Cómo leer, filtrar y trazar datos geoespaciales - Departamento del Caquetá

Sandra Katteryne Rodríguez Hurtado

Marzo 21 de 2020

deptos <- read_sf("./COL_adm1.shp")

head(deptos)

Simple feature collection with 6 features and 9 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -77.149 ymin: -4.228429 xmax: -69.36835 ymax: 11.10792
epsg (SRID):    4326
proj4string:    +proj=longlat +datum=WGS84 +no_defs

st_crs(deptos)

Coordinate Reference System:
  EPSG: 4326 
  proj4string: "+proj=longlat +datum=WGS84 +no_defs"

ggplot() + geom_sf(data = deptos) 

ggplot() + geom_sf(data = deptos) + coord_sf(crs=st_crs(3978))

deptos_utm <- st_transform(deptos, crs = st_crs(32618))

deptos_utm

ggplot() + geom_sf(data = deptos_utm)

caquetá <-  deptos %>%   filter(NAME_1 == "Caquetá")

ggplot() + geom_sf(data = caquetá)

munic <-  read_sf("./COL_adm2.shp")
mun_caquetá <- munic %>% filter(NAME_1 == "Caquetá")
ggplot() + geom_sf(data = mun_caquetá) 

mun_caquetá

Simple feature collection with 15 features and 11 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -76.3129 ymin: -0.730099 xmax: -71.4769 ymax: 2.9441
epsg (SRID):    4326
proj4string:    +proj=longlat +datum=WGS84 +no_defs

 caquetá_points <- st_centroid (mun_caquetá)

st_centroid assumes attributes are constant over geometries of xst_centroid does not give correct centroids for longitude/latitude data

caquetá_points <- cbind(mun_caquetá, 
                        st_coordinates(st_centroid(mun_caquetá$geometry)))

st_centroid does not give correct centroids for longitude/latitude data

ggplot(caquetá) +
  geom_sf() +
    geom_sf(data = caquetá_points, fill = "antiquewhite") + 
    geom_text(data = caquetá_points, aes(x=X, y=Y,label = ID_2), size = 2) +
    coord_sf(xlim = c(-76.4, -71.4), ylim = c(-0.8, 3), expand = FALSE)

library(scales)

ggplot(caquetá) + 
  geom_sf(data=caquetá_points, aes(x=X, y=Y, fill =
                                       ID_2), color = "black", size = 0.25) +
  geom_text(data = caquetá_points, aes(x=X, y=Y,label = ID_2), size = 2) +
  theme(aspect.ratio=1)+
  scale_fill_distiller(name="ID_2", palette = "YlGn", breaks = pretty_breaks(n = 5))+
  labs(title="Another  Map of caquetá")

Ignoring unknown aesthetics: x, y

ggsave("caquetá_municipios.pdf")

Saving 7 x 7 in image

ggsave("map_caquetá.png", width = 6, height = 6, dpi = "screen")

install.packages("leaflet")

library(leaflet)

ant_points <- as(caquetá_points, 'Spatial')

head(ant_points)

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CRS arguments: +proj=longlat +datum=WGS84 +no_defs 

install.packages("lwgeom")

Installing package into ‘/home/rstudio-user/R/x86_64-pc-linux-gnu-library/3.6’
(as ‘lib’ is unspecified)
trying URL 'http://package-proxy/src/contrib/lwgeom_0.2-1.tar.gz'
Content type 'application/x-tar' length 1908692 bytes (1.8 MB)
==================================================
downloaded 1.8 MB

* installing *binary* package ‘lwgeom’ ...
* DONE (lwgeom)

The downloaded source packages are in
    ‘/tmp/RtmpYqGuIx/downloaded_packages’

library(lwgeom)

Linking to liblwgeom 3.0.0beta1 r16016, GEOS 3.5.1, PROJ 4.9.2

mun_caquetá$area <- st_area(mun_caquetá)

mun_caquetá$km2 <- mun_caquetá$area/(1000000)

mun_caquetá$km2

Units: [m^2]
 [1]   323.5200   935.3236  8841.8345   474.2438  1735.2031   721.2803
 [7]  2023.9860   891.5957  1193.0877   223.3164  2733.4959   835.9698
[13] 18040.2569 49676.0412  1492.6313

ant_mun <- as(mun_caquetá, 'Spatial')

head(ant_mun)

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Slot "plotOrder":
[1] 1

Slot "labpt":
[1] -75.285882   1.708615

Slot "ID":
[1] "5"

Slot "area":
[1] 0.1410316


[[6]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] -75.417937   1.531032

Slot "area":
[1] 0.058618

Slot "hole":
[1] FALSE

Slot "ringDir":
[1] 1

Slot "coords":
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Slot "plotOrder":
[1] 1

Slot "labpt":
[1] -75.417937   1.531032

Slot "ID":
[1] "6"

Slot "area":
[1] 0.058618



Slot "plotOrder":
[1] 3 5 2 6 4 1

Slot "bbox":
       min        max
x -76.2171 -73.627899
y   0.4108   2.259299

Slot "proj4string":
CRS arguments: +proj=longlat +datum=WGS84 +no_defs 

bins <- c(0, 50, 100, 200, 300, 500, 1000, 2000, Inf)
pal <- colorBin("YlOrRd", domain = ant_mun$km2, bins = bins)


labels <- mun_caquetá$NAME_2

labels

 [1] "Albania"                "Belén de los Andaquies"
 [3] "Cartagena del Chairá"   "Curillo"               
 [5] "El Doncello"            "El Paujíl"             
 [7] "Florencia"              "La Montañita"          
 [9] "Milán"                  "Morelia"               
[11] "Puerto Rico"            "San José del Fragua"   
[13] "San Vicente del Caguán" "Solano"                
[15] "Valparaíso"            

m <- leaflet(ant_mun) %>%
  setView(-73.4, -0.1, 6)  %>% addPolygons(
  fillColor = ~pal(km2),
  weight = 2,
  opacity = 1,
  color = "white",
  dashArray = "3",
  fillOpacity = 0.7,
  highlight = highlightOptions(
    weight = 5,
    color = "#666",
    dashArray = "",
    fillOpacity = 0.7,
    bringToFront = TRUE),
  label = labels) %>%
  addLegend(pal = pal, values = ~km2, opacity = 0.7, title = NULL,
    position = "bottomright")

m

leaflet() %>%
  addProviderTiles(providers$Esri.WorldImagery, options= providerTileOptions(opacity = 0.99)) %>%
  addPolygons(data = ant_mun, popup= ant_mun$NAME_2,
    stroke = TRUE, fillOpacity = 0.25, smoothFactor = 0.25
  )

leaflet() %>%
  addTiles %>% #Add deafault OpenStreetMap map ties 
  addMarkers(lng=-73.628177, lat=4.148539, popup="Villavicencio")

foo <- leaflet() %>% 
    setView(lng =-73.628177, lat =4.148539, zoom = 10) %>%
    addTiles() 

foo %>% addProviderTiles("NASAGIBS.ModisTerraTRUEColorCR")

foo <- leaflet() %>% 
     setView(lng =-73.628177, lat =4.148539, zoom = 7) %>%
     addTiles() 
m %>% addProviderTiles("NASAGIBS.ViirsEarthAtNight2012")