Segundo cuaderno de R notebook. representara como hacer un mapa con poligonos.
library(rgeos)## Warning: package 'rgeos' was built under R version 4.0.4## Loading required package: sp## rgeos version: 0.5-5, (SVN revision 640)
## GEOS runtime version: 3.8.0-CAPI-1.13.1
## Linking to sp version: 1.4-5
## Polygon checking: TRUElibrary(sf)## Warning: package 'sf' was built under R version 4.0.4## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1library(leaflet)## Warning: package 'leaflet' was built under R version 4.0.3# usando la tabla anterior de ciudades
ciudades= read.csv(file = 'colombi.txt', header = F, sep= ";" )
ciudadesnames(ciudades)= c("id", "pais", "ciudad", "latitud","longitud", "altitud")
ciudadesmap= st_as_sf(ciudades, coords = c(5,4,6))
map#podemos extraer unicamente las coordenadas
coords= st_coordinates(map); coords## 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
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## 8 -75.69611 4.8133333 1445
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## 10 -75.23222 4.4388889 1082
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## 13 -75.52055 5.0700000 1935
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## 93 -76.48666 3.0130556 1061
## 94 -74.81194 7.5941667 51
## 95 -73.75667 3.9875000 579
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## 98 -75.29583 9.3177778 154
## 99 -76.31667 3.6880556 851
## 100 -75.58833 8.4147222 113#crear un vector de cada coordenada
lat= coords[,2]
long= coords[,1]
alt=coords[,3]list.files("departamentos1")## [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"
## [9] "MGN2020_DPTO_POLITICO.rar"deptos= read_sf("../geomatica/departamentos1/MGN_DPTO_POLITICO.shp"); deptosclass(deptos) #Conocer el tipo de archivos## [1] "sf" "tbl_df" "tbl" "data.frame"st_crs(deptos)# conocer que tipo de coordenadas y parametros de elipsoide. ## 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(deptos)deptos$DPTO_CNMBR## [1] "CAQUETÁ"
## [2] "CAUCA"
## [3] "PUTUMAYO"
## [4] "VALLE DEL CAUCA"
## [5] "GUAINÍA"
## [6] "VICHADA"
## [7] "CASANARE"
## [8] "AMAZONAS"
## [9] "VAUPÉS"
## [10] "GUAVIARE"
## [11] "CALDAS"
## [12] "QUINDIO"
## [13] "RISARALDA"
## [14] "ANTIOQUIA"
## [15] "CHOCÓ"
## [16] "NARIÑO"
## [17] "CÓRDOBA"
## [18] "BOLÍVAR"
## [19] "CESAR"
## [20] "LA GUAJIRA"
## [21] "MAGDALENA"
## [22] "SUCRE"
## [23] "ARCHIPIÉLAGO DE SAN ANDRÉS, PROVIDENCIA Y SANTA CATALINA"
## [24] "ARAUCA"
## [25] "BOYACÁ"
## [26] "CUNDINAMARCA"
## [27] "NORTE DE SANTANDER"
## [28] "BOGOTÁ, D.C."
## [29] "META"
## [30] "HUILA"
## [31] "SANTANDER"
## [32] "TOLIMA"
## [33] "ATLÁNTICO"# Para reducir el trabajo de memoria. se puede generalizar las lineas que conforman los limites de los departamentos. solo se puede haecr con coordenadas planas. por lo que es necesario proyectar los departamentos ( comvertir coordenadas geograficas a planas)
deptos2= deptos %>% st_transform(3116)
deptos3= st_simplify(deptos2, preserveTopology = T, dTolerance = 50) #el parametro preservar topologia es importante para mantener a los poligonos sin superponerse, la tolerancia tambien se puede ampliar o reducir
# Leafleat trabaja con datos geograficos en sistema de coordenadas CRS WGS84 por lo que necesiamos transformar el objeto simplificado a coordenadas geograficas.
deptos4= deptos3 %>% st_transform(4326)map= leaflet(deptos4) %>% addTiles()
labels= sprintf("<strong>%s</strong><br/>%g unknow units</sup>", deptos4$DPTO_CNMBR, deptos4$SHAPE_AREA) %>% lapply(htmltools::HTML) #lista que se puede representra en un archivo HTML
map= addPolygons(map, color = "#444444", weight = 1, smoothFactor = 0.5, opacity = 1.0, fillOpacity = 0.5, fillColor = ~colorQuantile("BrBG", SHAPE_AREA)(SHAPE_AREA), highlightOptions = highlightOptions(color = "orange", weight = 2, bringToFront = T), label = labels,labelOptions = labelOptions(style = list("font-weight"= "normal", padding= "3px 8px"), textsize = "15px", direction = "auto"))
#se añaden marcadores
map= addMarkers(map, lng = long,lat=lat, popup = map$ciudad)
mapsessionInfo()## R version 4.0.2 (2020-06-22)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19041)
##
## 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] leaflet_2.0.4.1 sf_0.9-7 rgeos_0.5-5 sp_1.4-2
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.5 RColorBrewer_1.1-2 compiler_4.0.2 pillar_1.4.6
## [5] class_7.3-17 tools_4.0.2 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 DBI_1.1.1 crosstalk_1.1.0.1
## [17] yaml_2.2.1 xfun_0.16 e1071_1.7-4 dplyr_1.0.2
## [21] stringr_1.4.0 knitr_1.29 generics_0.0.2 vctrs_0.3.3
## [25] htmlwidgets_1.5.2 classInt_0.4-3 grid_4.0.2 tidyselect_1.1.0
## [29] glue_1.4.1 R6_2.4.1 rmarkdown_2.3 farver_2.0.3
## [33] purrr_0.3.4 magrittr_1.5 scales_1.1.1 htmltools_0.5.0
## [37] ellipsis_0.3.1 units_0.7-0 colorspace_1.4-1 KernSmooth_2.23-17
## [41] stringi_1.4.6 munsell_0.5.0 crayon_1.3.4