In NiloofarNL/Populationpack2016: Information pertained to Mashhad's population, IRAN

Populationpack2016

This data provides information about population of Mashhad metropolice based on families,owners, tenants, and so on in each neighbourhood in 2016. There a number of different targets that can be reached through this package such as population density This dataset contains 14 variables and 173 rows.

source

Here is a summary of this package can be seen by the chunk below:

library(Populationpack2016)
summary(Population2016)

Following this, there is a list of libraries in this data set:

library(Populationpack2016)
library(knitr)
library(ggplot2)
library(devtools)
library(usethis)

As mentioned before, this data set has 14 variables

| | | |-------------------------|--------------------------------------------------------| | OBJECTID | Id of each block as a factor | | Neighbourhoods | The names of Mashhad's neighbourhoods | | Families | Number of families living in a block | | Owners | Number of people who has their own property in a block | | Tenants | Number of people who rent a property in a block | | Total Residential Units | Whole number of residential suits in a block | | Apartment Units | Number of suits in apartments in a block | | House Units | Number of village houses in a block | | Cottages or Sheds | Number of sheds in a block | | Shape_Length | Surrounding a block in meter scale | | Shape_Area | Surface area of a block in meter scale | | Area(Hectare) | Surface area of a neighbourhoods in hectare scale | | PopulationDensity | Population density of each neighbourhood | | Population | Whole population of each neighbourhood |

Also we can see the bar chart of population in each neighborhood

ggplot(data = Population2016, aes(x = OBJECTID, y = Population)) + 
  geom_bar(stat = "identity")

Now we can see population density in Mashhad based on its neighbourhoods in 2016.

Also here is the illustration of whole neighbourhoods in Mashhad.

Assuming that population density $\rho(r)$ at distance r from the city center declines monotonically, [@chen2008wave]reintroduce an empirical model that can be written as

{=tex} \begin{equation} \label{eq:1} \rho(r) = \rho_0 exp (-br) = \rho_0 exp (-\frac{r}{r_0}) \end{equation} Where $\rho_0$ is a constant of propotionality which is supposed to equal the central density, that is, $\rho_0 = \rho(0)$, $b$ denotes a rate at which the effect of distance attenuates, and $r_0 = 1/b$ refers to a characteristic radius of urban population distribution.

Bibliography

NiloofarNL/Populationpack2016 documentation built on Jan. 2, 2022, 7:16 p.m.