress among citizens and to summarize the best practices of applying the principles of salutogenic design in the urban environment to overcome stress and prevent psychological problems. Materials and methods. We conducted a non-systematic narrative literature review in the following databases: PubMed, Google Scholar, eLibrary.ru. Search request depth covered 20 years from 2003 to 2023. Results. Urban planning based on the principles of salutogenic design is one of the important tools for ensuring the health of citizens, extending beyond the scope of healthcare system. Moreover, addressing chronic stress, referred to as the «epidemic of the 21st century», can be considered a key direction in implementing salutogenic design in urban planning. The main focus areas of salutogenic design in the urban environment are regulating the density of urban development, creating public spaces, providing landscape design and greenery, offering convenient and safe urban navigation and using arts. Conclusions. Stress levels in cities are influenced by various factors. Effective urban planning that incorporates salutogenic design principles can contribute to improving public health and creating a supportive urban environment.

Remote Sensing Monitoring and Multidimensional Impact Factor Analysis of Urban Heat Island Effect in Zhengzhou City

In the 21st century, the rapid urbanization process has led to increasingly severe urban heat island effects and other urban thermal environment issues, posing significant challenges to urban planning and environmental management. This study focuses on Zhengzhou, China, utilizing Landsat remote sensing imagery data from five key years between 2000 and 2020. By applying atmospheric correction methods, we accurately retrieved the land surface temperature (LST). The study employed a gravity center migration model to track the spatial changes of heat island patches and used the geographical detector method to quantitatively analyze the combined impact of surface characteristics, meteorological conditions, and socio-economic factors on the urban heat island effect. Results show that the LST in Zhengzhou exhibits a fluctuating growth trend, closely related to the expansion of built-up areas and urban planning. High-temperature zones are mainly concentrated in built-up areas, while low-temperature zones are primarily found in areas covered by water bodies and vegetation. Notably, the Normalized Difference Built-up Index (NDBI) and the Normalized Difference Vegetation Index (NDVI) are the two most significant factors influencing the spatial distribution of land surface temperature, with explanatory power reaching 42.7% and 41.3%, respectively. As urban development enters a stable stage, government environmental management measures have played a positive role in mitigating the urban heat island effect. This study not only provides a scientific basis for understanding the spatiotemporal changes in land surface temperature in Zhengzhou but also offers new technical support for urban planning and management, helping to alleviate the urban heat island effect and improve the living environment quality for urban residents.

Sensing noise exposure and its inequality based on noise complaint data through vision-language hybrid method

This study seeks to reveal urban noise exposure patterns and inequalities using noise complaint data and vision-language hybrid method. By applying a natural language processing model to 17,243 noise complaint records, we uncovered distinct patterns of traffic, industrial, and living noise exposures across residential communities. Our analysis of street view images near complaint locations, utilizing a Residual Network (ResNet) model and Class Activation Mapping (CAM), identified the key environmental elements of different noise sources. Notably, our assessment of noise exposure inequality across 9791 communities yielded a counterintuitive finding: contrary to previous studies in Western contexts, rich communities in China experience higher and more unequal noise exposure compared to average communities, with Gini coefficients exceeding 0.8. This unexpected result likely stems from China's unique rapid urbanization process. Our use of crowdsourced complaint data aligns more closely with human subjective perceptions of noise, offering a novel perspective on noise exposure inequality. These findings challenge existing assumptions about the relationship between socioeconomic status and environmental quality in urban China, and have significant implications for urban planning and noise management strategies in rapidly developing cities.

Application of Deep Learning for Automatic Identification of Hazardous Materials and Urban Safety Supervision

The rapid process of urbanization and industrial development has raised significant concerns regarding the presence and management of hazardous substances. However, conventional methods employed for identifying hazardous substances and monitoring urban safety often suffer from low efficiency and accuracy. This paper proposes a novel approach that combines deep learning and genetic algorithms, which utilizes the Bidirectional Long Short-Term Memory model to capture temporal features in hazardous substance data and introduces the Attention Mechanism for weighted processing of crucial information, thereby improving recognition capability. Genetic Algorithms are employed to optimize the performance and generalization capacity of the deep learning model. Experimental validation demonstrates that the proposed approach achieves higher accuracy and faster processing speed, effectively enhancing urban safety monitoring. This research holds practical implications for urban safety management and accident prevention, offering an innovative solution to guarantee urban safety.

