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: 62
## Columns: 27
## $ pk <chr> "355", "372", "373", "0", "1", "2", "3",…
## $ ID_number <int> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population <dbl> 12016, 222485, 222485, 12016, 12016, 120…
## $ sum_population_active <dbl> 4882.2489, 105532.2246, 105532.2246, 488…
## $ sum_lits <dbl> 132, 3947, 3947, 132, 132, 132, 132, 0, …
## $ longueur_route <dbl> 11616.2283, 1641.0155, 3320.8521, 11530.…
## $ nb_intersections <dbl> 307, 57, 58, 415, 14, 20, 28, 24, 17, 6,…
## $ reseau_pedestre <dbl> 12929.695, 2270.085, 4169.607, 13503.413…
## $ longueur_pistes_cyclables <dbl> 2788.82654, 0.00000, 1010.40256, 2481.10…
## $ superficie_vegetation <dbl> 139364.053, 20276.108, 3587.067, 95503.4…
## $ nombre_arrets <dbl> 17, 28, 232, 17, 0, 1, 0, 1, 0, 0, 0, 0,…
## $ nombre_parkings <dbl> 512, 0, 4, 735, 2, 0, 0, 0, 0, 0, 0, 0, …
## $ nombre_commerces <dbl> 6, 0, 6, 37, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ nombre_sante <dbl> 9, 0, 15, 21, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ nombre_loisirs <dbl> 5, 1, 35, 6, 1, 1, 0, 0, 0, 0, 0, 0, 0, …
## $ nombre_restauration <dbl> 6, 2, 40, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ nombre_sports <dbl> 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_ronds_points <dbl> 5, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_eleves <dbl> 0, 542, 0, 451, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ superficie_iso <dbl> 721265.0, 146972.4, 285530.9, 642813.6, …
## $ ZA <dbl> 581900.94, 126696.30, 281943.82, 547310.…
## $ passage_niveau <dbl> 2, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0…
## $ sum_population_carreau <dbl> 2609.5, 1566.5, 3495.0, 2687.0, 305.0, 2…
## $ sum_population_carreau_decoup <dbl> 1370.363560, 329.510221, 1259.685966, 14…
## $ nombre_arrets_v2 <dbl> 4, 0, 9, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ pente_moyenne <dbl> 4.5633779, 4.0261046, 3.0796428, 4.01364…
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…glimpse(data_foot)## Rows: 72
## Columns: 13
## $ ID_number <dbl> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population_carreau_decoup <dbl> 0.5596334980, 0.1345664485, 0.5144346244…
## $ nombre_loisirs <dbl> 0.14285714, 0.02857143, 1.00000000, 0.17…
## $ nombre_commerces <dbl> 0.1621622, 0.0000000, 0.1621622, 1.00000…
## $ nombre_restauration <dbl> 0.150, 0.050, 1.000, 0.775, 0.000, 0.000…
## $ nombre_arrets <dbl> 0.073275862, 0.120689655, 1.000000000, 0…
## $ longueur_route <dbl> 0.76397701, 0.10792643, 0.21840606, 0.75…
## $ ZA <dbl> 0.751088265, 0.116545622, 0.332956349, 0…
## $ passage_niveau <dbl> 1.0, 0.0, 0.0, 0.5, 0.0, 0.0, 0.0, 0.0, …
## $ pente_moyenne <dbl> 0.46652428, 0.39917016, 0.28051902, 0.39…
## $ total_sum_allegee <dbl> 3.13646966, 0.15912943, 3.94744018, 4.17…
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…
