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: 38
## Columns: 27
## $ pk <chr> "0", "1", "2", "3", "4", "5", "6", "7", …
## $ ID_number <int> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population <dbl> 19192, 11350, 11350, 11350, 11350, 11350…
## $ sum_population_active <dbl> 9813.290, 5730.319, 5730.319, 5730.319, …
## $ sum_lits <dbl> 2369, 1111, 1111, 1111, 1111, 1111, 2186…
## $ longueur_route <dbl> 11684.747, 12335.438, 13969.569, 10536.1…
## $ nb_intersections <dbl> 406, 342, 351, 264, 3, 42, 111, 121, 29,…
## $ reseau_pedestre <dbl> 13772.320, 14363.365, 15323.940, 11582.3…
## $ longueur_pistes_cyclables <dbl> 528.01617, 2438.79631, 555.27691, 41.021…
## $ superficie_vegetation <dbl> 89148.47, 53766.71, 33594.98, 103944.57,…
## $ nombre_arrets <dbl> 19, 3, 6, 6, 0, 0, 0, 17, 1, 4, 4, 0, 9,…
## $ nombre_parkings <dbl> 440, 1097, 4, 4, 0, 0, 0, 2, 0, 0, 444, …
## $ nombre_commerces <dbl> 6, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_sante <dbl> 4, 2, 6, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_loisirs <dbl> 5, 2, 1, 6, 0, 0, 3, 5, 0, 0, 0, 0, 0, 0…
## $ nombre_restauration <dbl> 29, 5, 4, 7, 0, 0, 1, 4, 0, 0, 3, 0, 1, …
## $ nombre_sports <dbl> 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0…
## $ nombre_ronds_points <dbl> 4, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0…
## $ nombre_eleves <dbl> 1401, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ superficie_iso <dbl> 562780.7, 670134.3, 793653.0, 615306.9, …
## $ ZA <dbl> 473632.200, 616367.550, 760058.052, 5113…
## $ passage_niveau <dbl> 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0…
## $ sum_population_carreau <dbl> 2201.0, 1678.0, 2422.0, 1652.5, 30.5, 12…
## $ sum_population_carreau_decoup <dbl> 1701.0869643, 876.4670020, 1521.3518608,…
## $ nombre_arrets_v2 <dbl> 6, 2, 2, 2, 0, 0, 0, 3, 1, 1, 1, 0, 2, 0…
## $ pente_moyenne <dbl> 7.402577, 2.806753, 1.535868, 2.723099, …
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…glimpse(data_foot)## Rows: 57
## Columns: 13
## $ ID_number <dbl> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population_carreau_decoup <dbl> 1.0000000000, 0.5152393854, 0.8943410259…
## $ nombre_loisirs <dbl> 0.19230769, 0.07692308, 0.03846154, 0.23…
## $ nombre_commerces <dbl> 0.08108108, 0.01351351, 0.01351351, 0.04…
## $ nombre_restauration <dbl> 0.195945946, 0.033783784, 0.027027027, 0…
## $ nombre_arrets <dbl> 0.44186047, 0.06976744, 0.13953488, 0.13…
## $ longueur_route <dbl> 0.65687515, 0.69345474, 0.78531981, 0.59…
## $ ZA <dbl> 0.61989015, 0.80931129, 1.00000000, 0.66…
## $ passage_niveau <dbl> 0.3333333, 0.3333333, 0.3333333, 0.33333…
## $ pente_moyenne <dbl> 0.19416805, 0.04206195, 0.00000000, 0.03…
## $ total_sum_allegee <dbl> 3.32712577, 2.50326462, 3.23153113, 2.70…
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…
