En este segundo cuaderno sera escrito en R markdown. se ilustrara como hacer un mapa como un poligonos(se representan los departamentos de Colombia). el conjunto de datos de referencia es un shapefile proporcionado por el DANE
library(leaflet)
library(rgeos)## Warning: package 'rgeos' was built under R version 4.0.4library(sf)setwd("C:/Users/Juan Narvaez/Documents/geomatica")cities<- read.csv(file = "ciudades.txt",header = F, sep = ";")head(cities)## V1 V2 V3 V4 V5 V6
## 1 2338 Colombi Bogota 4.600000 -74.08334 2620
## 2 2339 Colombi Cali 3.437222 -76.52250 758
## 3 2340 Colombi Medellin 6.291389 -75.53611 2076
## 4 2341 Colombi Barranquilla 10.963889 -74.79639 33
## 5 2342 Colombi Cartagena 10.399722 -75.51444 36
## 6 2343 Colombi Cucuta 7.883333 -72.50528 314names(cities) <- c("id", "Pais","Ciudad", "Latitud", "Longitud", "Altud")
head(cities)## id Pais Ciudad Latitud Longitud Altud
## 1 2338 Colombi Bogota 4.600000 -74.08334 2620
## 2 2339 Colombi Cali 3.437222 -76.52250 758
## 3 2340 Colombi Medellin 6.291389 -75.53611 2076
## 4 2341 Colombi Barranquilla 10.963889 -74.79639 33
## 5 2342 Colombi Cartagena 10.399722 -75.51444 36
## 6 2343 Colombi Cucuta 7.883333 -72.50528 314###Longitud,latidud, altura
m<-st_as_sf(cities,coords=c(5,4,6))
m## Simple feature collection with 100 features and 3 fields
## geometry type: POINT
## dimension: XYZ
## bbox: xmin: -81.70055 ymin: 0.8302778 xmax: -70.76167 ymax: 12.58472
## CRS: NA
## First 10 features:
## id Pais Ciudad geometry
## 1 2338 Colombi Bogota POINT Z (-74.08334 4.6 2620)
## 2 2339 Colombi Cali POINT Z (-76.5225 3.437222 ...
## 3 2340 Colombi Medellin POINT Z (-75.53611 6.291389...
## 4 2341 Colombi Barranquilla POINT Z (-74.79639 10.96389...
## 5 2342 Colombi Cartagena POINT Z (-75.51444 10.39972...
## 6 2343 Colombi Cucuta POINT Z (-72.50528 7.883333...
## 7 2344 Colombi Bucaramanga POINT Z (-73.12583 7.129722...
## 8 2345 Colombi Pereira POINT Z (-75.69611 4.813333...
## 9 2346 Colombi Santa Marta POINT Z (-74.20167 11.24722 9)
## 10 2347 Colombi Ibague POINT Z (-75.23222 4.438889...(coords<- st_coordinates(m))## X Y Z
## 1 -74.08334 4.6000000 2620
## 2 -76.52250 3.4372222 758
## 3 -75.53611 6.2913889 2076
## 4 -74.79639 10.9638889 33
## 5 -75.51444 10.3997222 36
## 6 -72.50528 7.8833333 314
## 7 -73.12583 7.1297222 967
## 8 -75.69611 4.8133333 1445
## 9 -74.20167 11.2472222 9
## 10 -75.23222 4.4388889 1082
## 11 -75.56223 6.3388889 1489
## 12 -77.28111 1.2136111 2569
## 13 -75.52055 5.0700000 1935
## 14 -75.33028 2.9305556 507
## 15 -74.76667 10.9172222 10
## 16 -73.63500 4.1533333 529
## 17 -75.68111 4.5338889 1349
## 18 -74.22139 4.5872222 2413
## 19 -73.25056 10.4769444 163
## 20 -75.61139 6.1719444 1637
## 21 -75.89000 8.7575000 25
## 22 -75.39778 9.3047222 219
## 23 -73.08972 7.0647222 1026
## 24 -76.30361 3.5394444 863
## 25 -77.06973 3.8933333 1
## 26 -73.85472 7.0652778 45
## 27 -75.67250 4.8347222 1500
## 28 -76.20000 4.0866667 766
## 29 -75.56389 6.1730556 1784
## 30 -75.91167 4.7463889 722
## 31 -72.24416 11.3841667 44
## 32 -75.61750 1.6175000 579
## 33 -74.80083 4.3030556 328
## 34 -72.92973 5.7205556 2419
## 35 -76.30278 3.9022222 722
## 36 -73.36777 5.5352778 2717
## 37 -73.17306 7.0708333 712
## 38 -74.77306 10.8588889 5
## 39 -74.75333 9.2413889 18
## 40 -74.36667 4.8166667 2816
## 41 -72.90722 11.5444444 5
## 42 -73.02028 5.8269444 2501
## 43 -74.00584 5.0283333 2656
## 44 -74.36777 4.3438889 1745
## 45 -74.25417 11.0094444 12
## 46 -78.81556 1.7986111 1
## 47 -76.63472 7.8855556 57
## 48 -73.05361 6.9894444 1080
## 49 -73.35778 8.2363889 1272
## 50 -74.66917 5.4522222 152
## 51 -77.64445 0.8302778 2954
## 52 -76.66111 5.6947222 67
## 53 -73.62695 8.3125000 151
## 54 -76.49583 3.5850000 991
## 55 -70.76167 7.0902778 119
## 56 -74.92278 10.6377778 88
## 57 -75.60361 4.9825000 1488
## 58 -75.63750 6.0900000 1929
## 59 -72.47417 7.8338889 381
## 60 -74.06667 4.8666667 2325
## 61 -75.38889 6.1552778 2058
## 62 -75.64361 4.5325000 1459
## 63 -72.39417 5.3394444 426
## 64 -75.44778 8.9494444 72
## 65 -74.18667 10.5213889 55
## 66 -72.51334 7.8383333 385
## 67 -81.70055 12.5847222 -9999
## 68 -75.19722 7.9869444 65
## 69 -75.62139 4.8680556 1827
## 70 -74.88861 4.1527778 329
## 71 -75.40833 10.3294444 129
## 72 -75.79667 8.8855556 15
## 73 -73.97806 9.0047222 21
## 74 -74.21667 4.7166667 2276
## 75 -76.05639 1.8675000 1319
## 76 -76.41944 3.2336111 847
## 77 -72.65250 7.3780556 2516
## 78 -73.23889 10.0358333 183
## 79 -76.73167 8.0980556 7
## 80 -74.26833 4.7344444 2400
## 81 -75.34389 10.2544444 58
## 82 -75.64694 6.1605556 1887
## 83 -75.51305 6.3488889 1498
## 84 -74.78722 9.7919444 18
## 85 -76.68639 7.6769444 109
## 86 -75.13306 9.7222222 154
## 87 -76.23861 3.3275000 894
## 88 -73.82000 5.6188889 2713
## 89 -76.54444 3.2638889 890
## 90 -76.24472 3.4211111 912
## 91 -74.91833 10.7997222 124
## 92 -75.93611 4.2688889 1394
## 93 -76.48666 3.0130556 1061
## 94 -74.81194 7.5941667 51
## 95 -73.75667 3.9875000 579
## 96 -75.81973 9.2316667 7
## 97 -74.70361 7.0833333 638
## 98 -75.29583 9.3177778 154
## 99 -76.31667 3.6880556 851
## 100 -75.58833 8.4147222 113###latitud=y , longitud= x , alt= z
lat= coords[,2]