## $ data_rennes_classes <int> 4, 1, 4, 4, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1…glimpse(raw_data_bike)## Rows: 62
## Columns: 27
## $ pk <chr> "355", "372", "373", "0", "1", "2", "3",…
## $ ID_number <int> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population <dbl> 17057, 222485, 222485, 15061, 12016, 161…
## $ sum_population_active <dbl> 7251.479, 105532.225, 105532.225, 6330.1…
## $ sum_lits <dbl> 159, 3947, 3947, 159, 132, 132, 132, 132…
## $ longueur_route <dbl> 114095.047, 24828.755, 36760.471, 109967…
## $ nb_intersections <dbl> 2885, 666, 1052, 2902, 727, 841, 271, 18…
## $ reseau_pedestre <dbl> 146565.314, 28006.752, 39392.019, 134332…
## $ longueur_pistes_cyclables <dbl> 9983.64776, 2350.30288, 5616.75406, 1020…
## $ superficie_vegetation <dbl> 1844624.80, 84018.76, 61196.25, 1566032.…
## $ nombre_arrets <dbl> 18, 226, 424, 18, 3, 3, 1, 1, 1, 1, 1, 1…
## $ nombre_parkings <dbl> 14585, 2, 6, 15967, 358, 356, 2, 0, 0, 0…
## $ nombre_commerces <dbl> 73, 23, 66, 73, 30, 31, 0, 0, 0, 0, 1, 1…
## $ nombre_sante <dbl> 77, 50, 100, 45, 12, 13, 1, 0, 0, 0, 0, …
## $ nombre_loisirs <dbl> 28, 106, 227, 25, 18, 18, 3, 4, 3, 3, 0,…
## $ nombre_restauration <dbl> 57, 63, 196, 55, 16, 23, 1, 0, 0, 0, 1, …
## $ nombre_sports <dbl> 5, 2, 5, 5, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0…
## $ nombre_ronds_points <dbl> 34, 4, 8, 37, 11, 11, 3, 0, 3, 0, 3, 3, …
## $ nombre_eleves <dbl> 4062, 1078, 2597, 4062, 2234, 2234, 2234…
## $ superficie_iso <dbl> 11422523.9, 1607494.8, 2018061.8, 979788…
## $ ZA <dbl> 9577899.1, 1523476.0, 1956865.6, 8231857…
## $ passage_niveau <dbl> 9, 0, 0, 9, 5, 6, 1, 2, 1, 1, 1, 1, 1, 1…
## $ pente_moyenne <dbl> 3.042699, 2.762677, 2.723018, 3.164370, …
## $ sum_population_carreau <dbl> 10715.5, 17755.0, 21727.0, 10436.0, 3860…
## $ sum_population_carreau_decoup <dbl> 10370.745101, 11296.763859, 14803.934220…
## $ nombre_arrets_v2 <dbl> 4, 16, 26, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…glimpse(data_bike)## Rows: 72
## Columns: 15
## $ ID_number <dbl> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population_carreau_decoup <dbl> 0.589393240, 0.642051449, 0.841487269, 0…
## $ nombre_eleves <dbl> 1.00000000, 0.26538651, 0.63934023, 1.00…
## $ nombre_loisirs <dbl> 0.12334802, 0.46696035, 1.00000000, 0.11…
## $ nombre_sante <dbl> 0.77, 0.50, 1.00, 0.45, 0.12, 0.13, 0.01…
## $ nombre_commerces <dbl> 1.00000000, 0.31506849, 0.90410959, 1.00…
## $ nombre_restauration <dbl> 0.290816327, 0.321428571, 1.000000000, 0…
## $ nombre_sports <dbl> 0.5555556, 0.2222222, 0.5555556, 0.55555…
## $ longueur_route <dbl> 1.00000000, 0.20315466, 0.30966443, 0.96…
## $ ZA <dbl> 1.00000000, 0.15088194, 0.19657098, 0.85…
## $ passage_niveau <dbl> 1.0000000, 0.0000000, 0.0000000, 1.00000…
## $ pente_moyenne <dbl> 0.33619544, 0.27836770, 0.27017760, 0.36…
## $ total_sum_allegee <dbl> 6.32911314, 3.08715419, 6.44672805, 5.78…
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…
