Populationpack2016-vignette

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

Install the package

As a fundamental step, there is a need to install population package if you want to use this data set.

Here is a chunk in order to install the package:

knitr::opts_chunk$set(message = FALSE)
if(!require(remotes)){
    install.packages("remotes")
    library(remotes)
}
remotes::install_github("NiloofarNL/Populationpack2016")

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

library(Populationpack2016)
summary(Population2016)

##     OBJECTID   Neighbourhoods        Families         Owners    
##  Min.   :  1   Length:173         Min.   :    0   Min.   :   0  
##  1st Qu.: 44   Class :character   1st Qu.: 2552   1st Qu.:1120  
##  Median : 87   Mode  :character   Median : 4620   Median :2096  
##  Mean   : 87                      Mean   : 5259   Mean   :2342  
##  3rd Qu.:130                      3rd Qu.: 7034   3rd Qu.:3020  
##  Max.   :173                      Max.   :20359   Max.   :8314  
##                                   NA's   :1       NA's   :1     
##     Tenants      Total Residential Units Apartment Units  House Units   
##  Min.   :    0   Min.   :    0           Min.   :    0   Min.   :    0  
##  1st Qu.: 1162   1st Qu.: 2478           1st Qu.: 1002   1st Qu.:  758  
##  Median : 2174   Median : 4540           Median : 2391   Median : 1428  
##  Mean   : 2456   Mean   : 5122           Mean   : 3079   Mean   : 2043  
##  3rd Qu.: 3258   3rd Qu.: 6812           3rd Qu.: 4583   3rd Qu.: 2595  
##  Max.   :10708   Max.   :19815           Max.   :12164   Max.   :13236  
##  NA's   :1       NA's   :1               NA's   :1       NA's   :1      
##  Cottages or Sheds  Shape_Length     Shape_Area       Area(Hectare)   
##  Min.   : 0.000    Min.   : 1899   Min.   :  190576   Min.   :  19.0  
##  1st Qu.: 0.000    1st Qu.: 4290   1st Qu.:  876015   1st Qu.:  88.0  
##  Median : 1.000    Median : 5364   Median : 1368233   Median : 137.0  
##  Mean   : 1.773    Mean   : 5857   Mean   : 1762437   Mean   : 176.3  
##  3rd Qu.: 2.000    3rd Qu.: 6925   3rd Qu.: 2067674   3rd Qu.: 207.0  
##  Max.   :48.000    Max.   :20888   Max.   :16678412   Max.   :1668.0  
##  NA's   :1                                                            
##  PopulationDensity   Population   
##  Min.   :  0.00    Min.   :    0  
##  1st Qu.: 76.75    1st Qu.: 8415  
##  Median :131.00    Median :15387  
##  Mean   :131.25    Mean   :17141  
##  3rd Qu.:175.00    3rd Qu.:23460  
##  Max.   :367.00    Max.   :71466  
##  NA's   :1

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

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

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.

Population Density in Mashhad 2016

Also here is the illustration of whole neighbourhoods in Mashhad.

Mashhad’s Neighbourhoods in 2016

Assuming that population density \(\rho(r)\) at distance r from the city center declines monotonically, (Chen 2008)reintroduce an empirical model that can be written as

\[\begin{equation} \label{eq:1} \rho(r) = \rho_0 exp (-br) = \rho_0 exp (-\frac{r}{r_0}) \end{equation}\]

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

Chen, Yanguang. 2008. “A Wave-Spectrum Analysis of Urban Population Density: Entropy, Fractal, and Spatial Localization.” Discrete Dynamics in Nature and Society 2008.