Chargement des données :
tm_basemap(c(leaflet::providers$Esri.WorldTopoMap,
leaflet::providers$OpenStreetMap,
leaflet::providers$GeoportailFrance.orthos)) +
tm_shape(st_make_valid(all_isochrones),
name = "Isochrones 10min à pied") + tm_borders() +
tm_shape(data_car) + tm_dots(col = "data_rennes_classes",
palette = couleurs,
title = "Types d'emplacement",
legend.show = TRUE,
size = 0.9,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")
) +
tm_shape(data_bike) + tm_dots(col = "data_rennes_classes",
palette = couleurs, title = "Types d'emplacement",
legend.show = TRUE,
size = 0.5,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")) +
tm_shape(data_foot) + tm_dots(col = "data_rennes_classes",
palette = couleurs, title = "Types d'emplacement",
legend.show = TRUE,
size = 0.1,
labels = c("Très peu favorable", "Peu favorable", "Moyennement favorable", "Favorable", "Très favorable")) +
tm_shape(data_foot_c4) + tm_dots(size = 0.3, "#d95f0eff") +
tm_shape(data_foot_c5) + tm_dots(size = 0.3, "#993404ff") +
tm_shape(gares) + tm_dots() +
tm_text("Intitulé.gare", size = 1, fontface = 2,
just = "top", ymod = 0.5) +
tm_scale_bar()glimpse(raw_data_foot)## Rows: 282
## Columns: 24
## $ pk <chr> "457", "525", "526", "527", "615", "616"…
## $ ID_number <int> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population <dbl> 5736, 424, 705, 705, 2091, 2158, 78683, …
## $ sum_lits <dbl> 68, 0, 0, 0, 159, 159, 1337, 1337, 1337,…
## $ longueur_route <dbl> 3214.4267, 5239.1371, 1886.6417, 923.052…
## $ longueur_pistes_cyclables <dbl> 720.6147, 0.0000, 0.0000, 0.0000, 0.0000…
## $ superficie_vegetation <dbl> 224864.64, 67049.59, 99231.44, 16807.61,…
## $ nombre_arrets <dbl> 0, 6, 0, 0, 6, 0, 36, 20, 27, 8, 0, 0, 4…
## $ nombre_parkings <dbl> 0, 0, 0, 0, 0, 0, 260, 940, 381, 0, 0, 0…
## $ nombre_commerces <dbl> 2, 2, 0, 0, 0, 0, 4, 41, 5, 0, 0, 0, 0, …
## $ nombre_loisirs <dbl> 0, 2, 0, 0, 0, 0, 12, 5, 4, 0, 0, 0, 0, …
## $ nombre_restauration <dbl> 0, 0, 1, 0, 0, 0, 10, 9, 0, 0, 0, 0, 0, …
## $ nombre_sports <dbl> 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0…
## $ nombre_ronds_points <dbl> 0, 0, 0, 0, 1, 0, 1, 4, 4, 2, 0, 0, 0, 0…
## $ nombre_eleves <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ superficie_iso <dbl> 404902.2, 429741.4, 338888.1, 187163.7, …
## $ ZA <dbl> 180037.53, 362691.83, 239656.63, 170356.…
## $ passage_niveau <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1…
## $ sum_population_carreau_decoup <dbl> 89.8002595, 294.5014490, 6.1728685, 0.00…
## $ nombre_arrets_v2 <dbl> 0, 1, 0, 0, 1, 0, 16, 7, 10, 3, 0, 0, 0,…
## $ nombre_sante <dbl> 1, 0, 0, 0, 0, 0, 12, 5, 5, 0, 0, 0, 0, …
## $ nombre_arrets_v3 <dbl> 0, 1, 0, 0, 1, 0, 16, 7, 10, 3, 0, 0, 0,…
## $ pente_moyenne <dbl> 10.918756, 7.983167, 10.826729, 6.472442…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…glimpse(data_foot)## Rows: 304
## Columns: 13
## $ ID_number <dbl> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population_carreau_decoup <dbl> 2.122039e-02, 6.959262e-02, 1.458689e-03…
## $ nombre_loisirs <dbl> 0.0000000, 0.1428571, 0.0000000, 0.00000…
## $ nombre_commerces <dbl> 0.04878049, 0.04878049, 0.00000000, 0.00…
## $ nombre_restauration <dbl> 0.00, 0.00, 0.05, 0.00, 0.00, 0.00, 0.50…
## $ nombre_arrets <dbl> 0.00000000, 0.16666667, 0.00000000, 0.00…
## $ longueur_route <dbl> 0.14624358, 0.23835981, 0.08583466, 0.04…
## $ ZA <dbl> 0.19427995, 0.39503260, 0.25980643, 0.18…
## $ passage_niveau <dbl> 0.5, 0.5, 0.5, 0.0, 0.0, 0.0, 0.0, 0.0, …
## $ pente_moyenne <dbl> 0.33296625, 0.22396052, 0.32954907, 0.16…
## $ total_sum_allegee <dbl> 0.57755815, 1.33732881, 0.56755071, 0.05…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…
## $ data_rennes_classes <int> 2, 3, 2, 2, 2, 1, 5, 5, 4, 3, 2, 2, 2, 3…glimpse(raw_data_bike)## Rows: 282
## Columns: 23
## $ pk <chr> "457", "525", "526", "527", "615", "616"…
## $ ID_number <int> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population <dbl> 7686, 1260, 1260, 1260, 2324, 4423, 7868…
## $ sum_lits <dbl> 94, 15, 15, 15, 159, 625, 1337, 1337, 13…
## $ longueur_route <dbl> 41461.781, 13043.568, 13393.661, 6449.29…
## $ longueur_pistes_cyclables <dbl> 2498.4353, 0.0000, 0.0000, 0.0000, 0.000…
## $ superficie_vegetation <dbl> 4214073.6, 1729868.8, 1306503.7, 399389.…
## $ nombre_arrets <dbl> 8, 6, 6, 0, 8, 8, 184, 177, 132, 92, 21,…
## $ nombre_parkings <dbl> 1627, 2, 2, 0, 0, 0, 4529, 7042, 3030, 1…
## $ nombre_commerces <dbl> 25, 2, 2, 0, 1, 1, 174, 123, 80, 24, 5, …
## $ nombre_loisirs <dbl> 11, 3, 3, 0, 4, 4, 90, 71, 39, 24, 7, 1,…
## $ nombre_restauration <dbl> 14, 2, 2, 1, 1, 1, 152, 91, 46, 23, 9, 5…
## $ nombre_sports <dbl> 1, 0, 0, 0, 0, 0, 12, 9, 11, 6, 0, 1, 1,…
## $ nombre_ronds_points <dbl> 6, 0, 0, 0, 2, 2, 29, 31, 22, 15, 6, 8, …
## $ nombre_eleves <dbl> 0, 0, 0, 0, 0, 0, 6344, 6344, 1850, 0, 0…
## $ superficie_iso <dbl> 6821746, 3585401, 4066710, 2260015, 3526…
## $ ZA <dbl> 2607672, 1855532, 2760207, 1860625, 1980…
## $ passage_niveau <dbl> 3, 3, 3, 2, 2, 3, 0, 0, 0, 0, 2, 2, 3, 2…
## $ pente_moyenne <dbl> 8.506872, 15.362028, 11.813782, 8.050338…
## $ sum_population_carreau_decoup <dbl> 2045.88950, 400.91647, 401.04791, 62.214…
## $ nombre_arrets_v2 <dbl> 1, 1, 1, 0, 2, 2, 88, 87, 59, 40, 6, 4, …
## $ nombre_sante <dbl> 27, 0, 0, 0, 2, 2, 226, 244, 182, 103, 2…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…glimpse(data_bike)## Rows: 304
## Columns: 15
## $ ID_number <dbl> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population_carreau_decoup <dbl> 0.066911953, 0.013112196, 0.013116495, 0…
## $ nombre_eleves <dbl> 0.00000000, 0.00000000, 0.00000000, 0.00…
## $ nombre_loisirs <dbl> 0.12222222, 0.03333333, 0.03333333, 0.00…
## $ nombre_sante <dbl> 0.110655738, 0.000000000, 0.000000000, 0…
## $ nombre_commerces <dbl> 0.143678161, 0.011494253, 0.011494253, 0…
## $ nombre_restauration <dbl> 0.092105263, 0.013157895, 0.013157895, 0…
## $ nombre_sports <dbl> 0.08333333, 0.00000000, 0.00000000, 0.00…
## $ longueur_route <dbl> 0.25480921, 0.08016108, 0.08231263, 0.03…
## $ ZA <dbl> 0.3626070, 0.2560485, 0.3842171, 0.25677…
## $ passage_niveau <dbl> 0.75, 0.75, 0.75, 0.50, 0.50, 0.75, 0.00…
## $ pente_moyenne <dbl> 0.242236314, 0.528856674, 0.380501260, 0…
## $ total_sum_allegee <dbl> 1.2363229, 0.4073073, 0.5376317, 0.30501…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…
## $ data_rennes_classes <int> 2, 1, 2, 1, 2, 2, 5, 5, 4, 3, 2, 2, 2, 1…glimpse(raw_data_car)## Rows: 277
## Columns: 22
## $ pk <chr> "457", "525", "526", "527", "615", "616"…
## $ ID_number <int> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population <dbl> 14415, 2558, 2745, 1601, 11401, 11251, 1…
## $ sum_lits <dbl> 756, 15, 15, 15, 1160, 1150, 7867, 5892,…
## $ longueur_route <dbl> 215369.60, 47174.68, 63938.04, 42252.58,…
## $ longueur_pistes_cyclables <dbl> 7012.60402, 0.00000, 13.50064, 50.61811,…
## $ superficie_vegetation <dbl> 42215169, 10708098, 11879018, 7832931, 1…
## $ nombre_arrets <dbl> 9, 6, 6, 6, 14, 21, 557, 553, 530, 554, …
## $ nombre_parkings <dbl> 2677, 226, 226, 2, 2, 0, 22239, 20302, 1…
## $ nombre_commerces <dbl> 60, 5, 5, 3, 2, 3, 489, 490, 476, 493, 6…
## $ nombre_loisirs <dbl> 66, 5, 6, 3, 7, 9, 312, 312, 281, 307, 6…
## $ nombre_restauration <dbl> 71, 5, 7, 4, 3, 3, 671, 671, 636, 665, 7…
## $ nombre_sports <dbl> 4, 0, 0, 0, 0, 0, 35, 35, 33, 35, 10, 23…
## $ nombre_ronds_points <dbl> 24, 0, 0, 0, 4, 3, 110, 110, 90, 111, 28…
## $ nombre_eleves <dbl> 1876, 0, 0, 0, 0, 0, 11746, 11746, 11746…
## $ superficie_iso <dbl> 54254703, 23054441, 30342857, 22868178, …
## $ ZA <dbl> 12039533, 12346343, 18463838, 15035247, …
## $ passage_niveau <dbl> 4, 5, 5, 3, 5, 5, 3, 4, 3, 4, 3, 4, 3, 4…
## $ sum_population_carreau_decoup <dbl> 10703.1629, 643.7817, 833.4061, 589.9910…
## $ nombre_arrets_v2 <dbl> 1, 1, 1, 1, 4, 5, 285, 283, 267, 279, 90…
## $ nombre_sante <dbl> 59, 1, 1, 0, 5, 5, 517, 519, 507, 520, 2…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…glimpse(data_car)## Rows: 299
## Columns: 13
## $ ID_number <dbl> 99931, 190774, 190784, 190794, 220137, 2…
## $ sum_population_carreau_decoup <dbl> 0.119990529, 0.007217278, 0.009343111, 0…
## $ nombre_eleves <dbl> 0.15971395, 0.00000000, 0.00000000, 0.00…
## $ nombre_loisirs <dbl> 0.211538462, 0.016025641, 0.019230769, 0…
## $ nombre_sante <dbl> 0.112810707, 0.001912046, 0.001912046, 0…
## $ nombre_commerces <dbl> 0.121703854, 0.010141988, 0.010141988, 0…
## $ nombre_restauration <dbl> 0.105812221, 0.007451565, 0.010432191, 0…
## $ nombre_sports <dbl> 0.11428571, 0.00000000, 0.00000000, 0.00…
## $ ZA <dbl> 0.1988887, 0.2039630, 0.3051397, 0.24843…
## $ passage_niveau <dbl> 0.2857143, 0.3571429, 0.3571429, 0.21428…
## $ total_sum_allegee <dbl> 1.4304585, 0.6038544, 0.7133427, 0.49099…
## $ geom <POINT [m]> POINT (711679.4 6278143), POINT (7…
## $ data_rennes_classes <int> 3, 2, 2, 1, 2, 2, 5, 5, 5, 5, 4, 5, 5, 5…