long= coords[,1]
alt= coords[,3]long## 1 2 3 4 5 6 7 8
## -74.08334 -76.52250 -75.53611 -74.79639 -75.51444 -72.50528 -73.12583 -75.69611
## 9 10 11 12 13 14 15 16
## -74.20167 -75.23222 -75.56223 -77.28111 -75.52055 -75.33028 -74.76667 -73.63500
## 17 18 19 20 21 22 23 24
## -75.68111 -74.22139 -73.25056 -75.61139 -75.89000 -75.39778 -73.08972 -76.30361
## 25 26 27 28 29 30 31 32
## -77.06973 -73.85472 -75.67250 -76.20000 -75.56389 -75.91167 -72.24416 -75.61750
## 33 34 35 36 37 38 39 40
## -74.80083 -72.92973 -76.30278 -73.36777 -73.17306 -74.77306 -74.75333 -74.36667
## 41 42 43 44 45 46 47 48
## -72.90722 -73.02028 -74.00584 -74.36777 -74.25417 -78.81556 -76.63472 -73.05361
## 49 50 51 52 53 54 55 56
## -73.35778 -74.66917 -77.64445 -76.66111 -73.62695 -76.49583 -70.76167 -74.92278
## 57 58 59 60 61 62 63 64
## -75.60361 -75.63750 -72.47417 -74.06667 -75.38889 -75.64361 -72.39417 -75.44778
## 65 66 67 68 69 70 71 72
## -74.18667 -72.51334 -81.70055 -75.19722 -75.62139 -74.88861 -75.40833 -75.79667
## 73 74 75 76 77 78 79 80
## -73.97806 -74.21667 -76.05639 -76.41944 -72.65250 -73.23889 -76.73167 -74.26833
## 81 82 83 84 85 86 87 88
## -75.34389 -75.64694 -75.51305 -74.78722 -76.68639 -75.13306 -76.23861 -73.82000
## 89 90 91 92 93 94 95 96
## -76.54444 -76.24472 -74.91833 -75.93611 -76.48666 -74.81194 -73.75667 -75.81973
## 97 98 99 100
## -74.70361 -75.29583 -76.31667 -75.58833###ubicacion de los departamentos
list.files("MGN2020_DPTO_POLITICO")## [1] "MGN_DPTO_POLITICO.CPG" "MGN_DPTO_POLITICO.dbf"
## [3] "MGN_DPTO_POLITICO.prj" "MGN_DPTO_POLITICO.sbn"
## [5] "MGN_DPTO_POLITICO.sbx" "MGN_DPTO_POLITICO.shp"
## [7] "MGN_DPTO_POLITICO.shp.xml" "MGN_DPTO_POLITICO.shx"departament<-read_sf("MGN2020_DPTO_POLITICO/MGN_DPTO_POLITICO.shp")st_crs(departament)## Coordinate Reference System:
## User input: WGS 84
## wkt:
## GEOGCRS["WGS 84",
## DATUM["World Geodetic System 1984",
## ELLIPSOID["WGS 84",6378137,298.257223563,
## LENGTHUNIT["metre",1]]],
## PRIMEM["Greenwich",0,
## ANGLEUNIT["degree",0.0174532925199433]],
## CS[ellipsoidal,2],
## AXIS["latitude",north,
## ORDER[1],
## ANGLEUNIT["degree",0.0174532925199433]],
## AXIS["longitude",east,
## ORDER[2],
## ANGLEUNIT["degree",0.0174532925199433]],
## ID["EPSG",4326]]head(departament)## Simple feature collection with 6 features and 7 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -77.92834 ymin: -0.70584 xmax: -66.84722 ymax: 6.324317