## $ data_rennes_classes <int> 5, 3, 5, 4, 3, 3, 2, 1, 1, 1, 1, 1, 1, 1…glimpse(raw_data_car)## Rows: 62
## Columns: 26
## $ pk <chr> "355", "372", "373", "0", "1", "2", "3",…
## $ ID_number <int> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population <dbl> 23661, 279599, 271310, 22977, 19799, 202…
## $ sum_population_active <dbl> 10346.139, 133851.522, 129798.522, 9991.…
## $ sum_lits <dbl> 159, 5344, 5266, 159, 159, 159, 198, 198…
## $ longueur_route <dbl> 323207.352, 629613.379, 500753.017, 3263…
## $ nb_intersections <dbl> 5117, 17262, 14166, 5113, 3180, 3983, 48…
## $ reseau_pedestre <dbl> 475773.58, 819978.81, 625496.41, 476367.…
## $ longueur_pistes_cyclables <dbl> 20440.8604, 80915.6384, 62906.0918, 1950…
## $ superficie_vegetation <dbl> 12183716, 5977939, 3547182, 12482655, 34…
## $ nombre_arrets <int> 18, 2202, 2137, 18, 18, 18, 18, 18, 1, 1…
## $ nombre_parkings <dbl> 16883, 20540, 12254, 16883, 15074, 16460…
## $ nombre_commerces <dbl> 84, 659, 663, 84, 68, 77, 81, 80, 5, 2, …
## $ nombre_sante <dbl> 81, 690, 818, 81, 78, 80, 82, 85, 4, 1, …
## $ nombre_loisirs <dbl> 43, 987, 1181, 42, 30, 32, 42, 38, 11, 5…
## $ nombre_restauration <dbl> 65, 1034, 1151, 65, 57, 62, 63, 63, 6, 2…
## $ nombre_sports <dbl> 6, 31, 29, 6, 5, 6, 6, 6, 0, 0, 0, 0, 0,…
## $ nombre_ronds_points <dbl> 46, 180, 91, 45, 34, 41, 43, 44, 9, 5, 4…
## $ nombre_eleves <dbl> 4062, 23260, 26209, 4062, 4062, 4062, 40…
## $ superficie_iso <dbl> 94582972, 39490882, 27334904, 106789341,…
## $ ZA <dbl> 82399256, 33512943, 23787722, 94306686, …
## $ passage_niveau <int> 15, 2, 1, 15, 10, 11, 11, 11, 4, 1, 5, 2…
## $ sum_population_carreau <dbl> 15868.0, 148112.0, 154493.0, 15966.5, 11…
## $ sum_population_carreau_decoup <dbl> 15675.09494, 140673.64831, 148359.72176,…
## $ nombre_arrets_v2 <dbl> 4, 211, 202, 4, 4, 4, 4, 4, 0, 0, 0, 0, …
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…glimpse(data_car)## Rows: 72
## Columns: 13
## $ ID_number <dbl> 26592, 45915, 45925, 132896, 132906, 132…
## $ sum_population_carreau_decoup <dbl> 0.096025538, 0.866488141, 0.913863347, 0…
## $ nombre_eleves <dbl> 0.13856388, 0.79345045, 0.89404742, 0.13…
## $ nombre_loisirs <dbl> 0.036409822, 0.835732430, 1.000000000, 0…
## $ nombre_sante <dbl> 0.087757313, 0.747562297, 0.886240520, 0…
## $ nombre_commerces <dbl> 0.113360324, 0.889338731, 0.894736842, 0…
## $ nombre_restauration <dbl> 0.0564726325, 0.8983492615, 1.0000000000…
## $ nombre_sports <dbl> 0.1538462, 0.7948718, 0.7435897, 0.15384…
## $ ZA <dbl> 0.86496595, 0.33047919, 0.22415082, 0.99…
## $ passage_niveau <dbl> 1.00000000, 0.07142857, 0.00000000, 1.00…
## $ total_sum_allegee <dbl> 2.54740161, 6.22770087, 6.55662869, 2.67…
## $ geom <POINT [m]> POINT (372535.6 6744710), POINT (3…
## $ data_rennes_classes <int> 3, 5, 5, 3, 2, 2, 3, 2, 1, 1, 1, 1, 1, 1…