scholarly journals A STUDY ON THE PROGRESS PROCESS OF THE URBAN POPULATION DENSITY DISTRIBUTION PATTERN

1967 ◽  
Vol 1967 (143) ◽  
pp. 16-21
Author(s):  
Kozo Amano ◽  
Masahisa Fujita
Keyword(s):  
Population Density ◽  
Density Distribution ◽  
Distribution Pattern ◽  
Urban Population

scholarly journals The Relationship between Urban Population Density Distribution and Land Use in Guangzhou, China: A Spatial Spillover Perspective

2021 ◽  
Vol 18 (22) ◽  
pp. 12160
Author(s):  
Yisheng Peng ◽  
Jiahui Liu ◽  
Tianyao Zhang ◽  
Xiangyang Li
Keyword(s):  
Land Use ◽  
Population Density ◽  
Spatial Structure ◽  
Density Distribution ◽  
Rapid Growth ◽  
Urban Population ◽  
Spillover Effects ◽  
Urban Spatial Structure ◽  
Direct Effects ◽  
Spatial Spillover

Urban population density distribution contributes towards a deeper understanding of peoples’ activities patterns and urban vibrancy. The associations between the distribution of urban population density and land use are crucial to improve urban spatial structure. Despite numerous studies on population density distribution and land use, the significance of spatial dependence has attained less attention. Based on the Baidu heat map data and points of interests data in the main urban zone of Guangzhou, China, the current paper first investigated the spatial evolution and temporal distribution characteristics of urban population density and examined the spatial spillover influence of land use on it through spatial correlation analysis methods and the spatial Durbin model. The results show that the urban population density distribution is characterized by aggregation in general and varies on weekends and weekdays. The changes in population density within a day present a trend of “rapid growth-gentle decline-rapid growth-rapid decline”. Furthermore, the spatial spillover effects of land use exist and play the same important roles in population density distribution as the direct effects. Additionally, different types of land use show diverse direct effects and spatial spillover effects at various times. These findings suggest that balancing the population density distribution should consider the indirect effect from neighboring areas, which hopefully provide implications for urban planners and policy makers in utilizing the rational allocation of public resources and regarding optimization of urban spatial structure.

scholarly journals Effectiveness of Government Policies in Controlling COVID-19 in India

2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Urban Areas ◽  
Urban Population ◽  
Demographic Factors ◽  
Poverty Rate ◽  
Government Policies ◽  
Cumulative Number ◽  
Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

scholarly journals PENGARUH FAKTOR EKONOMI, SOSIAL EKONOMI DAN IKLIM TERHADAP BENCANA ALAM DI INDONESIA

Jurnal Ecogen ◽  
2019 ◽  
Vol 1 (3) ◽  
pp. 539
Author(s):  
Surya Irmayani ◽  
Zul Azhar ◽  
Melti Roza Adry
Keyword(s):  
Economic Growth ◽  
Population Density ◽  
Natural Disasters ◽  
Urban Population ◽  
Participation Rate ◽  
Least Square ◽  
Ordinary Least Square ◽  
Descriptive Research ◽  
Negative Effect ◽  
Education Participation

This purpose of the research  are to the analyse the Economic Growth, Education Participation Rate, Urban Population, Population Density, Number of Rainfall in terms of Damage Natural Disasters in Indonesia. This type of research is associative descriptive research. This study is based on data 2015 obtained from institutions and related institution. Methods that being used are Ordinary Least Square (OLS). The estimation results show that Economic Growth has a significant negative effect the Damage Natural Disasters in Indonesia, Education Participation Rate has a not significant effect the Damage Natural Disasters in Indonesia, Urban Population has a significant positive effect the Damage Natural Disasters in Indonesia, Population Density has a not significant effect the Damage Natural Disasters in Indonesia, Number of rainfall has a not significant effect the Damage Natural Disasters in Indonesia. Keywords: Economic Growth, Education Participation Rate, Urban Population, Population Density, Number of Rainfall

Urban Population Density: A Comment

1981 ◽  
Vol 13 (2) ◽  
pp. 239-241
Author(s):  
J Andrulis
Keyword(s):  
Population Density ◽  
Cost Function ◽  
Gamma Function ◽  
Urban Population ◽  
Travel Cost ◽  
Specification Error ◽  
The Poor

The poor results obtained with certain members of the quadratic gamma family is shown to be due to a specification error in most of the members of that family. By choosing a more admissible travel-cost function, the displaced quadratic gamma function is derived, which does not contain this specification error.

Urban population density estimation based on spatio‐temporal trajectories

2020 ◽  
Vol 32 (14) ◽  
Author(s):  
Fei Xue ◽  
Yang Cao ◽  
Zhiming Ding ◽  
Hengliang Tang ◽  
Xi Yang ◽  
...  
Keyword(s):  
Population Density ◽  
Density Estimation ◽  
Urban Population ◽  
Spatio Temporal

scholarly journals Population Distribution in the Wake of a Sphere

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1498 ◽  
Author(s):  
Taraprasad Bhowmick ◽  
Yong Wang ◽  
Michele Iovieno ◽  
Gholamhossein Bagheri ◽  
Eberhard Bodenschatz
Keyword(s):  
Reynolds Number ◽  
Spatial Distribution ◽  
Population Density ◽  
Density Distribution ◽  
Population Distribution ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Wake Flow ◽  
Sample Number ◽  
Scalar Fluxes

The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

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