## geographic CRS: WGS 84
## # A tibble: 6 x 8
## DPTO_CCDGO DPTO_CNMBR DPTO_NANO_ DPTO_CACTO DPTO_NANO SHAPE_AREA SHAPE_LEN
## <chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 18 CAQUETÁ 1981 Ley 78 de~ 2020 7.32 21.4
## 2 19 CAUCA 1857 15 de jun~ 2020 2.53 14.0
## 3 86 PUTUMAYO 1991 Articulo ~ 2020 2.11 12.7
## 4 76 VALLE DEL~ 1910 Decreto N~ 2020 1.68 12.7
## 5 94 GUAINÍA 1991 Articulo ~ 2020 5.75 21.2
## 6 99 VICHADA 1991 5 de Juli~ 2020 8.10 17.3
## # ... with 1 more variable: geometry <MULTIPOLYGON [°]>departament$DPTO_CNMBR## [1] "CAQUETÁ"
## [2] "CAUCA"
## [3] "PUTUMAYO"
## [4] "VALLE DEL CAUCA"
## [5] "GUAINÍA"
## [6] "VICHADA"
## [7] "CASANARE"
## [8] "AMAZONAS"
## [9] "VAUPÉS"
## [10] "GUAVIARE"
## [11] "CALDAS"
## [12] "QUINDIO"
## [13] "RISARALDA"
## [14] "ANTIOQUIA"
## [15] "CHOCÓ"
## [16] "NARIÑO"
## [17] "CÓRDOBA"
## [18] "BOLÍVAR"
## [19] "CESAR"
## [20] "LA GUAJIRA"
## [21] "MAGDALENA"
## [22] "SUCRE"
## [23] "ARCHIPIÉLAGO DE SAN ANDRÉS, PROVIDENCIA Y SANTA CATALINA"
## [24] "ARAUCA"
## [25] "BOYACÁ"
## [26] "CUNDINAMARCA"
## [27] "NORTE DE SANTANDER"
## [28] "BOGOTÁ, D.C."
## [29] "META"
## [30] "HUILA"
## [31] "SANTANDER"
## [32] "TOLIMA"
## [33] "ATLÁNTICO"departament2<- departament %>% st_transform(3116)
departament3<- st_simplify(departament2,preserveTopology = T ,dTolerance = 100) object.size(departament)## 16290112 bytesdepartament4<- departament3 %>% st_transform(4326)###mapas de los departamentos de Colombia
map<- leaflet(departament4)
map<- addTiles(map)labels <- sprintf(
"<strong>%s</strong><br/>% g unkown units </sup>",
departament4$DPTO_CNMBR, departament4$SHAPE_AREA
) %>% lapply(htmltools::HTML)##map<- addMarkers(map , lng= long, lat = lat , popup = m$Ciudad)map<- addPolygons(map,color = "#444444",weight = 1, smoothFactor = 0.5,opacity = 1.0, fillColor = ~colorQuantile("YlOrRd", SHAPE_AREA)(SHAPE_AREA), highlightOptions = highlightOptions(color = "blue", weight = 2,
bringToFront = TRUE),label = labels,labelOptions = labelOptions(
style = list("font-weight" = "normal", padding= "3px 8px"),textsize = "15px",
direction = "auto"))
map<- addMarkers(map , lng= long, lat = lat , popup = m$Ciudad)
map sessionInfo()## R version 4.0.3 (2020-10-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19042)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Spanish_Colombia.1252 LC_CTYPE=Spanish_Colombia.1252
## [3] LC_MONETARY=Spanish_Colombia.1252 LC_NUMERIC=C
## [5] LC_TIME=Spanish_Colombia.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] sf_0.9-6 rgeos_0.5-5 sp_1.4-2 leaflet_2.0.4.1
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.5 RColorBrewer_1.1-2 compiler_4.0.3 pillar_1.4.6
## [5] class_7.3-17 tools_4.0.3 digest_0.6.25 jsonlite_1.7.0
## [9] evaluate_0.14 lifecycle_0.2.0 tibble_3.0.3 lattice_0.20-41
## [13] pkgconfig_2.0.3 rlang_0.4.7 cli_2.0.2 DBI_1.1.0
## [17] crosstalk_1.1.0.1 yaml_2.2.1 xfun_0.16 e1071_1.7-3
## [21] stringr_1.4.0 dplyr_1.0.2 knitr_1.29 generics_0.0.2
## [25] htmlwidgets_1.5.1 vctrs_0.3.2 tidyselect_1.1.0 classInt_0.4-3
## [29] grid_4.0.3 glue_1.4.1 R6_2.4.1 fansi_0.4.1
## [33] rmarkdown_2.3 farver_2.0.3 purrr_0.3.4 magrittr_1.5
## [37] scales_1.1.1 htmltools_0.5.0 ellipsis_0.3.1 units_0.6-7
## [41] assertthat_0.2.1 colorspace_1.4-1 utf8_1.1.4 KernSmooth_2.23-17
## [45] stringi_1.4.6 munsell_0.5.0 crayon_1.3.4