Plots for population scenarios

9.1 living space yearly

9.1.1 livings space by year

WHY? e.g. to support the base year decision

9.1.2 living space by year and owner

Figure 9.2: living space by year and owner

9.2 living space (area, apartments, people, by dyw)

9.2.1 space

Figure 9.3: living space by district, year and owner

9.2.2 area

Figure 9.4: area by district, year and owner

9.2.3 apartments

Figure 9.5: apartments by district, year and owner

9.2.4 people

Figure 9.6: people by district, year and owner

9.3 predictions

9.3.1 entire city, by owner

Figure 9.7: living space prediction by year and ownership

9.3.2 entire city, by district and owner

Figure 9.8: living space prediction by district, year and ownership

9.3.3 Escher Wyss, by owner

WHY a different approach for the Escher Wyss district, private housing? the living space over time differs substantially from the other districts (increase until 2013, then decrease) reason: few apartments in 2008 then very intense construction activity numbers: less than 1500 apartments in 2008, more than 3100 apartments in 2017 after construction some apartments were finished, yet no one lived there yet for a certain moment the empty apartments increase the living space (based on buildings) due to the high ratio of new buildings (compared to existing buildings) the living space was increased this will not happen again in future (due to the higher amount of buildings)

Figure 9.9: living space prediction for Escher Wyss district, by year and ownership

9.4 combine datasets

9.4.1 past and prediction

Figure 9.10: living space prediction by district, year and owner; different datasets

9.4.2 plot both (i.e. per district, and entire city)