of mapped structures. Whereas Figs. \[fig\_morpho\]-\[fig\_influences\] showed distinct classes at expected locations, this plot displays a rather uniform and chaotic distribution of high weights for $d_2$, $d_3$, and $d_4$, revealing a pervasive role of roads, city centers, and accessibility. Only density $d_1$ correlates better with its own evaluation function $D$ (a high influence of density results in low-density patterns), except for the cluster on the right.[]{data-label="fig_influences"}](morpho){width="\columnwidth"}

![Influence of each explicative variable $d_k$ on urban morphogenesis. Color darkness corresponds to the relative value of weight $\alpha_k$ used during the growth of mapped structures. Whereas Figs. \[fig\_morpho\]-\[fig\_influences\] showed distinct classes at expected locations, this plot displays a rather uniform and chaotic distribution of high weights for $d_2$, $d_3$, and $d_4$, revealing a pervasive role of roads, city centers, and accessibility. Only density $d_1$ correlates better with its own evaluation function $D$ (a high influence of density results in low-density patterns), except for the cluster on the right.[]{data-label="fig_influences"}](paramInfluences){width="\columnwidth"}

#### Classification of structures

Using the pair of morphological indicators $(D,I)$ defined above, and by varying the $\alpha_k$’s, we constructed a 2D map of the dynamical regimes of our system (Figs. \[fig\_morpho\]-\[fig\_influences\]), in which qualitatively different morphological “classes” could be distinguished. The projected locations of 