The Housing Units

Using Google Earth, it is possible to import the coordinates defining the boundaries of the neighbourhoods defined by both Idealista and OMI and measure their extension (in either m² or km²) Importing the boundaries from Idealista and overlapping them with OMI’s, it is possible to measure the percentage of an OMI area belonging to an Idealista area by calculating a ratio where the denominator is the total extension of a specific zone and the numerator is the area part of an Idealista neighbourhood. The formula:

These values can be used to populate a matrix where the rows represent OMI areas while the columns report the 27 neighbourhoods defined by Idealista. The numbers in each cell report what percentage of a specific OMI area (on the row) is included in any of the Idealista neighbourhoods (on the columns). For example, Table 1 shows that 77% of OMI area B4 is part of Idealista neighbourhood Centro Storico, while the remaining 23% belongs to Crocetta. It is important that each row’s total is 1, otherwise some data will be lost.

Centro Storico San Salvario Crocetta

B1 1 0 0

B2 1 0 0

B3 1 0 0

B4 0,77 0 0,23

B5 1 0 0

Table 1. Focus on how the OMI/Idealista matrix was populated.

The whole matrix can be found in Exhibit 2, whereas its use will be described in the following sections.

Figure 3.2. Housing units by OMI area in the city of Turin.

Source: OMI, 2018.

Figure 3.3 presents the precise number of housing units for each of the 41 areas, which totalled 498.215 in 2018. These numbers are extremely different across neighbourhoods, since OMI areas span from very small central zones to vaster ones such as D5 or D8. The graph includes data from three different years only to show that the differences between them are very small. To have a clearer representation, Figure 3.4 shows the variation in total number of housing units registered in 2016 and 2017 relative to the estimated stock in 2018. The differences are negligible, except for some small areas (such as B1 or B3) where there have been larger changes due to the relatively lower stock, meaning for example that a large commercial building that was converted into residential units is immediately impacting the local stock. Because of these considerations, from now stock data will only refer to the year 2018 and it will be assumed that the distribution of housing units in each neighbourhood remained constant across the years.

Figure 3.3. Residential properties in the city of Turin by OMI area, ‘A’ category data excluding offices (A10).

Source: OMI.

- 10,000 20,000 30,000 40,000 50,000 60,000 70,000 B1

B2 B3 B4 B5 B6 B7 B8 B9 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C15 C16 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 E1 E2 E3

2016 TOTAL 2017 TOTAL 2018 TOTAL

Figure 3.4. Variation in total number of housing units registered in 2016 and 2017 relative to the estimated stock in 2018.

-4.0% -3.5% -3.0% -2.5% -2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0%

B1 B2 B3 B4 B5 B6 B7 B8 B9 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C15 C16 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 E1 E2 E3

2017 2016

These figures can be rearranged to have the number of housing units attributable to Idealista neighbourhoods. Using the matrix described in 3.1.4, it is possible to obtain the values in Figure 3.5, which refer to 2018 only. Using values from only one year is sufficient in this case, since the number of buildings and houses do not change significantly over time, particularly in a city where the population is not increasing.

Figure 3.5. Number of ‘A’ category properties (excluding A10) found in each Idealista neighbourhood, 2018 OMI data.

A heat map with these figures is shown in Figure 3.6. The differences one may find with Figure 3.2 only depend on the different design of boundaries in the two maps.

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Centro Storico

Pozzo Strada Santa Rita Parella Crocetta Mirafiori Nord Aurora San Salvario Barriera di Milano Madonna di Campagna San Paolo Vanchiglia Lingotto Nizza-Millefonti San Donato Borgo Vittoria Mirafiori Sud Falchera-Villaretto Sassi-Madonna del Pilone Cenisia Lucento Regio Parco-Barca-Bertolla Rebaudengo Cit Turin Borgata Lesna Campidoglio Vallette

Figure 3.6. Housing units by Idealista area in the city of Turin, ‘A’ category excluding offices (A10).

Now that housing units have been attributed to Idealista neighbourhoods, it is possible to investigate what type of properties are usually found in the different areas. The stack bars in Figure 3.7 show the number of units belonging to the main cadastral categories, which are the following (note that “Other” includes the categories A06, A07, A08, A09 and A11):

A01 Abitazioni Signorili Higher-class homes A02 Abitazioni Civili Regular homes A03 Abitazioni Economiche Economical homes A04 Abitazioni Popolari Public housing homes

A05 Abitazioni Ultrapopolari Homes with a lower quality than A04 A06 Abitazioni Rurali Rural homes

A07 Abitazioni in Villini Small villas

A08 Abitazioni in Ville Higher-class villas

A09 Castelli e Palazzi artistici o storici Castles and historical buildings A11 Abitazioni Tipiche dei luoghi Typical homes

© 2020 Mapbox © OpenStreetMap

4,443 32,399 Housing Units

Figure 3.7. Composition of Idealista neighbourhoods by property type.

Source: OMI data, 2018.

As the graph shows, the most widely diffused category is A03, followed by A02 and A04, while the remaining classes make up a very small share of the number of housing units. The dataset used for these graphs provides the total number of square meters for each property

- 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Centro Storico

Pozzo Strada Santa Rita Parella Crocetta Mirafiori Nord Aurora San Salvario Barriera di Milano Madonna di Campagna San Paolo Vanchiglia Lingotto Nizza-Millefonti San Donato Borgo Vittoria Mirafiori Sud Falchera-Villaretto Sassi-Madonna del Pilone Cenisia Lucento Regio Parco-Barca-Bertolla Rebaudengo Cit Turin Borgata Lesna Campidoglio Vallette

A03 A02 A04 A05 A01 Other

category which, using the number of housing units belonging to each category, can be used to estimate the average dimension of homes. Weighing these ‘category dimensions’ for their percentage on the total stock in the city, 91 m² happens to be the average dimension of a home in Turin (using 2018 data).