The Spatiotemporal Characteristics and Mechanism of Rural Spatial Shrinkage in Local County, Southeast China

The rapid urbanization process has brought about the shrinkage of rural space as a typical issue. Nevertheless, due to the dearth of effective assessment approaches, the patterns of rural spatial shrinkage remain poorly grasped. This study intends to establish a quantitative assessment model to scientifically disclose the spatiotemporal characteristics and mechanisms of rural spatial shrinkage. The “Population-Industry-Function-Land” (PIFL) assessment model has been rigorously constructed, encompassing eight assessment indices, such as the ratio of permanent residents, rural population density, and the rate of abandoned cultivated land. The model was adopted to conduct an analysis of the spatial shrinkage scenarios of the 18 administrative villages in Panxi Town spanning from 2011 to 2021. The results indicate that the temporal dimension of rural spatial shrinkage exhibits an accelerating trend, with discernible declines or increases in the ratio of permanent residents, rate of the elderly labor force, and housing vacancy rate. The shrinkage of rural spaces displays spatial heterogeneity, with more pronounced shrinkage characteristics observed in villages located further from the central town. According to the comprehensive shrinkage index, the villages are categorized into four types: relative shrinkage (0.2447 ≤ Z ≤ 0.2462), mild shrinkage (0.2463 ≤ Z ≤ 0.4423), moderate shrinkage (0.4424 ≤ Z ≤ 0.6125), and severe shrinkage (0.6126 ≤ Z ≤ 0.7988). The research findings possess significant reference value for the governance of rural spatial shrinkage.

A Robustness Study on Early Fire Image Recognitions

With the advancement of society and the rapid urbanization process, there is an escalating need for effective fire detection systems. This study endeavors to bolster the efficacy and dependability of fire detection systems in intricate settings by refining the existing You Only Look Once version 5 (YOLOv5) algorithm and introducing algorithms grounded on fire characteristics. Primarily, the Convolutional Block Attention Module (CBAM) attention mechanism is introduced to steer the model towards substantial features, thereby amplifying detection precision. Subsequently, a multi-scale feature fusion network, employing the Adaptive Spatial Feature Fusion Module (ASFF), is embraced to proficiently amalgamate feature information from various scales, thereby enhancing the model’s comprehension of image content and subsequently fortifying detection resilience. Moreover, refining the loss function and integrating a larger detection head further fortify the model’s capability to discern diminutive targets. Experimental findings illustrate that the refined YOLOv5 algorithm attains accuracy advancements of 8% and 8.2% on standard and small target datasets, respectively. To ascertain the practical viability of the refined YOLOv5 algorithm, this study introduces a temperature-based flame detection algorithm. By amalgamating and deploying both algorithms, the ultimate experimental outcomes reveal that the integrated algorithm not only elevates accuracy but also achieves a frame rate of 57 frames, aligning with the prerequisites for practical deployment.

Optimizing Solar Power Generation in Urban Industrial Blocks: The Impact of Block Typology and PV Material Performance

The block-scale application of photovoltaic technology in cities is becoming a viable solution for renewable energy utilization. The rapid urbanization process has provided urban buildings with a colossal development potential for solar energy in China, especially in industrial areas that provide more space for the integration of PV equipment. In developing solar energy resources, the block layout and the PV materials are two critical factors affecting the distribution of solar radiation and generation. However, few studies have analyzed how to select the most suitable PV materials for different layouts of industrial blocks to obtain the best generation. This study considered the layout of industrial blocks and PV materials simultaneously, and the generation yield was calculated when combined. A total of 40 real industrial block cases were constructed, and radiation distribution data on building surfaces of different block cases were calculated. Data on both were combined to calculate the generation of different PV materials for each block type. The findings indicated that single-story industrial blocks possessed the highest potential for solar radiation, primarily due to the higher percentage of roof area. The influence of PV materials on the installation rate of different building facades varied, with the installation rate of the west facade being the most impacted by PV performance and the roof being the least impacted. Using different PV materials in industrial blocks could lead to a 59.2% difference in solar generation capacity. For single-layer industrial blocks, mono crystalline and poly crystalline silicon were preferable to achieve higher power generation. In contrast, multi-story and high-rise industrial blocks were best suited for a-Si and CIGS to attain higher cost performance. The methods and results of this study guided the selection and installation of PV equipment in various block typologies, thereby improving the refinement of solar resource development, maximizing solar resource utilization, and promoting the development of energy conservation and carbon reduction in cities.

