230
G. M. Oliveira et al.
3 The Outcomes of WeGIx Application to Portugal: Results
Analysis
The best and worst ten scores for Portuguese municipalities are presented in Table 4.
These results correspond to WeGIx calculation, according to Eq. 4, with the final set
of twenty-nine indicators selected by the described Factor Analysis.
For the observed timeline, it is worth to mention that all the best-scored positions correspond to the largest cities in the country and that the worst scores are
associated to urban densely populated areas or to rural industrialized areas. Table 5
presents results of One-way ANOVA with post hoc Tukey HSD (Honestly Significant
Difference) to compare WeGIx scores by population density (according to Fig. 1),
for years 2009, 2015 and present. Significant statistical differences were found for
2009 (F = 3.8; p = 0.025), revealing higher mean scores in predominantly urban
areas compared to semi-urban and to predominantly rural regions. For the other time
measures, no significant differences were found.
Another One-way ANOVA with post hoc Tukey HSD was performed to compare
territory typologies according to Fig. 2 criterion. Within the timeline under analysis
no significant statistical difference was found (p > 0.05), as is visible at Table 6.
Clusters’ existence based on WeGIx scores was verified using a K-Means Cluster
Analysis (Table 10—Appendix), revealing two groups in each year. Outliers were
found associated with the lowest WeGIx scores means, which correspond to the
higher populated municipalities in the country.
Another important reflection is to evaluate how the country’s inequalities are
evolving in time, as more population are associated to WeGIx scores below the
national average. Table 7 exhibits the share of population whose municipalities are
positioned above or below the reference value W eGIx |Portugal = 0, for each period of
analysis. At present, the scenario is worse than in 2009 (at the time the country was
in financial crisis), now, almost two-thirds of the country population experiences
life conditions below the national average. It is worth to remark that the WeGIx
benchmark is the country itself, thus these results reflect a worsening of the country
inequalities, unfolding a legitimate concern regarding the country’s strategies and
policies towards achieving the SDGs.
Figures 3 and 4 mirror the results of Table 7 for easier comprehension.
G. M. Oliveira et al.
3 The Outcomes of WeGIx Application to Portugal: Results
Analysis
The best and worst ten scores for Portuguese municipalities are presented in Table 4.
These results correspond to WeGIx calculation, according to Eq. 4, with the final set
of twenty-nine indicators selected by the described Factor Analysis.
For the observed timeline, it is worth to mention that all the best-scored positions correspond to the largest cities in the country and that the worst scores are
associated to urban densely populated areas or to rural industrialized areas. Table 5
presents results of One-way ANOVA with post hoc Tukey HSD (Honestly Significant
Difference) to compare WeGIx scores by population density (according to Fig. 1),
for years 2009, 2015 and present. Significant statistical differences were found for
2009 (F = 3.8; p = 0.025), revealing higher mean scores in predominantly urban
areas compared to semi-urban and to predominantly rural regions. For the other time
measures, no significant differences were found.
Another One-way ANOVA with post hoc Tukey HSD was performed to compare
territory typologies according to Fig. 2 criterion. Within the timeline under analysis
no significant statistical difference was found (p > 0.05), as is visible at Table 6.
Clusters’ existence based on WeGIx scores was verified using a K-Means Cluster
Analysis (Table 10—Appendix), revealing two groups in each year. Outliers were
found associated with the lowest WeGIx scores means, which correspond to the
higher populated municipalities in the country.
Another important reflection is to evaluate how the country’s inequalities are
evolving in time, as more population are associated to WeGIx scores below the
national average. Table 7 exhibits the share of population whose municipalities are
positioned above or below the reference value W eGIx |Portugal = 0, for each period of
analysis. At present, the scenario is worse than in 2009 (at the time the country was
in financial crisis), now, almost two-thirds of the country population experiences
life conditions below the national average. It is worth to remark that the WeGIx
benchmark is the country itself, thus these results reflect a worsening of the country
inequalities, unfolding a legitimate concern regarding the country’s strategies and
policies towards achieving the SDGs.
Figures 3 and 4 mirror the results of Table 7 for easier comprehension.