*4.2. Data Normalization*

The analysis carried out was located in places that, in addition to their geographical proximity, belong to the same Autonomous Community. Its relationship with The French Way of Saint James and its main distinctive characteristics are described in Section 2.

To make the cities comparable with the data and indicators provided by the SUA, they were reduced to a predominant non-dimensional unit for which the normalization method was used through the minimum-maximum index. Once the descriptive data of the SUA was collected, first, and following the steps considered by Nagy et al., 2018 [49], each of the variables was normalized on a scale of 0 to 10, where 0 indicates the worst performance and 10 the best performance. To eliminate the effect of extreme values, the lower and upper limits of each indicator were identified in each of the cities analyzed, and then the minimum-maximum method [50] was used, which makes it possible to create a range from 0 to 10.

Considering the main criteria of the New Urban Agenda [51], for some indicators (such as indicator D.05. "Green areas per 1000 people"), the high value score was considered to represent a good performance in terms of sustainability, marked as *x*ˆ in Table 3, and for others, it was considered that it represented a poor performance (such as indicator D.02.a. "Artificial coverage area by municipality"), marked as *x*ˇ in Table 3. Therefore, the formulas were applied inversely depending on the attributes and thus also ensures that higher values represent better performance:

$$\hat{\mathfrak{x}} = \left(\frac{\mathfrak{x} - \min(\mathfrak{x})}{\max(\mathfrak{x}) - \min(\mathfrak{x})}\right) \ast 10$$

$$\mathfrak{x} = \left(\frac{\max(\mathfrak{x}) - \mathfrak{x}}{\max(\mathfrak{x}) - \min(\mathfrak{x})}\right) \ast 10$$

where *x* is the raw data value; *min*(*x*) and *max*(*x*) determine the lower and upper limits for the worst and best performance, respectively; and *x*ˆ / *x*ˇ is the normalized value after the rescaling process.


**Table 3.** Descriptive data of the SUA considered for the analysis.


#### **Table 3.** *Cont.*

Through normalization, the data became easily comparable between all the indicators. Therefore, values were obtained for each of the cities analyzed according to each of the 10 Specific Objectives of the SUA (mentioned in the Table 2). Using the arithmetic mean method using the values described, a general value per city was obtained and normalized on a scale of 0 to 10 according to its particular contribution to the SUA Objectives and, therefore, according to urban sustainability.

In Table 3, the indicators, the source, and the relationship with the Specific Objectives of the SUA are displayed. In addition, the maximum and minimum values of the group of cities analyzed without their respective normalization are revealed, in such a way that they serve as a reference framework to consider the ranges of real values that are handled between the cities of Astorga, Cacabelos, León, Ponferrada, Valverde de la Virgen, and Burgos.
