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1
Li, Qiang, Xin Yuan, Meng Zhang, Weiwei Xu, Liming Huo e Qingkai Mu. "A modified agglomeration kernel model used for particle agglomeration". Advanced Powder Technology 33, n. 1 (gennaio 2022): 103349. http://dx.doi.org/10.1016/j.apt.2021.11.001.
2
Cronin, Kevin, e Francisco Javier Gutiérrez Ortiz. "The Evolution of Variance and Entropy of the Granule Size Distribution in Fluidized Bed Agglomeration". Processes 11, n. 8 (26 luglio 2023): 2247. http://dx.doi.org/10.3390/pr11082247.
Abstract (sommario):
The evolution of the variance and entropy of granule size in the fluidized bed agglomeration process using two different aggregation kernels is examined. The first is a constant kernel (aggregation is independent of both time and granule size) and permits the most unconstrained agglomeration process that can occur where granules in any size class (up to a maximum size) can be formed at any point in time. This gives the fastest and largest increase in the variance and entropy of the resulting granule size distribution. The second kernel is a mechanistic kernel including a granule growth-limiting mechanism, in this case implemented by the consideration that not all collisions result in coalescence. This markedly changes the evolution of the variance and entropy of the distribution and reduces both significantly. Quantifying the entropy of the distribution provides another perspective on the change in the size distribution in an agglomeration process. It is shown that entropy can provide a better measure of size evolution than variance in that it represents the changing shape of the distribution more closely.
3
Liu, Zhonglan, e Yuanyuan Bao. "Spatial and Temporal Divergence of Water Resource Carrying Capacity in Hubei Province, China, from the Perspective of Three Major Urban Agglomerations". Sustainability 16, n. 12 (14 giugno 2024): 5059. http://dx.doi.org/10.3390/su16125059.
Abstract (sommario):
Water resource carrying capacity is indispensable for sustainable development, acting as a crucial determinant for harmonizing ecological preservation with socio-economic development. This study centers on Hubei Province, which is an important water conservation area in the Yangtze River Basin and is one of the core water source areas for the South-to-North Water Diversion Project, and evaluates the water resource carrying capacity of the three major urban agglomerations in Hubei Province from 2005 to 2020 based on the four dimensions of water resources, economics, society, and ecology, using the entropy weighting method and the TOPSIS model to construct an evaluation index system. We then employ the kernel density estimation method, ArcGIS visualization, and the Dagum Gini coefficient method to perform a comprehensive analysis of spatial and temporal differences, dynamic evolution, and contribution sources. The results show that (1) the water resource carrying capacity of Hubei Province as a whole increased from a severe overload to overload level during the study period. The water resource carrying capacity of the three major urban agglomerations shows a regional distribution pattern where the Yi-Jing-Jing-En agglomeration’s capacity surpasses that of the Wuhan urban agglomeration, which is bigger than Xiang-Shi-Sui-Shen urban agglomeration. A lower ecological water use rate primarily constrains the enhancement of the carrying capacity of water resources in Hubei Province. (2) The kernel density estimation reveals an increase in the overall water resource carrying capacity across Hubei Province’s three major urban agglomerations during the study period, alongside a pronounced trend towards polarization. (3) While the overall Gini coefficient, indicating an imbalance in water resource carrying capacity in Hubei Province, remains high, it demonstrates a declining trend, suggesting a growing disparity in water resource carrying capacity across the province’s three major urban agglomerations. Hubei Province’s water resource carrying capacity faces challenges of an overall imbalance and localized vulnerability. Strategies should aim to enhance synergy, address these deficiencies directly, and devise targeted measures tailored to the distinct features of various urban clusters.
4
Lu, Hao, e Jie Bao. "Spatial Differentiation Effect of Rural Logistics in Urban Agglomerations in China Based on the Fuzzy Neural Network". Sustainability 14, n. 15 (28 luglio 2022): 9268. http://dx.doi.org/10.3390/su14159268.
Abstract (sommario):
Rural logistics is particularly important for the sustainable development of Chinese urban agglomeration, which features the coexistence of urban circles and vast countryside. However, the existing literature generally focuses on urban logistics while ignoring rural logistics. Taking the Chengdu-Chongqing agglomeration as an example, this study constructed a rural logistics index system and proposed a new dynamic assessment model for rural logistics development using a fuzzy neural network, Moran index, and Kernel density estimation. The results are as follows: the development of rural logistics has been enhanced, and gaps among cities have gradually narrowed over the past decade. In particular, the spatial distribution of rural logistics showcases a dual-core structure in the Chengdu-Chongqing agglomeration, which is different from the unipolar structure manifested in other urban agglomerations. Because of administrative barriers, the impact from the dual-core cities is very different: Chengdu has a significant spillover effect on its surrounding cities, which is not the case for Chongqing. The findings are of great significance for local governments to provide decision-making support for the sustainable development of urban agglomerations.
5
Wang, Yi. "The Spatiotemporal Evolution and Influencing Factors of Urban Economic Resilience in the Yangtze River Delta Urban Agglomeration". Frontiers in Business, Economics and Management 5, n. 3 (19 ottobre 2022): 293–300. http://dx.doi.org/10.54097/fbem.v5i3.2039.
Abstract (sommario):
Urban agglomerations are the highest form of spatial organization in the mature stage of urban development, and will be impacted by external risks during the development process. How to enhance the urban economic resilience of urban agglomerations plays an important role in the sustainable development of urban agglomerations. Based on resilience theory and taking the Yangtze River Delta urban agglomeration as the research object, this paper explores the spatiotemporal characteristics, influencing factors and predictions of urban economic resilience in the future. The study found: (1) Based on the kernel density estimation, the economic resilience of the Yangtze River Delta urban agglomeration has significant spatial non-equilibrium characteristics; (2) Based on the correlation analysis, the degree of industrial structure optimization, government financial support, degree of opening to the outside world, innovation investment, Financial development level, urbanization level and ecological level are positively correlated with urban economic resilience; based on principal component analysis, government financial support is a key factor affecting urban economic resilience, with a weight of 17%; (3) Based on the grayscale prediction model, GM(1,1) can better fit the overall urban economic resilience of the Yangtze River Delta urban agglomeration from 2011 to 2020, and the overall urban economic resilience of the Yangtze River Delta urban agglomeration is at a high level from 2021 to 2025, but there is a downward trend . This research has important guiding significance for understanding the urban economic resilience of urban agglomerations and how to improve the urban economic resilience of urban agglomerations and promote regional coordinated development.
6
Golovin, Ievgen, Gerd Strenzke, Robert Dürr, Stefan Palis, Andreas Bück, Evangelos Tsotsas e Achim Kienle. "Parameter Identification For Continuous Fluidized Bed Spray Agglomeration". Processes 6, n. 12 (30 novembre 2018): 246. http://dx.doi.org/10.3390/pr6120246.
Abstract (sommario):
Agglomeration represents an important particle formation process used in many industries. One particularly attractive process setup is continuous fluidized bed spray agglomeration, which features good mixing as well as high heat and mass transfer on the one hand and constant product throughput with constant quality as well as high flow rates compared to batch mode on the other hand. Particle properties such as agglomerate size or porosity significantly affect overall product properties such as re-hydration behavior and dissolubility. These can be influenced by different operating parameters. In this manuscript, a population balance model for a continuous fluidized bed spray agglomeration is presented and adapted to experimental data. Focus is on the description of the dynamic behavior in continuous operation mode in a certain neighborhood around steady-state. Different kernel candidates are evaluated and it is shown that none of the kernels are able to match the first six minutes with time independent parameters. Afterwards, a good fit can be obtained, where the Brownian and the volume independent kernel models match best with the experimental data. Model fit is improved for identification on a shifted time domain neglecting the initial start-up phase. Here, model identifiability is shown and parameter confidence intervals are computed via parametric bootstrap.
7
Otto, Eric, Anton Maksakov, Robert Diirr, Stefan Palis e Achim Kienle. "Direct Discretized Kernel Identification for Continuous Agglomeration Processes". IFAC-PapersOnLine 55, n. 7 (2022): 260–65. http://dx.doi.org/10.1016/j.ifacol.2022.07.454.
8
Zhong, Yang, Aiwen Lin, Chiwei Xiao e Zhigao Zhou. "Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data". Remote Sensing 13, n. 6 (17 marzo 2021): 1150. http://dx.doi.org/10.3390/rs13061150.