Drivers of autochthonous malaria cases over time: could the Central European present the African future?

BackgroundResults of spatial and temporal comparison of malaria hotspots and coldspots could improve the health measures of malaria control and eradication strategies. The study aimed to reveal the spatially and temporally independent correlations between the potentially most effective background variables and the number of autochthonous malaria cases.MethodsRelationships between malaria cases and background variables were studied in 2 km × 2 km sized quadrates (10 Central European and 10 African). In addition to the current habitat structure of the African sites, annual precipitation, and annual mean temperature, data of the above parameters detected in the nineteenth and twentieth centuries and currently in the Central European sites were included in the analyses (n = 40). Mann–Whitney tests, Principal Component Analysis, and Generalized Linear Models were used for the examinations.ResultsIn addition to the apparent significant positive correlation of malaria cases with annual rainfall and mean temperature, several correlations were found for habitat parameters. The cover of marshlands in the 19th-century habitat structure of Central European quadrates was considerably the same as in the recent African ones. The extent of rural residential areas was significantly smaller in the 19th-century habitat structure of Central European quadrats than in present-day African ones. According to the revealed correlations, the surface cover of rural residential areas is the main driver of the number of autochthonous malaria cases that we can directly impact.ConclusionsThe study confirmed with historical comparison that not only the annual rainfall and mean temperature, the cover of marshlands and other habitats with breeding sites, but also the elements of the rural human environment play a significant role in the high number of autochthonous malaria cases, probably through the concentration and enhancing sites for vector mosquitoes. The latter confirms that a rapid urbanization process could reduce malaria cases in the most infected areas of Africa. Until the latter happens, extensive biological control of Anopheles larvae and chemical control (both outdoor and indoor) of their imagoes, further mosquito nets, repellents, and carbon dioxide traps will need to be applied more widely in the most heavily infested areas.

An empirical analysis of the coupling and coordinated development of new urbanization and ecological welfare performance in China’s Chengdu–Chongqing economic circle

New urbanization (NU) and ecological welfare performance (EWP) play pivotal roles in achieving sustainable urban development, with both emphasizing social equity and environmental management. Exploring the coordinated relationship between EWP and NU is invaluable for understanding the symbiotic interplay between humans and nature. We constructed a framework to elucidate the coupling mechanism of EWP and NU from the perspective of systems theory. We quantified the levels of NU and EWP utilizing the entropy weighting method and the super-efficient SBM method, respectively. Furthermore, we assessed the degree of coupling coordination between the two using the coupling coordination degree model (CCDM). Spatial and temporal evolution analysis was conducted, and factors influencing the degree of coupling coordination between EWP and NU were explored through a spatial–temporal geographically-weighted regression model (GTWR). The results indicate: (1) During the study period, the average annual increase in EWP in the study area was 2.59%, with a narrowing relative gap between cities. Conversely, the average annual increase in the level of NU was 7.6%, with demographic and economic dimensions carrying the highest weights. (2) The type of coupling coordination between EWP and NU transitions from basic coordination to moderate coordination, with the development of EWP lagging behind that of NU. (3) City size demonstrates a positive yet diminishing trend on the coupling coordination level, with economic development exerting the greatest influence and exhibiting a "V" trend, while the impact of green technology innovation diminishes negatively. Additionally, regional disparities are significant, with city size exhibiting a negative impact in areas of high population density and low economic levels, and green technology innovation showing notable polarization characteristics in core cities. These findings serve as a foundation for fostering coordinated ecological development amid the rapid urbanization process of the Chengdu–Chongqing Economic Circle.

