# F Exercise 04

Last updated: 2024-06-24 11:11:04

## F.1 Materials

The materials for this exercise are:

• Vector layers (Chapter 7)
• Geometric operations with vector layers (Chapter 8)

## F.2 Question 1

• Load the built-in data.frame object named world.cities from the maps package, as follows:
library(maps)
##                 name country.etc   pop   lat  long capital
## 1 'Abasan al-Jadidah   Palestine  5629 31.31 34.34       0
## 2 'Abasan al-Kabirah   Palestine 18999 31.32 34.35       0
## 3       'Abdul Hakim    Pakistan 47788 30.55 72.11       0
## 4 'Abdullah-as-Salam      Kuwait 21817 29.36 47.98       0
## 5              'Abud   Palestine  2456 32.03 35.07       0
## 6            'Abwein   Palestine  3434 32.03 35.20       0
• The world.cities object is a table with information about world cities. The table includes the longitude and latitude of each city in the long and lat columns, respectively.
• Choose a city which starts with the same letter as your first name. (In your code, you can use the city name and the country name for subsetting.)
• Find the 5 nearest cities (excluding self) to the city you selected. (Hint: use st_distance to find the distances to all cities, then sort the cities by distance.)
• Plot (Figure F.1):
• the selected city,
• the five other nearest cities,
• labels with the city names, and
• a convex hull polygon of all 6 cities combined.
• Use axes=TRUE to show the axis coordinates in the plot.

(50 points)

## F.3 Question 2

• Load the built-in data.frame object named world.cities from the maps package, as follows:
library(maps)
##                 name country.etc   pop   lat  long capital
## 1 'Abasan al-Jadidah   Palestine  5629 31.31 34.34       0
## 2 'Abasan al-Kabirah   Palestine 18999 31.32 34.35       0
## 3       'Abdul Hakim    Pakistan 47788 30.55 72.11       0
## 4 'Abdullah-as-Salam      Kuwait 21817 29.36 47.98       0
## 5              'Abud   Palestine  2456 32.03 35.07       0
## 6            'Abwein   Palestine  3434 32.03 35.20       0
• The world.cities object is a table with information about world cities. The table includes the longitude and latitude of each city in the long and lat columns, respectively.
• Read the Shapefile named nafot.shp, which includes polygons of “Nafa” administrative regions in Israel
• Subset those cities which intersect with the “Nafa” polygons
• Calculate the average population density (people per $$km^2$$) per “Nafa” polygon, i.e., the sum of the 'pop' column of all cities falling into each “Nafa”, divided by the area of the “Nafa” in $$km^2$$
• Plot the population densities using a color scale, as shown in Figure F.2

(50 points)