Abstract (sommario):
In this paper, based on electrical power consumption (EPC) data extracted from DMSP/OLS night light data, we select three national-level urban agglomerations in China’s Yangtze River Economic Belt(YREB), includes Yangtze River Delta urban agglomerations(YRDUA), urban agglomeration in the middle reaches of the Yangtze River(UAMRYR), and Chengdu-Chongqing urban agglomeration(CCUA) as the research objects. In addition, the coefficient of variation (CV), kernel density analysis, cold hot spot analysis, trend analysis, standard deviation ellipse and Moran’s I Index were used to analyze the Spatio-temporal Dynamic Evolution Characteristics of EPC in the three urban agglomerations of the YREB. In addition, we also use geographically weighted regression (GWR) model and random forest algorithm to analyze the influencing factors of EPC in the three major urban agglomerations in YREB. The results of this study show that from 1992 to 2013, the CV of the EPC in the three urban agglomerations of YREB has been declining at the overall level. At the same time, the highest EPC value is in YRDUA, followed by UAMRYR and CCUA. In addition, with the increase of time, the high-value areas of EPC hot spots are basically distributed in YRDUA. The standard deviation ellipses of the EPC of the three urban agglomerations of YREB clearly show the characteristics of “east-west” spatial distribution. With the increase of time, the correlations and the agglomeration of the EPC in the three urban agglomerations of the YREB were both become more and more obvious. In terms of influencing factor analysis, by using GWR model, we found that the five influencing factors we selected basically have a positive impact on the EPC of the YREB. By using the Random forest algorithm, we found that the three main influencing factors of EPC in the three major urban agglomerations in the YREB are the proportion of secondary industry in GDP, Per capita disposable income of urban residents, and Urbanization rate.
9
Moseley, James L. "The discrete agglomeration model with a time-varying kernel". Nonlinear Analysis: Real World Applications 8, n. 2 (aprile 2007): 405–23. http://dx.doi.org/10.1016/j.nonrwa.2005.12.001.
10
Liu, Fei, Genyu Zhang, Chenghao Li, Tao Ren e Donato Masi. "Analysis of the Temporal and Spatial Pattern and Convergence Characteristics of High-Quality Sustainable Economic Development of Urban Agglomeration". Sustainability 15, n. 20 (12 ottobre 2023): 14807. http://dx.doi.org/10.3390/su152014807.
Abstract (sommario):
Based on the sample data of 149 cities in ten major urban agglomerations from 2004 to 2019, the entropy method, Dagum Gini coefficient, and three-dimensional kernel density estimation method are used to calculate and describe the spatial pattern of the high-quality, sustainable economic development of these ten major urban agglomerations. We then use the spatial econometric model to estimate the β convergence trend within the urban agglomerations and among the urban agglomerations at different levels. Our main findings include the following: First, the urban agglomeration tends to develop a high-quality economy, but the gap between the urban agglomerations can be large. Second, although the gap within the overall group of urban agglomerations is expanding, the gap between high-quality individuals and the average is constantly shrinking; the gap between groups is still the leading cause of the spatial gap, with a contribution rate of 70.51%. Third, all urban agglomerations have an absolute and conditional β convergence trend, and the convergence speed presents the characteristics of “high level slow, low level fast”. Government intervention, financial development, urbanization, and human capital contribute to the high-quality, sustainable economic development of each urban agglomeration. There is a heterogeneous influence; there is also absolute and conditional β convergence among urban agglomerations at all levels, and the convergence rate presents a gradient characteristic of “third level > second level > first level”, and by balancing the financial relationships between city groups within each level, development differences can promote the dynamic coordination of high-quality, sustainable economic development rates.
11
Liu, Song, Ying Liu, Rongrong Zhang, Yongwang Cao, Ming Li, Bahram Zikirya e Chunshan Zhou. "Heterogeneity of Spatial Distribution and Factors Influencing Unattended Locker Points in Guangzhou, China: The Case of Hive Box". ISPRS International Journal of Geo-Information 10, n. 6 (14 giugno 2021): 409. http://dx.doi.org/10.3390/ijgi10060409.
Abstract (sommario):
Hive Box is a company that operates a network of express unattended collection and delivery points (UCDPs) in China. Hive Box distribution enhances community-based end-to-end delivery services and low-carbon city logistics. It is argued that UCDPs compared with attended collection and delivery points (ACDPs) should be considered for further investigation. Therefore, the present study employed kernel density estimation, spatial autocorrelation analysis, and geographically weighted regression to investigate the spatial heterogeneity of Hive Box distribution across Guangzhou. Hive Box location data were collected from smartphone apps. The results were as follows: (1) the kernel density declined from the city center toward the outskirts, and showed point-like spatial agglomerations in the city center; (2) the Moran’s I index analysis showed that Hive Box distribution exhibited spatial agglomeration from a global perspective and geographic variations in locality in space; the heterogeneity of urban–rural differences implies the uneven development of Hive Box distribution in Guangzhou; and (3) the factors influencing Hive Box distribution were multilevel, and their effects were complex and varied across regions. These results shed light on the agglomeration and heterogeneity characteristics of the spatial distribution and influencing factors of Hive Boxes. For an enhanced community-based end-to-end delivery service, this study suggested the identification of the geographic variations of Hive Box distribution and the combined effects of multiple factors in intensifying the infrastructure of unattended locker points.
12
Liu, Yuefeng, e Jiayi Yao. "Analysis of the Aggregation Characteristics and Influencing Elements of Urban Catering Points in Small Scale: Methods and Results". ISPRS International Journal of Geo-Information 12, n. 7 (11 luglio 2023): 275. http://dx.doi.org/10.3390/ijgi12070275.
Abstract (sommario):
Urban catering systems constitute an important subsystem of the complex urban system. They can reveal not only the impact of urban functional structure on the catering but also the behavioral patterns of individual catering points through the exploration of their small-scale aggregation characteristics and influencing elements, thus becoming an essential basis for urban functional planning. In this study, we analyze the aggregation characteristics of catering points in a particular study area using the probabilistic methods, with Beijing catering points as a sample. The analysis revealed a good power-law distribution characteristic of the catering points density at the small scale. Then, an aggregation effect analysis model and an agglomeration effect analysis model were established. Based on this, an empirical analysis of candidate agglomeration kernel elements was conducted. The results showed that the influence of candidate agglomeration kernel elements on catering points exhibited a categorical nature. Additionally, a good power-law attenuation relationship was uncovered between the density and distance of catering points, which ultimately revealed the mechanism of preferential attachment in the competition for catering point site selection. Using the results of the agglomeration analysis, a reasonable explanation was provided for the power-law distribution characteristic of the density of catering points, which achieved an organic connection between micro-analysis and macro-characteristic analysis. These findings could provide a reference for the analysis of aggregation characteristics of other urban commercial formats.
13
Liu, Hexin, Fuxin Yang, Zhenghong Li, Houzhang Tan, Peng Feng e Xing Liu. "Simulation and optimization of the particle agglomeration in an aerodynamic agglomerator using a CFD–PBM coupled model". International Journal of Modern Physics C 31, n. 09 (29 luglio 2020): 2050121. http://dx.doi.org/10.1142/s0129183120501211.
Abstract (sommario):
As an effective method to remove fine particulate matter (FPM) in coal-fired industries, the aerodynamic agglomeration has recently received increasing attention due to its application value. In this paper, a CFD–PBM coupled model of the particle agglomeration for industrial application was developed to predict the particle size distributions (PSDs) using Eulerian multiphase approach and Population Balance Model. Three kinds of particles with different inertia (i.e. inertialess, finite inertial, and inertial) and Brownian motion were considered, and a collision efficiency was induced to modify the kernel functions. Furthermore, the impacts of inlet velocity, initial particle concentration and flow field on the PSDs and the agglomeration efficiency were investigated. The results show that the agglomeration efficiencies of particulate matters with aerodynamic diameter [Formula: see text] 2.5[Formula: see text][Formula: see text]m and [Formula: see text] 10[Formula: see text][Formula: see text]m (i.e. PM[Formula: see text] and PM[Formula: see text]) both present logarithmic curves with the inlet velocity or the initial particle concentration. Under the working condition of the calculation, the optimal inlet velocity is in the range of 11–15[Formula: see text]m[Formula: see text][Formula: see text][Formula: see text]s[Formula: see text], and the optimal agglomeration efficiency of [Formula: see text] and [Formula: see text] is about 40%. The aerodynamic agglomerator is suitable for the traditional coal-fired power plants and cement plants, but it is not recommended when the initial particle concentration is less than 16.9[Formula: see text]g[Formula: see text][Formula: see text][Formula: see text]m[Formula: see text]. The analysis of the flow field shows that the longitudinal edge of the vortex and the windward side of the vortex generator are the main regions where particles agglomerate.
