Brontekst bekijken van Introduction to Geoprocessing

<i> Vak over programmeren, gedoceerd door prof. Van Lipzig. 

==Juni 2025==
</b> Het examen is in het Engels, vertaling op de achterkant. </b>
Heat wave mortality over Brussels: 
Extreme heat kan be dangerous for humann health, and people may die during a heat wave. Scientific studies have shown that mortality significantly increases during days with very high temperatures. In this excersice, we will calculate how many people heve died in Brussels due to a five-day heat wave. The temperature distribution over Brussels for each of these five days is provided in five files. Each file contains a 10x10 matrix representing a grid over Brussels with maximum temperature values of that day. These files can be found in the shared folder. You may consider Brussels as the entire square represented by the 10x10 grid points. Make a Jupyter Notebook that solves the following exercises: 
**The </u> relative risk </u> is defined as the risk of mortality during a period of high temperature compared to the risk at an ideal reference temperature. This relative risk is given by the following equation. RR = exp(a(Ti-Th)) if Ti - Th > 0, onterwise 1 where a is a coefficient with the value 0,011°C^-1 and Th the threshold temperature which is 22,8°C. Make a Jupyter Notebook that plots the relative risk as a function of temperature for temperatures between 20°C and 35°C.
** Use the function </u> np.load </u> to load the temperature data from the file teperature_day_1.npy, and plot this 10x10 matrix. Calculate the average temperature in Brussels and print it to the screen. Detemine and discplay the highest temperature of that day. 
**Make plots of the spatial distribution of the Population Attribute Fraction (PAF) and the Attributable Deaths (AD) over the city of Brussels for day 1. The population attributable fraction indicates how much of the total mortality could have been avoided if the population had not been exposed to the extreme heat and is given by: PAF = (RR-1)/RR. The number of attributable deaths indicates how many people deceased due to the high temperature in each pixel and is calculated as: AD = PAF . m(c) . f(p) where the crude mortality rate m(c) is 2,6 deaths per 100000 inhabitants per day. You have to calculate the value for f(p) yourself which is the population in a grid box devided by 100000. Each pixel in the grid represents an area of 0,6x0,6 kilometers and contains a population of 12000 people.
** Read all five temperature files and now calculate the attributable deaths for each day and plot the attributable deaths as a function of time. To reduce the mortality during a heat wave, the city is planning to implement green (trees and grasss) in the city which reduced the temperature of each pixel by 0,5°C. Plot in the same figure the evolution over the five days nut now for when the temperature is reduced. Make also a graph where you plot on the x-axis the reduction in temperature from 0 to 3°C and on the y-axis the attributable deathsover the fill 5-dayperiod. So you plot the attributable deaths in function of this temperature reduction as a sensitivity study. 
**Challenge