## $ data_rennes_classes <int> 4, 3, 4, 4, 1, 1, 2, 3, 1, 1, 1, 1, 1, 1…glimpse(raw_data_bike)## Rows: 38
## Columns: 27
## $ pk <chr> "0", "1", "2", "3", "4", "5", "6", "7", …
## $ ID_number <int> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population <dbl> 19192, 19192, 19192, 16956, 11350, 15595…
## $ sum_population_active <dbl> 9813.290, 9813.290, 9813.290, 8655.215, …
## $ sum_lits <dbl> 2369, 2369, 2369, 2359, 1111, 2186, 2186…
## $ longueur_route <dbl> 95533.20, 113521.89, 96405.44, 66894.33,…
## $ nb_intersections <dbl> 2174, 2443, 2196, 1465, 515, 413, 404, 3…
## $ reseau_pedestre <dbl> 120823.19, 141910.01, 117847.01, 80005.3…
## $ longueur_pistes_cyclables <dbl> 4389.7309, 4799.3609, 3856.7041, 2882.55…
## $ superficie_vegetation <dbl> 1668364.3, 1974884.3, 1566421.3, 946539.…
## $ nombre_arrets <int> 44, 50, 43, 16, 6, 31, 31, 31, 11, 1, 13…
## $ nombre_parkings <dbl> 6304, 6304, 4771, 3107, 8, 175, 175, 175…
## $ nombre_commerces <dbl> 18, 15, 13, 8, 4, 1, 1, 1, 0, 0, 3, 6, 6…
## $ nombre_sante <dbl> 21, 20, 19, 16, 6, 2, 2, 2, 0, 0, 0, 7, …
## $ nombre_loisirs <int> 28, 35, 27, 16, 7, 11, 11, 11, 1, 1, 6, …
## $ nombre_restauration <int> 49, 52, 50, 24, 10, 11, 11, 10, 5, 2, 11…
## $ nombre_sports <dbl> 5, 5, 5, 3, 0, 2, 2, 2, 0, 0, 2, 3, 3, 1…
## $ nombre_ronds_points <dbl> 16, 14, 10, 4, 1, 3, 3, 3, 1, 0, 1, 1, 1…
## $ nombre_eleves <dbl> 2165, 2165, 2165, 2165, 0, 0, 0, 0, 0, 0…
## $ superficie_iso <dbl> 7723672, 8680399, 7135944, 4860926, 1871…
## $ ZA <dbl> 6055307.6, 6705514.3, 5569522.9, 3914387…
## $ passage_niveau <dbl> 2, 2, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0…
## $ pente_moyenne <dbl> 7.649586, 8.015691, 7.558802, 7.011601, …
## $ sum_population_carreau <dbl> 9227.0, 9739.5, 9135.0, 6605.5, 2826.0, …
## $ sum_population_carreau_decoup <dbl> 8351.1045, 9118.2989, 8490.6815, 5737.87…
## $ nombre_arrets_v2 <int> 16, 18, 15, 7, 2, 7, 7, 7, 5, 1, 4, 7, 6…
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…glimpse(data_bike)## Rows: 57
## Columns: 15
## $ ID_number <dbl> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population_carreau_decoup <dbl> 0.914748199, 1.000000000, 0.930258202, 0…
## $ nombre_eleves <dbl> 1.00000000, 1.00000000, 1.00000000, 1.00…
## $ nombre_loisirs <dbl> 0.55102041, 0.69387755, 0.53061224, 0.30…
## $ nombre_sante <dbl> 0.70000000, 0.66666667, 0.63333333, 0.53…
## $ nombre_commerces <dbl> 0.21428571, 0.17857143, 0.15476190, 0.09…
## $ nombre_restauration <dbl> 0.26256983, 0.27932961, 0.26815642, 0.12…
## $ nombre_sports <dbl> 1.0, 1.0, 1.0, 0.6, 0.0, 0.4, 0.4, 0.4, …
## $ longueur_route <dbl> 0.83883349, 1.00000000, 0.84664818, 0.58…
## $ ZA <dbl> 0.90115122, 1.00000000, 0.82729899, 0.57…
## $ passage_niveau <dbl> 0.250, 0.250, 0.250, 0.250, 0.125, 0.125…
## $ pente_moyenne <dbl> 0.12212038, 0.14649466, 0.11607628, 0.07…
## $ total_sum_allegee <dbl> 6.3826089, 6.8184453, 6.1910693, 4.43988…
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…