14
Ma, Hongyu, e Lingli Li. "The coupling coordination relationship between sports industry agglomeration and economic resilience in the Yangtze River Delta region". PLOS ONE 19, n. 5 (24 maggio 2024): e0302356. http://dx.doi.org/10.1371/journal.pone.0302356.
Abstract (sommario):
With a rapidly growing sports industry worldwide, one may argue that sports industry agglomeration can play a crucial role in the economy of the sports industry. In particularly, the coupling linkage between sports industry agglomeration and economic resilience can be leveraged to promote both economic quality and efficiency. Based on data on three provinces and one city in the Yangtze River Delta region during the 2011–2020 period, this study uses the entropy-weighted TOPSIS method, coupling coordination degree model, and relative development models to explore the coupling coordination relationship between sports industry agglomeration and economic resilience in this region. The results show that: (1) Sports industry agglomeration shows an overall increasing albeit fluctuating trend with inter-provincial differences. (2) Economic resilience has steadily increased, while the economic resilience kernel density curve generally shows a "dual peaks" trend. (3) The coupling coordination between sports industry agglomeration and economic resilience remains in a fluctuating, albeit coordinated state. These findings are relevant for the integration and high-quality development of the sports industry in the Yangtze River Delta region.
15
Jażdżewska, Iwona. "Changes in population density of the urban population in southern Poland in the period 1950-2011 against the background of political and economic transformation". Miscellanea Geographica 21, n. 3 (1 settembre 2017): 107–13. http://dx.doi.org/10.1515/mgrsd-2017-0017.
Abstract (sommario):
Abstract This paper presents the changes in urban population density in the twentieth and twenty-first centuries in an area of approximately 20,000 km2 in southern Poland, which includes close to 100 towns and cities with a population of almost 4.5 million (in 2011) and an urbanisation index over 70%. It is the most urbanised part of Poland and includes the Cracow agglomeration and the Upper Silesian conurbation. The analysis was performed using one of the statistical methods for estimating discrete distributions, the kernel function method. The conclusions served as a basis for the presentation of changes occurring in this area against the backdrop of political and economic transformation in Poland, as well as a scientific discussion concerning the state and future of the merging of these agglomerations in the light of the factors discussed.
16
Yan, Yan, Qingyuan Yang, Huiming Zhang, Rongrong Zhang, Kaiyue Yang e Xiaochi Qu. "The Spatial Features and Driving Mechanism of Homestead Agglomeration in the Mountainous and Hilly Areas of Southwestern China: An Empirical Study of 22 Villages in Chongqing". Land 11, n. 8 (21 agosto 2022): 1363. http://dx.doi.org/10.3390/land11081363.
Abstract (sommario):
Scientific analysis of the spatial features and driving factors of homestead agglomeration in different landform types of mountainous and hilly areas in Southwest China is of great significance for the optimization of national spatial patterns and high-quality rural development. This paper selects 22 villages in 3 towns with different landform types in Chongqing and examines the spatial features and driving factors of homestead agglomeration in different landform types from the perspectives of terrain gradient, kernel density estimation, farmer household agglomeration status, and landscape index. We analyzed the agglomeration spatial features of different landform types and explored their driving factors and mechanisms. It was found that (1) the distribution of homesteads in mountainous and hilly areas has obvious terrain gradient characteristics, and the layout of platform area homesteads is not constrained by terrain conditions. (2) Chongqing homesteads show a spatially dispersed pattern, but the degree of homestead spatial agglomeration varies significantly among different landform types, with those in mountainous and hilly areas being mainly dispersed and those in platform areas being mainly clustered. (3) Homestead spatial agglomeration is characterized by a combination of factors inside and outside the rural system and farmers’ willingness. There are differences in the driving factors of homestead agglomeration in different landform types. Homestead agglomeration in mountainous and hilly areas is mainly driven externally, while homestead agglomeration in platform areas is mainly driven internally. In both situations, farmers’ willingness must be fully considered. The results of this study can provide a scientific basis for the spatial planning and optimal allocation of land resources in the southwestern hilly area.
17
Zhang, Xiaowei, Xinjian Huang e Jiujun Li. "The Evolution of Green Development, Spatial Differentiation Pattern and Its Influencing Factors in Characteristic Chinese Towns". Sustainability 15, n. 6 (13 marzo 2023): 5079. http://dx.doi.org/10.3390/su15065079.
Abstract (sommario):
Characteristic Chinese towns are “green ecology” innovation space units based on the background of the ‘Beautiful China Initiative’ (BCI), new urbanization, supply-side structural reform and the implementation of rural revitalization strategies. In this paper, spatial analysis models such as kernel density analysis, spatial autocorrelation analysis, the local correlation index and ArcGIS 10.5 are used to analyze the spatial layout and structural characteristics of the green development evolution of characteristic towns and to explore their spatial differentiation characteristics and laws, internal influencing factors and mechanisms. The analysis of the spatial distribution kernel density shows that regional economic development is an important influencing factor that affects the layout of the characteristic towns. Spatial autocorrelation analysis indicates that the spatial distribution of the characteristic towns does not have random distribution characteristics but is clustered in areas of similar scale. The results show the following: (1) The spatial layout of characteristic towns is generally a cohesive distribution with obvious agglomeration trends and differences, showing the characteristics of “dense in the southeast, sparse in the northwest” and “overall agglomeration, relying on economy, along the coast and along traffic arteries, spreading around cities, and differentiating by scenery”. (2) The high-density core area and sub-high-density area of characteristic towns are situated along the coast and along traffic arteries, are characterized by resource endowments and economic development, and are distributed along urban agglomerations and metropolitan areas. (3) The spatial pattern of green development evolution is organically coupled across three dimensions: location, industry and community. Our research results will help improve the level of green development in characteristic towns; coordinate the spatial layout of new urbanization; improve regional, high-quality, and coordinated development; and realize Chinese-style modernization for common prosperity.
18
Li, Manfei, Ran Zhao, Yanfang Du, Xiaomeng Shen, Qiang Ning, Yunfu Li, Dan Liu, Qing Xiong e Zuxin Zhang. "The Coordinated KNR6–AGAP–ARF1 Complex Modulates Vegetative and Reproductive Traits by Participating in Vesicle Trafficking in Maize". Cells 10, n. 10 (30 settembre 2021): 2601. http://dx.doi.org/10.3390/cells10102601.
Abstract (sommario):
The KERNEL NUMBER PER ROW6 (KNR6)-mediated phosphorylation of an adenosine diphosphate ribosylation factor (Arf) GTPase-activating protein (AGAP) forms a key regulatory module for the numbers of spikelets and kernels in the ear inflorescences of maize (Zea mays L.). However, the action mechanism of the KNR6–AGAP module remains poorly understood. Here, we characterized the AGAP-recruited complex and its roles in maize cellular physiology and agronomically important traits. AGAP and its two interacting Arf GTPase1 (ARF1) members preferentially localized to the Golgi apparatus. The loss-of-function AGAP mutant produced by CRISPR/Cas9 resulted in defective Golgi apparatus with thin and compact cisternae, together with delayed internalization and repressed vesicle agglomeration, leading to defective inflorescences and roots, and dwarfed plants with small leaves. The weak agap mutant was phenotypically similar to knr6, showing short ears with fewer kernels. AGAP interacted with KNR6, and a double mutant produced shorter inflorescence meristems and mature ears than the single agap and knr6 mutants. We hypothesized that the coordinated KNR6–AGAP–ARF1 complex modulates vegetative and reproductive traits by participating in vesicle trafficking in maize. Our findings provide a novel mechanistic insight into the regulation of inflorescence development, and ear length and kernel number, in maize.
19
Shi, Yan, Yan Wu, Bingrong Chen, Da Wang e Min Deng. "A Formation Mechanism of Spatial Distribution Pattern of Industrial Clusters under Flow Space". Applied Sciences 13, n. 11 (31 maggio 2023): 6704. http://dx.doi.org/10.3390/app13116704.
