Este cuaderno tiene la finalidad de ilustrar y representar una interpolación espacial usando un conjunto de datos de precipitación mensual sobre el departamento de Boyaca.
rm(list=ls())library(sf)## Linking to GEOS 3.9.1, GDAL 3.3.2, PROJ 7.2.1; sf_use_s2() is TRUElibrary(rgdal)## Loading required package: sp## Please note that rgdal will be retired by the end of 2023,
## plan transition to sf/stars/terra functions using GDAL and PROJ
## at your earliest convenience.
##
## rgdal: version: 1.5-32, (SVN revision 1176)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.4.3, released 2022/04/22
## Path to GDAL shared files: C:/Users/GERARDO/AppData/Local/R/win-library/4.2/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721]
## Path to PROJ shared files: C:/Users/GERARDO/AppData/Local/R/win-library/4.2/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.5-0
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal.library(rasterVis)## Loading required package: latticelibrary(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(raster)##
## Attaching package: 'raster'## The following object is masked from 'package:dplyr':
##
## selectlibrary(gstat)
library(berryFunctions)##
## Attaching package: 'berryFunctions'## The following object is masked from 'package:raster':
##
## distance## The following object is masked from 'package:dplyr':
##
## between(boyaca <- st_read("C:/Users/GERARDO/Desktop/GB2022/Datos/15_BOYACA/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp"))## Reading layer `MGN_MPIO_POLITICO' from data source
## `C:\Users\GERARDO\Desktop\GB2022\Datos\15_BOYACA\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 123 features and 9 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -74.66496 ymin: 4.655196 xmax: -71.94885 ymax: 7.055557
## Geodetic CRS: WGS 84## Simple feature collection with 123 features and 9 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -74.66496 ymin: 4.655196 xmax: -71.94885 ymax: 7.055557
## Geodetic CRS: WGS 84
## First 10 features:
## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## 1 15 15001 TUNJA 1541
## 2 15 15022 ALMEIDA 1908
## 3 15 15047 AQUITANIA 1789
## 4 15 15051 ARCABUCO 1856
## 5 15 15087 BELÉN 1756
## 6 15 15090 BERBEO Ordenanza 28 de Abril 9 de 1913
## 7 15 15092 BETÉITIVA 1754
## 8 15 15097 BOAVITA 1613
## 9 15 15104 BOYACÁ 1537
## 10 15 15106 BRICEÑO Ordenanza 14 del 25 de Julio de 1890
## MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area
## 1 119.68957 2017 BOYACÁ 0.5723744 0.009766301
## 2 57.67212 2017 BOYACÁ 0.3484692 0.004701759
## 3 942.14660 2017 BOYACÁ 1.8003115 0.076843504
## 4 137.89859 2017 BOYACÁ 0.7527090 0.011256738
## 5 163.08822 2017 BOYACÁ 0.6293489 0.013314920
## 6 58.01301 2017 BOYACÁ 0.4291743 0.004730850
## 7 101.89955 2017 BOYACÁ 0.4738184 0.008317810
## 8 145.30529 2017 BOYACÁ 0.6597822 0.011867743
## 9 48.02287 2017 BOYACÁ 0.3256140 0.003918022
## 10 64.59970 2017 BOYACÁ 0.4849753 0.005273255
## geometry
## 1 POLYGON ((-73.34014 5.58308...
## 2 POLYGON ((-73.36793 5.01349...
## 3 POLYGON ((-72.76242 5.63856...
## 4 POLYGON ((-73.50487 5.84347...
## 5 POLYGON ((-72.91692 6.08612...
## 6 POLYGON ((-73.0677 5.27048,...
## 7 POLYGON ((-72.81796 5.97422...
## 8 POLYGON ((-72.64907 6.43640...
## 9 POLYGON ((-73.34806 5.47411...
## 10 POLYGON ((-73.89118 5.73749...(precip <- raster("C:/Users/GERARDO/Desktop/GB2022/Datos/rep_boyaca_dem.tif"))## class : RasterLayer
## dimensions : 680, 288, 195840 (nrow, ncol, ncell)
## resolution : 180, 180 (x, y)
## extent : 560865, 612705, 412335, 534735 (xmin, xmax, ymin, ymax)
## crs : +proj=utm +zone=18 +datum=WGS84 +units=m +no_defs
## source : rep_boyaca_dem.tif
## names : rep_boyaca_dem
## values : -258, 4201 (min, max)names(precip) <- "X2019.07"library(leaflet)
library(RColorBrewer)
pal <- colorNumeric(c("red", "orange", "#fcc000","yellow", "cyan", "blue", "#3240cd"), values(precip$X2019.07),
na.color = "transparent")
leaflet() %>% addTiles() %>%
addRasterImage(precip$X2019.07 , colors = pal, opacity = 0.8) %>%
addLegend(pal = pal, values = values(precip$X2019.07),
title = "Rainfall-Jul.2019 [mm]")## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
## prefer_proj): Discarded ellps WGS 84 in Proj4 definition: +proj=merc +a=6378137
## +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null
## +wktext +no_defs +type=crs## Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
## prefer_proj): Discarded datum World Geodetic System 1984 in Proj4 definition(precip.mask <- mask(x = precip, mask = boyaca))## class : RasterLayer
## dimensions : 680, 288, 195840 (nrow, ncol, ncell)
## resolution : 180, 180 (x, y)
## extent : 560865, 612705, 412335, 534735 (xmin, xmax, ymin, ymax)
## crs : +proj=utm +zone=18 +datum=WGS84 +units=m +no_defs
## source : memory
## names : X2019.07
## values : NA, NA (min, max)leaflet() %>% addTiles() %>%
addRasterImage(precip.mask$X2019.07 , colors = pal, opacity = 0.8) %>%
addLegend(pal = pal, values = values(precip.mask$X2019.07),
title = "Rainfall in Boyacá-Jul.2019 [mm]")## Warning in min(x): ningún argumento finito para min; retornando Inf## Warning in max(x): ningun argumento finito para max; retornando -Inf## Warning in pal(c(r[1], cuts, r[2])): Some values were outside the color scale
## and will be treated as NA