## $ data_rennes_classes <int> 5, 5, 5, 4, 2, 2, 2, 2, 1, 1, 2, 3, 3, 1…glimpse(raw_data_car)## Rows: 38
## Columns: 26
## $ pk <chr> "0", "1", "2", "3", "4", "5", "6", "7", …
## $ ID_number <int> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population <dbl> 39355, 42532, 40423, 40423, 16956, 32081…
## $ sum_population_active <dbl> 20183.651, 21927.805, 20811.256, 20811.2…
## $ sum_lits <dbl> 3451, 4520, 3736, 3736, 2359, 9341, 3444…
## $ longueur_route <dbl> 200157.15, 281037.31, 234163.63, 198635.…
## $ nb_intersections <dbl> 3665, 4936, 4174, 3514, 1620, 3331, 3927…
## $ reseau_pedestre <dbl> 292119.1, 424624.3, 345538.4, 296005.3, …
## $ longueur_pistes_cyclables <dbl> 5902.6884, 7633.9495, 7268.6580, 5629.28…
## $ superficie_vegetation <dbl> 7856514, 15124012, 10914373, 10556179, 1…
## $ nombre_arrets <int> 71, 122, 99, 66, 19, 113, 133, 93, 103, …
## $ nombre_parkings <dbl> 10008, 10224, 10000, 7404, 2421, 6696, 6…
## $ nombre_commerces <int> 29, 43, 34, 21, 6, 20, 28, 16, 12, 17, 8…
## $ nombre_sante <dbl> 25, 37, 25, 22, 15, 24, 28, 19, 9, 11, 3…
## $ nombre_loisirs <int> 63, 93, 69, 58, 24, 51, 65, 43, 37, 44, …
## $ nombre_restauration <int> 80, 111, 91, 61, 18, 63, 95, 63, 49, 53,…
## $ nombre_sports <dbl> 6, 8, 7, 7, 3, 9, 10, 7, 7, 7, 9, 8, 8, …
## $ nombre_ronds_points <dbl> 23, 28, 26, 20, 7, 15, 21, 9, 7, 8, 18, …
## $ nombre_eleves <dbl> 2165, 2267, 2267, 2165, 764, 764, 2165, …
## $ superficie_iso <dbl> 23648364, 37675985, 28388217, 24541348, …
## $ ZA <dbl> 15791850, 22551973, 17473844, 13985169, …
## $ passage_niveau <int> 5, 6, 5, 3, 2, 3, 3, 3, 2, 3, 7, 3, 4, 7…
## $ sum_population_carreau <dbl> 13732.0, 20620.0, 15646.5, 13580.0, 6740…
## $ sum_population_carreau_decoup <dbl> 12847.913, 18997.858, 14396.260, 12808.6…
## $ nombre_arrets_v2 <int> 25, 44, 34, 23, 8, 31, 37, 24, 25, 30, 5…
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…glimpse(data_car)## Rows: 57
## Columns: 13
## $ ID_number <dbl> 14074, 14084, 14094, 14104, 14114, 14124…
## $ sum_population_carreau_decoup <dbl> 0.6687829, 1.0000000, 0.7521721, 0.66666…
## $ nombre_eleves <dbl> 0.95500662, 1.00000000, 1.00000000, 0.95…
## $ nombre_loisirs <dbl> 0.6551724, 1.0000000, 0.7241379, 0.59770…
## $ nombre_sante <dbl> 0.625, 0.925, 0.625, 0.550, 0.375, 0.600…
## $ nombre_commerces <dbl> 0.29473684, 0.44210526, 0.34736842, 0.21…
## $ nombre_restauration <dbl> 0.31018519, 0.45370370, 0.36111111, 0.22…
## $ nombre_sports <dbl> 0.6, 0.8, 0.7, 0.7, 0.3, 0.9, 1.0, 0.7, …
## $ ZA <dbl> 0.63101160, 1.00000000, 0.72282002, 0.53…
## $ passage_niveau <dbl> 0.33333333, 0.41666667, 0.33333333, 0.16…
## $ total_sum_allegee <dbl> 5.073229, 7.037476, 5.565943, 4.601186, …
## $ geom <POINT [m]> POINT (986908.4 6540869), POINT (9…
## $ data_rennes_classes <int> 4, 5, 4, 3, 2, 3, 4, 3, 2, 2, 4, 3, 3, 5…