Abstract (sommario):
This study focuses on analyzing the spatial distribution pattern and formation mechanisms of urban industrial clusters and aims to address the mismatch between industrial clusters and resource distribution. Firstly, the spatial distribution pattern of industrial clusters is analyzed using the kernel density estimation approach. Subsequently, a multi-layered model of interactive driving factors is constructed to analyze the functional types within the multi-layered network space. Lastly, a spatial weighted regression analysis model, considering the intensity of flow space, is developed to explore the intrinsic formation mechanisms of industrial agglomeration. The experimental results indicate the following: (1) There is a trend of industrial agglomeration in the Yangtze River Delta region, primarily concentrated in cities such as Shanghai, Nanjing, Hefei, Jinhua, and Taizhou. (2) The impact of spatial interaction factors on industrial agglomeration development is significant, and the analysis of interaction networks reflects the strength of interactive influencing factors to a certain extent. (3) The regression analysis model, which incorporates interactive information considering flow space intensity, better aligns with the study of the actual mechanisms behind industrial agglomeration in physical space.
20
Han, Han, Weihua Chen, Jun Zhang, Wei Wang, Zhipeng Xiao, Zhijin Wang e Yangtao Wan. "Study on the Characteristics of Spatial Evolution and Influencing Factors of Green Buildings in China". Buildings 14, n. 3 (7 marzo 2024): 714. http://dx.doi.org/10.3390/buildings14030714.
Abstract (sommario):
Utilizing panel data pertaining to green building across 333 prefecture-level administrative units in China (excluding Hong Kong, Macao, and Taiwan) during the period spanning 2008–2020, an exhaustive examination of the evolution of China’s spatial pattern in green building is conducted employing the nearest neighbor index method, spatial autocorrelation analysis method, and kernel density analysis method. Furthermore, geographic probes are employed to scrutinize the determinants influencing China’s spatial configuration of green buildings. The findings reveal that: (1) An alteration in the density distribution from a “unipolar nucleus and double sub-nuclei” configuration to a “triple polar nuclei and multiple sub-nuclei” manifestation has been discerned in the spatial agglomeration of green buildings in China, exhibiting annual growth. Additionally, the center of green building development has shifted from the northwest to the southwest. (2) Pronounced agglomerations are predominantly situated in the eastern, central, and western regions of the country. High-high agglomerations have gradually dissipated over time in the central provincial capitals of China, the Yangtze River Delta, the Pearl River Delta, and the city clusters of Beijing-Tianjin-Hebei along the eastern seaboard. The western regions manifest a concentration of low-low and low-high aggregates, with high-low agglomeration primarily observed in the provincial capitals of the western regions. (3) The spatial differentiation of green buildings in China is attributable to a multitude of variables encompassing the environment, economy, society, and policies. Among these factors, economic, social, and innovative elements exert the most significant influence on the explicable degree of spatial differentiation.
21
Otto, Eric, Robert Dürr, Gerd Strenzke, Stefan Palis, Andreas Bück, Evangelos Tsotsas e Achim Kienle. "Kernel identification in continuous fluidized bed spray agglomeration from steady state data". Advanced Powder Technology 32, n. 7 (luglio 2021): 2517–29. http://dx.doi.org/10.1016/j.apt.2021.05.028.
22
Moseley, James L. "THE DISCRETE AGGLOMERATION MODEL: THE MOMENT PROBLEM FOR THE AUTONOMOUS QUADRATIC KERNEL". Far East Journal of Applied Mathematics 91, n. 3 (27 giugno 2015): 157–87. http://dx.doi.org/10.17654/fjamjun2015_157_187.
23
Liu, Tao, Wang Yifei e Kai Liu. "Temporal and Spatial Evolution of Economic Quality Difference between North and South China". Research in Economics and Management 8, n. 3 (23 agosto 2023): p111. http://dx.doi.org/10.22158/rem.v8n3p111.
Abstract (sommario):
Based on the “Five development Concepts”, this paper uses the entropy method to measure the economic quality of 336 prefecture-level regions and above in China from 1991 to 2020, and uses Dagum Gini coefficient, Kernel density estimation, spatial autocorrelation and standard deviation ellipse to explore the spatio-temporal evolution characteristics of North-South economic quality differences. The main conclusions are as follows: 1) From 1991 to 2020, the economic quality of the north and south continues to grow, and the spatial distribution pattern shows a relatively significant feature of “the south is relatively high, the north is relatively low” and “the coastal economic belt is relatively high, and the inland city is relatively low”. 2) In the past 30 years, the relative difference between the north and south regions has fluctuated and decreased, while the absolute difference has increased. 3) The economic quality of southern cities has a more significant spatial agglomeration. HH agglomeration and LL agglomeration are dominant in the south, while LL agglomeration is more inclined in the north. 4) The economic mass center of gravity in the north and the south showed a migration trend of “northeast-north” and “northwest-southwest” respectively.
24
He, Qinghua, Xin Zheng, Xin Xiao, Lei Luo, Hui Lin e Shan He. "The Spatiotemporal Evolution and Influencing Factors of the Ceramics Industry in Jingdezhen in the Last 40 Years". Land 12, n. 8 (5 agosto 2023): 1554. http://dx.doi.org/10.3390/land12081554.
Abstract (sommario):
The ceramic industry has been vital to the city’s development and prosperity in Jingdezhen, but the development of the ceramics industry in Jingdezhen has been unclear since China’s economic reforms, which will become a bottleneck limiting the sustainable development of the city. This study explored the spatial agglomeration and spatiotemporal evolution of the ceramics industry in Jingdezhen from 1980 to 2020 using enterprise directory data. The study opted for a microscopic perspective and employed kernel density estimation and exploratory spatial data analysis to obtain the necessary results. It also analyzed the influencing factors using a Geodetector. The results show that the temporal evolution of the ceramics industry in Jingdezhen went through two stages from 1980 to 2020. The number of enterprises experienced exponential growth, with fluctuations. The spatial evolution of the ceramics industry transitioned from a “single-center” to a “double-center” model and further evolved into a “multi-center” model. Moreover, the spatial agglomeration of the ceramics industry underwent the process of “agglomeration-diffusion-polarization”, ultimately developing into four ceramic industrial agglomeration patterns in six hotspots. Agglomeration, historical, technological, policy, and transportation factors had positive effects on the evolution of the ceramics industry in Jingdezhen, with agglomeration being the top contributor. Likewise, there were obvious interactions between the factors. This study can provide a basis for formulating policies to support urban spatial planning for urban revitalization, and provide foundation for the development of the national ceramic culture inheritance and innovation pilot zone in Jingdezhen.
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Yuan, Xiaodie, Baoyu Chen, Xiong He, Guojun Zhang e Chunshan Zhou. "Spatial Differentiation and Influencing Factors of Tertiary Industry in the Pearl River Delta Urban Agglomeration". Land 13, n. 2 (1 febbraio 2024): 172. http://dx.doi.org/10.3390/land13020172.
Abstract (sommario):
The tertiary industry has become the main driving force for China’s economic development, and the adjustment and optimization of its structure are important prerequisites for achieving high-quality economic development. Existing studies have mostly focused on the spatial layout and influencing factors of the tertiary industry, with insufficient exploration of its internal structure. In this study, the PRD urban agglomeration is selected as the study area. On the basis of classifying the tertiary industry, the Dagum Gini coefficient, kernel density estimation, and local spatial autocorrelation are used to explore the spatial differentiation of various tertiary industries. The influencing factors are analyzed using geographical detectors, and suggestions for future development strategies are proposed. The results show that in terms of regional differentiation, the agglomeration of various tertiary industries in Guangzhou and Shenzhen is the most significant, but there is insufficient spillover to surrounding cities. In terms of development structure, the level of agglomeration of the consumptive tertiary industry is higher, the public tertiary industry tends to be more evenly distributed, and the productive tertiary industry is relatively dispersed. In terms of influencing factors, the interaction between population and employment dominates the spatial differentiation and evolution of the tertiary industry in the PRD urban agglomeration. Therefore, in the future, the tertiary industry in PRD urban agglomeration should promote the optimization of industrial structure and regional coordinated development under the guidance of the government.
26
Long, Fei, Jiaming Liu, Shuying Zhang, Hu Yu e Hou Jiang. "Development Characteristics and Evolution Mechanism of Homestay Agglomeration in Mogan Mountain, China". Sustainability 10, n. 9 (21 agosto 2018): 2964. http://dx.doi.org/10.3390/su10092964.