Urban Texture Identification and Characteristic Analysis Based on Percolation Theory—A Case Study of the Second Ring Road Area in Wuhan City

The urban texture is the physical manifestation of the urban form’s evolution. In the rapid process of urbanization, protecting and reshaping the urban texture has become an essential means to sustain the overall form and vitality of cities. Previous studies in this field have primarily relied on image analysis or typological methods, lacking a quantitative approach to identify and analyze the urban texture on a large scale. Moreover, the hierarchical structure and networked organization of the urban texture are gradually being elucidated and emphasized. This study takes a complex network perspective and applies percolation theory to identify and analyze the urban texture. The hierarchical evolutionary characteristics of the urban fabric and the underlying mechanisms driving the scale-dependent differences are analyzed, and the toughness of the urban texture is evaluated based on hierarchical connections. The research findings reveal the key scale in the cross-scale evolution of urban textures, with variations in scale dependence and hierarchical evolution characteristics among different types of urban texture. The traditional urban texture displays sensitivity to scale changes, maintaining its integrity and internal connectivity at small scales. On the other hand, the texture characteristics of modern and contemporary urban areas are only discernible at larger scales. The emergence of large-scale texture clusters at specific scale levels can be explained using multiple index systems. This study has reference significance for the preservation and renewal of the urban fabric in urban renewal processes.

The Association between Rapid Urbanization Process and Mangrove Land Use Changes in Coastal Regions of Mainland China: A ten-years Systematic Review

Objective: This research aims to summarize the impacts on mangroves in mainland China due to changes in land use patterns in the context of rapid urbanization. Theoretical Framework: Grounded in theories of urbanization, land use change, and ecosystem dynamics, this research adopts a theoretical framework that integrates concepts from geography, ecology, and urban studies. It explores the complex interactions between urban development and mangrove ecosystems, considering factors such as population growth, economic development, and policy interventions. Method: The systematic literature review method used in this study follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. From 359 papers, 14 were selected for review and summary based on sources and identification, inclusion and exclusion criteria, screening, and data extraction. Results and Discussion: We realize that development activities that land use, such as land reclamation and port construction, pose the most significant threat to mangroves, often leading to irreversible damage. In addition to the obvious destruction, the covert and sustained impacts of urban development on mangrove forests have been receiving increasing attention. To address the negative impact of substantial demand for construction land, the establishment of protected areas at different levels has been proven to be indeed effective. However, the sustainable development of management and service functions within protected areas requires further research. Research Implications: Understanding the specific impacts of the urbanization process on mangrove forests is crucial for mangrove restoration efforts and for formulating and adjusting urban development-related plans and policies. Originality/Value: This study assesses urbanization impacts on mangroves, detailing loss reasons and distinguishing explicit and implicit effects of construction. It evaluates protective measures and discusses tailored conservation strategies for sustainable mangrove management.

Resilient city plans as important aspect of future development plans of Indian cities

While in developed countries urbanisation has mainly taken place in the second half of the 19th century, developing countries are in the middle of their urban growth now. The other major issue of Climate change is now a current reality. Three major movements are coming together: urbanization, decentralization, and the rise of domestic capital markets. The rapid process of urbanisation and the growing number of the megacities, cause a lot of different ecological, economical and social problems and risks. This impacts cause challenges for urban policies and urban planning strategies to manage the development in a sustainable way, when the population in some cities doubles every 10 to 15 years. As the numerous national and international conferences on urbanisation and megacities show, there is an obvious need for more and better urban development strategies, long term land policy and forceful urban management.

Exploring the relationship between land use change patterns and variation in environmental factors within urban agglomeration

Sustainable Development Goal (SDG) 11 aims to promote a more livable urban environment for humanity. However, the rapid global urbanization process has exerted significant pressure on urban environment, posing challenges for many cities to achieve this target. The urbanization process within urban agglomeration is accompanied by rapid and diverse land use change. Exploring the relationship between land use change and environmental factors is crucial for achieving sustainable urban development. To address this issue, this study investigates the interactive relationship between pixel-scale land use change and environmental indicators (CO2, Land Surface Temperature, and PM2.5) in China's three major urban agglomerations from 2000 to 2020. This study aims to analyze major land use change patterns, explore intrinsic connections among environmental indicators, and assess the impact of land use change on these indicators. The findings show that cropland, forestland, and built-up land are the major types of land change in all three urban agglomerations. Regions characterized by high population density, heavy industry, and intense transportation exhibit more pollutant emissions. Rapid urban construction has resulted in different types of environmental degradation issues. This study provides a comprehensive examination of the relationship between urbanization and environmental issues.