Abstract (sommario):
The homestay business has contributed to the development of the tourism industry, and it has revitalized tourism resources and boosted the tourism economy. This article takes the Mogan Mountain homestay agglomeration of Yangtze River Delta, the most developed and actively invested in business in the industry, as a research site focus to discuss the recent trends in the Chinese homestay business. Standard deviational ellipse analysis, spatial analysis of nearest-neighbor, and density are empirically tested with the data from the inn/homestay channel of Qunar.com, which is a widely acclaimed website with high page views. Based on the above researches, this paper uses the standard deviation ellipse analysis, the nearest neighbor analysis, and the kernel density estimation analysis method to explore the development characteristics of the Mogan Mountain homestay agglomeration. Combined with the Butler tourist destination life cycle model, it can be concluded that the Mogan Mountain homestay agglomeration area experienced a stage of initial development (2007–2011) and rapid development (2012–2015) and now is in a mature development stage (2016 up to now). This study proposes five actors: physical geographical conditions, traffic location conditions, tourism self-organization mechanism, policy influence, and community residents’ willingness to develop and significantly drive the evolution of Mogan Mountain homestay agglomeration. The formation and evolution of the Mogan Mountain homestay agglomeration are the results of the accumulation of resource-driven effect, scale effect, and differentiation effect at different stages. The unique organization and incentive mechanism promote regional sustainable development.
27
Iseki, Hiroyuki, e Hyunjoo Eom. "Impacts of Rail Transit Accessibility on Firm Spatial Distribution: Case Study in the Metropolitan Area of Washington, DC". Transportation Research Record: Journal of the Transportation Research Board 2673, n. 11 (11 giugno 2019): 220–32. http://dx.doi.org/10.1177/0361198119844464.
Abstract (sommario):
Agglomeration economies can arise in areas with high concentrations of firms, which can be facilitated by improved transportation accessibility. Accessibility can be improved by public transit infrastructure, especially in combination with careful planning for transit-oriented development (TOD) that creates compact, high density, mixed-use, and pedestrian-friendly built environments in proximity to public transit infrastructure. Although the literature on TOD has increasingly shown positive effects on residential development and property values, its effects on commercial and industrial development, location of firms, and associated agglomeration economies are less clear and require more empirical study. This study analyzes firm location patterns by industry/sector in the metropolitan area of Washington, DC and examines whether significant spatial clusters have developed in relation to: 1) the presence of Metrorail stations; and 2) the presence of specific industry firms in the earlier year, using kernel density analysis and multinomial logit (MNL) regression. The analysis results indicated that firms in certain industries, such as finance and insurance/real estate and public administration, are more likely to benefit from proximity to Metrorail stations than other industries. Furthermore, firms in several industries show the effects of agglomeration within the same industry while several combinations of industries exhibit cross-industry agglomeration effects. The findings of this study contribute to the understanding of which industry sectors are more likely to be located in proximity to rail transit stations and TOD areas and to the understanding of agglomeration effects within the same industry and between different industries.
28
Hoffmann, Thomas L. "An extended kernel for acoustic agglomeration simulation based on the acoustic wake effect". Journal of Aerosol Science 28, n. 6 (settembre 1997): 919–36. http://dx.doi.org/10.1016/s0021-8502(96)00489-2.
29
Moseley, James L. "THE DISCRETE AGGLOMERATION MODEL: THE FIXED PROBLEM WITH APPLICATION TO THE QUADRATIC KERNEL". Far East Journal of Applied Mathematics 96, n. 5 (21 giugno 2017): 245–65. http://dx.doi.org/10.17654/am096050245.
30
Livk, I., e D. Ilievski. "A macroscopic agglomeration kernel model for gibbsite precipitation in turbulent and laminar flows". Chemical Engineering Science 62, n. 14 (luglio 2007): 3787–97. http://dx.doi.org/10.1016/j.ces.2007.03.030.
31
Hussain, Mubashir, Mirko Peglow, Evangelos Tsotsas e Jitendra Kumar. "Modeling of aggregation kernel using Monte Carlo simulations of spray fluidized bed agglomeration". AIChE Journal 60, n. 3 (7 gennaio 2014): 855–68. http://dx.doi.org/10.1002/aic.14332.
32
Wu, Zhixia, Xiazhong Zheng, Yijun Chen, Shan Huang, Chenfei Duan e Wenli Hu. "Regional differences and dynamic evolution of high-quality development in service industry: A case study of the Chengdu-Chongqing economic circle". PLOS ONE 19, n. 3 (1 marzo 2024): e0297755. http://dx.doi.org/10.1371/journal.pone.0297755.
Abstract (sommario):
The high-quality development of service industry has become an important engine for promoting sustainable economic development. This paper first constructed the evaluation index system of high-quality development of service industry, based on panel data from 2005 to 2020. Second, Kernel density, Markov chain and Dagum Gini coefficient were used to represent the regional differences and dynamic evolution of service industry, and the Koo method was used to explore the characteristics of spatial agglomeration. Finally, social network analysis was used to identify core indicators. The study found that: (1) From 2005 to 2020, the overall level of service industry first decreases and then increases, with Chengdu and Chongqing leading other cities. (2) The development of service industry in the CCEC has large spatial differences, mainly due to inter-regional differences. (3) The level of spatial agglomeration is less variable, with high agglomeration mainly in Chengdu. (4) Indicators such as the level of human capital are the core factors of its high-quality development. This study is of great theoretical and practical significance for the optimization and upgrading of service industry in the CCEC and the synergetic development of the region.
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Schreier, Julia, e Ulrich Bröckel. "Morphology of Graphite Agglomerates Obtained by Spherical Agglomeration via Propagation-Based X-Ray Microtomography". Image Analysis and Stereology 43, n. 1 (3 aprile 2024): 85–95. http://dx.doi.org/10.5566/ias.2974.
Abstract (sommario):
The aim of this work was to develop a novel method for studying the 3D morphology of agglomerates obtained by spherical agglomeration. It has been found, that the combination of shock-freezing the samples in a mixture of ethanol and dry ice followed by an X-ray microtomography measurement leads to useful results. Hereby, the image quality for low absorbing material like the used graphite was enhanced by propagation-based X-ray microtomography, which results in phase contrast images. We also discuss our 3D image post-processing routine, which is used to determine the morphology parameters sphericity, fractal dimension and packing density. Furthermore, a two-dimensional kernel density estimation is used to calculate the joint probability density of agglomerate size and the morphology parameter. In future, this method will be used to determine the morphological behaviour of agglomerates during the different phases of spherical agglomeration.
34
Wang, Weiwu, Shan Wang, Huan Chen, Lingjun Liu, Tianle Fu e Yuxin Yang. "Analysis of the Characteristics and Spatial Pattern of the Catering Industry in the Four Central Cities of the Yangtze River Delta". ISPRS International Journal of Geo-Information 11, n. 6 (24 maggio 2022): 321. http://dx.doi.org/10.3390/ijgi11060321.
Abstract (sommario):
The development of the catering industry in big cities is of great significance for countries to improve the quality of development and improve people’s living standards. In recent years, the urban catering industry has effectively promoted the process of urbanization, and it is significant to study the development characteristics and spatial distribution of the catering industry for the urban pattern. Taking the four central cities (Shanghai, Hangzhou, Nanjing, and Hefei) of China’s Yangtze River Delta (YRD) urban agglomeration as examples, first, the point-of-interest (POI) data of various catering facilities in the city’s main urban area were crawled from the Amap (AutoNavi map) open platform through Python. Second, for the first time, three quantitative indicators were constructed to characterize the development and urbanization of the urban catering industry, namely cuisine localization index (CLI), cuisine diversity index (CDI), and cuisine geographical preference index (CGPI). Third, the overall spatial characteristics of the catering industry in the four central cities and administrative districts were obtained using the methods of kernel density and spatial autocorrelation analysis. The spatial distribution of the catering industry development in each city is displayed through GIS visualization, and its influencing factors are discussed preliminarily through geographically weighted regression (GWR) model. The research shows that: (1) the four central cities in the YRD have formed core catering areas with different agglomeration levels. Different cuisines in the city have the characteristics of partial spatial overlap. (2) In the four central cities of the YRD, there is a significant positive spatial correlation between the catering industry as a whole and individuals. Hangzhou and Hefei have higher CLI (0.38), but the cuisine structure is relatively simple. The CLI of Shanghai and Nanjing is at a low level, but the overall cuisine structure is relatively balanced. (3) The catering industry in the four central cities has a high degree of agglomeration, a wide range of agglomeration, and many agglomeration points. Only Shanghai cuisine, Jiangsu and Zhejiang cuisine, Anhui cuisine, Fujian cuisine, Shandong cuisine, and Hunan cuisine have significant positive correlations in space, and the correlations weaken in turn. (4) The influence intensity of the influencing factors on CLI and CDI is in the order of degree of openness, regional economic level, market vitality, population concentration level, industrial structure. The spatial pattern of catering in a city is greatly affected by the regional economy and population density. This study can provide a reference for research on the spatial distribution of the catering industry in similar urban agglomerations around the world.
35
Zhang, Penglin, Hongli Li, Junqiang Wang e Jiewen Hong. "Analysis of Spatial Wharf Pattern of the Yangtze River Delta Urban Agglomeration, China". ISPRS International Journal of Geo-Information 8, n. 12 (28 novembre 2019): 541. http://dx.doi.org/10.3390/ijgi8120541.
Abstract (sommario):
Wharves, which play a vital role in ensuring and promoting social progress and national economic development, are important in water transportation. At present, studies on related fields mainly focus on ports. A robust research system has been formed through the continuous development of port geography from the perspective of space. However, the number of relevant studies on wharves is limited. This study explores the spatial distribution characteristics of wharves in the Yangtze River Delta Urban Agglomeration by using spatial analysis methods, such as nearest neighbor index, multi-distance spatial clustering, kernel density estimation, and standard deviation ellipse. Moreover, it evaluates the allocation level of wharves from different scales by constructing an index system based on the location data of 1264 wharves in the Yangtze River Delta Urban Agglomeration. Results show that the spatial pattern of wharves exhibits evident aggregation and regional differences. The spatial distribution of wharves is characterized by a “band” structure, which is densely distributed along the Yangtze River and the eastern coast. The allocation level of wharves presents evident agglomeration at different scales. The relationship between the spatial wharf pattern and the economy shows that high gross domestic product and total imports and exports correspond to a considerable number of wharves.
36
Peng, Ruijuan, e Wanqianrong Gao. "Spatial distribution pattern and driving mechanism of tourist attractions in Gansu Province based on POI data". PLOS ONE 18, n. 10 (5 ottobre 2023): e0292165. http://dx.doi.org/10.1371/journal.pone.0292165.
Abstract (sommario):
The article utilizes POI (Point of Interest) data of tourist attractions in Gansu Province in 2021, adopts Moran’s I and kernel density analysis to study the spatial distribution pattern of tourist attractions in Gansu Province, and uses spatial autoregressive modeling to explore the driving mechanism affecting their spatial distribution pattern. The results show that: (1) Gansu Province has a large number and rich types of tourist attractions, and there are differences in the number of different types of tourist attractions; (2) The spatial distribution pattern of different types of tourist attractions in different cities and towns shows the phenomenon of both agglomeration and dispersion, with a higher degree of agglomeration in the central and northwestern regions of the province and a lower degree of agglomeration in the southwestern and southeastern corners; (3) The overall spatial distribution pattern of tourist attractions shows the distribution characteristics of multi-core decentralized distribution, forming 8 core aggregation areas in the southeast of the province; (4) The article analyzes the driving mechanism of the spatial distribution pattern of tourist attractions in Gansu Province using the buffer zone and OLS models, and the results show that the natural environment, transportation location, national policies and socio-economics all have a positive impact on the distribution of tourist attractions.
37
Zhang, Rui, Hai Long Wang, Lian Gao, Shao Kang Guan e Jing Kun Guo. "Spheroid Growth during Sintering of Copper Coated Silicon Carbide Particles in the Fabrication of Nanocomposite". Key Engineering Materials 280-283 (febbraio 2007): 1275–78. http://dx.doi.org/10.4028/www.scientific.net/kem.280-283.1275.
Abstract (sommario):
Copper coated silicon carbide clusters were used to fabricate nanocomposite. Compacts were isostatically pressed and heated in nitrogen atmosphere. Microstructure observations were carried out to show the spheroid growth of the coated clusters. Spheroid growth was found to proceed through coalescence of smaller spheroids of the coated Cu/SiC composite particles. The densification process contains steps of agglomeration – kernel-shell formation – slumping movement. Grain growth of the adherent Cu particles is suppressed due to the constraint of rigid SiC particles. This is the deterministic characteristic of the coated composite particles.
38
Zhang, Tiange, Xia Zhu, Yuanping Liu, Cui Jia e Huimin Bai. "Research on the Spatial Structure of the Beijing–Tianjin–Hebei Urban Agglomeration Based on POI and Impervious Surface Coverage". Buildings 14, n. 6 (13 giugno 2024): 1793. http://dx.doi.org/10.3390/buildings14061793.
Abstract (sommario):
Exploring urban spatial structures through spatial coupling analysis methods is an important method to provide theoretical support for the construction of sustainable urban structures. In order to make up for the neglect of POI species differences in previous studies, information entropy was introduced to calculate POI confusion, and a comprehensive POI index was constructed by combining kernel density and the entropy weight method; impervious surface coverage was extracted based on land cover data. The spatial distribution of the Beijing–Tianjin–Hebei urban agglomeration and some typical cities was analyzed by coupling two types of data using the dual-factor mapping method. The research indicates the following: (1). The spatial distribution of the two sets of data in the Beijing–Tianjin–Hebei region is highly consistent, indicating a state of high spatial coupling; Beijing has the highest proportion of coupling in the same region at the city level (73.39%). (2). The areas with different coupling of the two types of data are mainly distributed in the urban fringe areas transitioning from the city center to the suburbs, as well as in large-scale areas with single functionality such as airports, scenic spots, and ports. This study shows that analysis combining the POI comprehensive index and impervious surface coverage can effectively characterize urban spatial structure characteristics, providing a new perspective for the study of the spatial structure of the Beijing–Tianjin–Hebei urban agglomeration. It is of great significance for a deeper understanding of the laws of urban agglomeration spatial structures and guiding the coordinated development of the Beijing–Tianjin–Hebei urban agglomeration.
39
Chen, Hao, Tao Wang, Zhongyang Luo, Dong Zhou, Mengshi Lu, Mingchun He, Mengxiang Fang e Kefa Cen. "Agglomeration Kernel of Bipolar Charged Particles in the Presence of External Acoustic and Electric Fields". Aerosol and Air Quality Research 17, n. 4 (2017): 857–66. http://dx.doi.org/10.4209/aaqr.2016.09.0378.
40
Lu, Chenyu, Min Pang, Yang Zhang, Hengji Li, Chengpeng Lu, Xianglong Tang e Wei Cheng. "Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China". ISPRS International Journal of Geo-Information 9, n. 2 (1 febbraio 2020): 92. http://dx.doi.org/10.3390/ijgi9020092.
Abstract (sommario):
The study of urban spatial structure is currently one of the most popular research fields in urban geography. This study uses Lanzhou, one of the major cities in Northwest China, as a case area. Using the industry classification of POI data, the nearest-neighbor index, kernel density estimation, and location entropy are adopted to analyze the spatial clustering-discrete distribution characteristics of the overall economic geographical elements of the city center, the spatial distribution characteristics of the various industry elements, and the overall spatial structure characteristics of the city. All of these can provide a scientific reference for the sustainable optimization of urban space. The urban economic geographical elements generally present the distribution trend of center agglomeration. In respect of spatial distribution, the economic geographical elements in the central urban area of Lanzhou have obvious characteristics of central agglomeration. Many industrial elements have large-scale agglomeration centers, which have formed specialized functional areas. There is a clear “central–peripheral” difference distribution in space, with an obvious circular structure. Generally, tertiary industry is distributed in the central area, and secondary industry is distributed in the peripheral areas. In general, a strip-shaped urban spatial structure with a strong main center, weak subcenter and multiple groups is present. Improving the complexity of urban functional space is an important goal of spatial structure optimization.
41
Liu, Fan, Xiaoding Liu, Tao Xu, Guang Yang e Yaolong Zhao. "Driving Factors and Risk Assessment of Rainstorm Waterlogging in Urban Agglomeration Areas: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area, China". Water 13, n. 6 (12 marzo 2021): 770. http://dx.doi.org/10.3390/w13060770.
Abstract (sommario):
Understanding the driving factors and assessing the risk of rainstorm waterlogging are crucial in the sustainable development of urban agglomerations. Few studies have focused on rainstorm waterlogging at the scale of urban agglomeration areas. We used the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as a case study. Kernel density estimation (KDE) and spatial autocorrelation analysis were applied to study the spatial distribution characteristics of rainstorm waterlogging spots during 2013–2017. A geographical detector (GD) and geographically weighted regression (GWR) were used to discuss the driving mechanism of rainstorm waterlogging by considering eight driving factors: impervious surface ratio (ISR), mean shape index of impervious surface (Shape_MN), aggregation index of impervious surface (AI), fractional vegetation cover (FVC), elevation, slope, river density, and river distance. The risk of rainstorm waterlogging was assessed using GWR based on principal component analysis (PCA). The results show that the spatial distribution of rainstorm waterlogging in the GBA has the characteristics of multicenter clustering. Land cover characteristic factors are the most important factors influencing rainstorm waterlogging in the GBA and most of the cities within the GBA. The rainstorm waterlogging density increases when ISR, Shape_MN, and AI increase, while it decreases when FVC, elevation, slope, and river distance increase. There is no obvious change rule between rainstorm waterlogging and river density. All of the driving factors enhance the impacts on rainstorm waterlogging through their interactions. The relationships between rainstorm waterlogging and the driving factors have obvious spatial differences because of the differences in the dominant factors affecting rainstorm waterlogging in different spatial positions. Furthermore, the result of the risk assessment of rainstorm waterlogging indicates that the southwest area of Guangzhou and the central area of Shenzhen have the highest risks of rainstorm waterlogging in GBA. These results may provide references for rainstorm waterlogging mitigation through urban renewal planning in urban agglomeration areas.
42
Kong, Fanchao, Kaixiao Zhang, Hengshu Fu, Lina Cui, Yang Li e Tengteng Wang. "Temporal–Spatial Variations and Convergence Analysis of Land Use Eco-Efficiency in the Urban Agglomerations of the Yellow River Basin in China". Sustainability 15, n. 16 (9 agosto 2023): 12182. http://dx.doi.org/10.3390/su151612182.
Abstract (sommario):
Achieving synergistic development of efficient urban land use and the natural environment is crucial in promoting green urbanization. The assessment of land use eco-efficiency (LUEE) and its temporal–spatial changes provides an effective means of quantifying the relationship between the urban ecological environment and land use. Targeting 55 selected cities in the Yellow River Basin (YRB), in this study, we utilize the Super-EBM method to gauge the LUEE. We explore the temporal patterns and the spatial convergence of LUEE utilizing kernel density estimation and spatial econometric methods. Considering the resource and environmental costs of land use, we assumed the industrial pollutant emissions generated during urban land use as the undesired outputs and designed a framework for measuring the level of LUEE under double constraints, which theoretically revealed the formation process and spatial convergence mechanism of LUEE. The results show the following: (1) Throughout the sample period, the LUEE of the YRB urban agglomeration decreased from 0.158 in 2009 to 0.094 in 2020, indicating a decreasing spatial disparity in LUEE over time. Notably, the Lanxi urban cluster exhibited the largest gap in LUEE, whereas the Guanzhong Plain urban agglomeration displayed the smallest gap. The hyper-variable density exceeded the inter-group gap as the main factor leading to the difference in LUEE. (2) Although the LUEE of urban agglomerations has increased, there still exists a noticeable polarization phenomenon. (3) The LUEE of YRB demonstrates a pattern of conditional convergence and exerts a significant spatial spillover effect. Over time, the LUEE of YRB will tend towards an individual steady state. The findings have implications for strengthening linkage and synergy among cities in YRB, promoting factor integration across administrative regions, and formulating heterogeneous policies.
43
Luo, Guanglian, Bin Wang, Dongqi Luo e Chaofu Wei. "Spatial Agglomeration Characteristics of Rural Settlements in Poor Mountainous Areas of Southwest China". Sustainability 12, n. 5 (28 febbraio 2020): 1818. http://dx.doi.org/10.3390/su12051818.
Abstract (sommario):
The rural settlements in poverty-stricken mountainous areas are the "living fossils" of an economic society with the characteristics of spatial dispersion and are slowly changing. Spatial agglomeration is the development direction of rural settlements. In-depth exploration of the spatial agglomeration characteristics and influencing factors of rural settlements in poverty-stricken mountainous areas is a way to provide a basis for rural settlement restructuring. We selected Pengshui County, a national poverty-stricken county in the southwestern mountainous area of China, as the research area. Spatial buffer and kernel density analysis were used to analyze the agglomeration characteristics of rural settlements and influencing factors. The results show that: (1) The rural settlements are small in scale and the space is evenly dispersed. 55.63% of the rural settlements’ sizes are less than 1000 m2, 84.15% of the rural settlements’ sizes are less than 2500 m2, and 92.81% of the rural settlements are within 200 m. (2) The elevation and slope of topographic factors have a significant agglomeration effect on rural settlements. However, the slope direction has no agglomeration effect. 85.41% of rural settlements (52.75% of rural settlements are gathered between 400 and 800 m above sea level) are gathered at an altitude of 1000 m or less, and 77.59% of rural settlements are gathered with a slope of 6~25°. Additionally, there are few rural settlements with a slope of 0~2°. Moreover, the distribution of residential areas has no agglomeration effect on rural settlements. (3) The cultivated land exerts the most significant effect on rural settlements followed by roads and water sources, while the role of urban land is weak. 99.48% of rural settlements are concentrated in the 100 m area of cultivated land. Therefore, in the poverty-stricken mountainous areas in the southwestern mountainous areas of China, convenient farming is the primary condition for production and living. Rural settlements are highly correlated with cultivated land. Rural settlements are scattered and concentrated with the scattered cultivated land. The rural settlements were leaded by the distribution of cultivated land. Less high-quality cultivated land with less slope were occupied or not by rural residential areas’ people.
44
Li, Dongbing, Yao Chang, Zibibula Simayi e Shengtian Yang. "Multi-Scenario Dynamic Simulation of Urban Agglomeration Development on the Northern Slope of the Tianshan Mountains in Xinjiang, China, with the Goal of High-Quality Urban Construction". Sustainability 14, n. 11 (4 giugno 2022): 6862. http://dx.doi.org/10.3390/su14116862.
Abstract (sommario):
The construction of high-quality urban agglomeration has become a guiding strategy for future urban development. Based on the current development status of urban agglomeration on the northern slope of the Tianshan Mountains, the concepts of environmental protection, harmonious coexistence, and sustainable development were combined in the present study. Land cover data for 2010 and 2020 as well as data on various driving factors and limiting factors were selected to simulate and forecast the land change of the urban agglomeration under environmental constraints. At the same time, to simulate the natural development scenario, farmland protection scenario, and ecological protection scenario for the land development of urban agglomeration on the northern slope of the Tianshan Mountains in 2030, the future land use simulation and Markov (FLUS-Markov) model and the urban growth boundary (UGB) model were combined. The following conclusions may be drawn from the results. (1) Using the land cover in 2010 to simulate the land cover in 2020, the kappa value was 0.724, the overall accuracy was 82.9%, and the FOM value was 0.245, exhibiting a high accuracy. (2) Under the three scenarios, the degree of expansion varied significantly from 2020 to 2030, but the proportion of construction area remained stable at 3%. Under the natural development scenario, urban land expansion was the most obvious, followed by the farmland protection scenario, while under the ecological protection scenario, construction land expansion was the least obvious. (3) Under the three scenarios, the expansion of construction land was mainly dominated by the encroachment of grassland, and the edge expansion mode was characterized by concentrated contiguous land. (4) The kernel density results show that the urban area exhibited a year-by-year expansion, and the best suitable development area was the surrounding farmland. (5) Under the three scenarios, the delineation of UGB in urban agglomeration at the northern slope of the Tianshan Mountains was reasonable and effective, and it can provide a relevant reference for the government’s future urban development and layout planning.
45
Zhu, Huxiao, Xiangjun Ou, Zhen Yang, Yiwen Yang, Hongxin Ren e Le Tang. "Spatiotemporal Dynamics and Driving Forces of Land Urbanization in the Yangtze River Delta Urban Agglomeration". Land 11, n. 8 (21 agosto 2022): 1365. http://dx.doi.org/10.3390/land11081365.
Abstract (sommario):
Land urbanization is a comprehensive mapping of the relationship between urban production, life and ecology in urban space and a spatial carrier for promoting the modernization of cities. Based on the remote sensing monitoring data of the land use status of the Yangtze River Delta urban agglomeration collected in 2010 and 2020, the spatial differentiation characteristics and influencing factors of land urbanization in the area were analyzed comprehensively using hot spot analysis, kernel density estimation, the multi-scale geographically weighted regression (MGWR) model and other methods. The results indicated the following: (1) From 2010 to 2020, the average annual growth rate of land urbanization in the Yangtze River Delta urban agglomeration was 0.50%, and nearly 64.28% of the counties had an average annual growth rate that lagged behind the overall growth rate. It exhibited dynamic convergence characteristics. (2) The differentiation pattern of land urbanization in the Yangtze River Delta urban agglomeration was obvious from the southeast to the northwest. The hot spots of land urbanization were consistently concentrated in the southeastern coastal areas and showed a trend of spreading, while the cold spots were concentrated in the northwest of Anhui Province, showing a shrinking trend. (3) Compared with the GWR model and the OLS model, the MGWR model has a better fitting effect and is more suitable for studying the influencing factors of land urbanization. In addition, there were significant spatial differences in the scale and degree of influence of different influencing factors. Analyzing and revealing the spatiotemporal characteristics and driving mechanism of land urbanization in the Yangtze River Delta urban agglomeration has important theoretical value and practical significance for the scientific understanding of new-type urbanization and the implementation of regional integration and rural revitalization strategies.
46
Tang, Shuang, Jingxiang Zhang e Fangqu Niu. "Spatial-Temporal Evolution Characteristics and Countermeasures of Urban Innovation Space Distribution: An Empirical Study Based on Data of Nanjing High-Tech Enterprises". Complexity 2020 (28 ottobre 2020): 1–12. http://dx.doi.org/10.1155/2020/2905482.
Abstract (sommario):
Since the financial crisis in 2008, innovation has gradually become the orientation of global economic development and the strategic choice for China’s urban development. With the transformation of the urban development mode from factor-driven and capital-driven to innovation-driven, many innovation spaces have begun to emerge in cities, which attract academic attention. A large number of studies on the relation between innovation activities and geographic space mainly focus on the phenomena at the regional level, and the city is only regarded as a target of innovation activities agglomeration. The study on the distribution of innovation space within the city is insufficient. In particular, there is a lack of studies on the spatial-temporal evolution of urban innovation space distribution. However, the study on the spatial-temporal evolution characteristics of urban innovation space distribution can provide planning countermeasures for the construction of innovative cities in China. Taking Nanjing as an empirical area, the spatial-temporal evolution of urban innovation space distribution was studied through methods such as average nearest neighbor, standard deviational ellipse, kernel density estimation, and exploratory spatial data analysis based on the data of high-tech enterprises identified from 2008 to 2019. The results showed the following: (1) the distribution of urban innovation space has significant spatial agglomeration characteristics, and the degree of agglomeration continued to rise; (2) regardless of the macro- or microperspective, the distribution of urban innovation space has shown the characteristic of diffusion at the initial, but the trend of polarization in recent years is significant; and (3) the distribution of urban innovation space exhibited diverse agglomeration modes and evolution trends in different regions, and it can be divided into three categories: grouped, banded, and scattered.
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Wang, Jiacan, Mo Chen, Hongyan Zhang e Fang Ye. "Intangible Cultural Heritage in the Yangtze River Basin: Its Spatial Distribution Characteristics and Influencing Factors". Sustainability 15, n. 10 (12 maggio 2023): 7960. http://dx.doi.org/10.3390/su15107960.
Abstract (sommario):
The intangible cultural heritage in the Yangtze River Basin is rich and complete, therefore revealing its spatial distribution characteristics and influencing factors can provide a scientific basis for the diversified cultural protection and inheritance in the Yangtze River Basin and the high-quality sustainable development of the region. This study sets a total of 1250 national intangible cultural heritage from the first batch to the fifth batch in 11 provinces, municipalities, and autonomous regions which the main stream of the Yangtze River flows through as the research object. The results are visually expressed using ArcGIS spatial analysis technology in combination with the geographic concentration index, nearest neighbor index, kernel density analysis, geographical detector, and the like, which are as follows: (1) The Yangtze River Basin is a highly concentrated area for all categories of intangible cultural heritage in China. There is little difference in the overall distribution of intangible cultural heritage in the eastern, central, and western parts, but it differs a lot between different provincial areas. (2) The overall and different types of intangible cultural heritage in the Yangtze River Basin shows differentiated agglomeration characteristics, with the overall distribution structure of the “six cores and one belt”; from the perspective of types, intangible cultural heritages of traditional craftsmanship, traditional drama, folklore, folk literature, and traditional dance have obvious agglomeration; intangible cultural heritages of traditional medicine and traditional fine arts have little agglomeration; intangible cultural heritages of traditional sports, entertainment, and acrobatics are sparsely distributed, and have the least agglomeration. (3) Human and social factors are the primary factors that affect the spatial and temporal distribution of intangible cultural heritage in the Yangtze River Basin, followed by natural geographical factors, and the policy environment.
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Silva, Géssica Ramos da, Maicon De Paiva Torres, Marciana Lima Góes e Helio Pedro Amaral Souto. "Análise do comportamento oscilatório de gotas de fluidos de van der Waals sob condições de microgravidade usando o método Smoothed Particle Hydrodynamics". Ciência e Natura 41 (16 luglio 2019): 9. http://dx.doi.org/10.5902/2179460x33534.
Abstract (sommario):
In the present work, the Smoothed Particle Hydrodynamics method (SPH) is employed in the modeling of a two-dimensional drop formation problem, without an external atmosphere, using a van der Waals fluid. In addition, influences of Reynolds number, initial aspect ratio and Péclet number on drops oscillatory behavior are studied in open space conditions with zero gravity assumption. In view of the most recent researches in drops formation field using the SPH method, a hyperbolic kernel is applied to all simulations in order to ensure uniform drops liquid formation, i.e., without particle agglomeration. Through the usage of this smoothing function the tensile instability is reduced, avoiding unnecessary numerical treatments.
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Guijin, Ding, Wu Jinfeng e Deng Chunchun. "Spatial Distribution and Its Evolution Characteristics of A-grade Scenic spots of Xinjiang in the Context of Big Data". E3S Web of Conferences 253 (2021): 02002. http://dx.doi.org/10.1051/e3sconf/202125302002.
Abstract (sommario):
In the context of big data, based on the space analysis function in GIS, using the nearest neighbor index, kernel density analysis and the model of gravity center migration, this article studies spatial distribution and its evolution characteristics of A-grade scenic spots. The results showed that: 1) The number of A-grade scenic spots of Xinjiang grows rapidly and the grade structure is constantly optimized. 2) The spatial distribution characteristics of A-grade scenic spots of Xinjiang are as follows: the spatial distribution of scenic spots is in the pattern of "large dispersion and small agglomeration", mainly along 120km around the city and 10km on both sides of the traffic trunk lines, presenting a "cluster" distribution. 3) The spatial evolution characteristics of A- grade scenic spot in Xinjiang are as follows: the center of gravity of the scenic spot is gradually moving to the west, the overall distribution scope is constantly expanding, and the degree of local agglomeration is constantly increasing, formed three core distribution areas: Urumqi-changji, Yili and Kashgar. 4) The spatial distribution and evolution characteristics of A-grade scenic spots of Xinjiang are mainly affected by topography, the nearby city, population scale and traffic conditions.
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Liao, Zhenjie, e Lijuan Zhang. "Spatial Distribution Characteristics and Accessibility Analysis of Characteristic Towns in Guangdong Province Based on Ripley’s K Function". Journal of Mathematics 2022 (22 aprile 2022): 1–14. http://dx.doi.org/10.1155/2022/2873707.
Abstract (sommario):
Characteristic towns are an essential focus for developing urbanization and implementing rural revitalization in China. Studying the spatial distribution characteristics and influencing factors are of great significance for the scientific and rational cultivation and deployment of characteristic towns and promotion of the integrated development of urban and rural areas. The spatial distribution characteristics and accessibility of 142 characteristic towns in Guangdong Province were investigated using Ripley's K function and kernel density estimation. The results show that (1) the characteristic towns in Guangdong Province present the overall spatial distribution characteristics of “the Pearl River Delta region” and the local distribution characteristics of multicore diffusion in “eastern Guangdong” and “western Guangdong”; (2) the spatial distribution of industrial development, cultural tourism type, innovative and creative characteristic towns shows significant agglomeration, whereas the agglomeration characteristics of agricultural service-oriented and commercial and trade circulation-oriented characteristic towns are not significant; (3) population, economy, resources, and location are the main factors affecting the spatial distribution of characteristic towns in Guangdong Province; (4) the overall spatial accessibility of characteristic towns in Guangdong Province is relatively good. However, the accessibility of characteristic towns of industrial development is better than that of other types of characteristic towns.