Informe3parte2Interpolacion

library(sf)

## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1; sf_use_s2() is TRUE

library(stars)

## Loading required package: abind

library(gstat)
library(automap)

## Loading required package: sp

library(leaflet)
library(leafem)

(narino <- st_read("/cloud/project/MunicipiosNarino.shp"))

## Reading layer `MunicipiosNarino' from data source 
##   `/cloud/project/MunicipiosNarino.shp' using driver `ESRI Shapefile'
## Simple feature collection with 66 features and 11 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -79.01021 ymin: 0.3613481 xmax: -76.83368 ymax: 2.683898
## Geodetic CRS:  WGS 84

## Simple feature collection with 66 features and 11 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -79.01021 ymin: 0.3613481 xmax: -76.83368 ymax: 2.683898
## Geodetic CRS:  WGS 84
## First 10 features:
##    DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR
## 1          52        083      BELÉN
## 2          52        110    BUESACO
## 3          52        203      COLÓN
## 4          52        480     NARIÑO
## 5          52        506     OSPINA
## 6          52        720    SAPUYES
## 7          52        786  TAMINANGO
## 8          52        788     TANGUA
## 9          52        240  CHACHAGÜÍ
## 10         52        254   EL PEÑOL
##                                                     MPIO_CRSLC MPIO_NAREA
## 1                            Ordenanza 53 Noviembre 29 de 1985   41.84541
## 2                                                         1899  635.96083
## 3                                         Ordenanza 37 de 1921   61.75053
## 4  Ordenanza 027 de Noviembre. 29 de 1999. Decreto 0312 del 24   25.31281
## 5                                         Ordenanza 50 de 1865   64.84321
## 6                                                         1849  115.54851
## 7                                                         1834  234.65783
## 8                                        Ordenanza 103 de 1874  217.95977
## 9                            Ordenanza 20 Noviembre 24 de 1992  146.27176
## 10                        Ordenanza 036 de Diciembre 7 de 1998  119.85744
##    MPIO_CCNCT MPIO_NANO DPTO_CNMBR  SHAPE_AREA SHAPE_LEN ORIG_FID
## 1       52083      2020     NARIÑO 0.003391678 0.3732840        0
## 2       52110      2020     NARIÑO 0.051533090 1.2292312        1
## 3       52203      2020     NARIÑO 0.005005108 0.4592866        2
## 4       52480      2020     NARIÑO 0.002050175 0.2642048        3
## 5       52506      2020     NARIÑO 0.005249269 0.3371496        4
## 6       52720      2020     NARIÑO 0.009351438 0.6599792        5
## 7       52786      2020     NARIÑO 0.019009395 0.6601636        6
## 8       52788      2020     NARIÑO 0.017652117 0.7808421        7
## 9       52240      2020     NARIÑO 0.011849554 0.7373282        8
## 10      52254      2020     NARIÑO 0.009707107 0.5550189        9
##                          geometry
## 1  POLYGON ((-77.07227 1.63422...
## 2  POLYGON ((-77.23516 1.45240...
## 3  POLYGON ((-77.04473 1.67173...
## 4  POLYGON ((-77.34282 1.31465...
## 5  POLYGON ((-77.55776 1.07006...
## 6  POLYGON ((-77.71499 1.0915,...
## 7  POLYGON ((-77.32644 1.67981...
## 8  POLYGON ((-77.36152 1.19568...
## 9  POLYGON ((-77.30295 1.51777...
## 10 POLYGON ((-77.39239 1.60127...

library(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, union

narino %>% dplyr::select( MPIO_CCNCT, MPIO_CNMBR) -> narino
narino

## Simple feature collection with 66 features and 2 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -79.01021 ymin: 0.3613481 xmax: -76.83368 ymax: 2.683898
## Geodetic CRS:  WGS 84
## First 10 features:
##    MPIO_CCNCT MPIO_CNMBR                       geometry
## 1       52083      BELÉN POLYGON ((-77.07227 1.63422...
## 2       52110    BUESACO POLYGON ((-77.23516 1.45240...
## 3       52203      COLÓN POLYGON ((-77.04473 1.67173...
## 4       52480     NARIÑO POLYGON ((-77.34282 1.31465...
## 5       52506     OSPINA POLYGON ((-77.55776 1.07006...
## 6       52720    SAPUYES POLYGON ((-77.71499 1.0915,...
## 7       52786  TAMINANGO POLYGON ((-77.32644 1.67981...
## 8       52788     TANGUA POLYGON ((-77.36152 1.19568...
## 9       52240  CHACHAGÜÍ POLYGON ((-77.30295 1.51777...
## 10      52254   EL PEÑOL POLYGON ((-77.39239 1.60127...

rename(narino, MPIO_CCDGO = MPIO_CCNCT)

## Simple feature collection with 66 features and 2 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -79.01021 ymin: 0.3613481 xmax: -76.83368 ymax: 2.683898
## Geodetic CRS:  WGS 84
## First 10 features:
##    MPIO_CCDGO MPIO_CNMBR                       geometry
## 1       52083      BELÉN POLYGON ((-77.07227 1.63422...
## 2       52110    BUESACO POLYGON ((-77.23516 1.45240...
## 3       52203      COLÓN POLYGON ((-77.04473 1.67173...
## 4       52480     NARIÑO POLYGON ((-77.34282 1.31465...
## 5       52506     OSPINA POLYGON ((-77.55776 1.07006...
## 6       52720    SAPUYES POLYGON ((-77.71499 1.0915,...
## 7       52786  TAMINANGO POLYGON ((-77.32644 1.67981...
## 8       52788     TANGUA POLYGON ((-77.36152 1.19568...
## 9       52240  CHACHAGÜÍ POLYGON ((-77.30295 1.51777...
## 10      52254   EL PEÑOL POLYGON ((-77.39239 1.60127...

archivo <- ("/cloud/project/precip.tif")
(precip <- read_stars(archivo))

## stars object with 2 dimensions and 1 attribute
## attribute(s):
##             Min. 1st Qu. Median     Mean 3rd Qu. Max. NA's
## precip.tif     0       0    0.7 1.864508     2.3 31.8  257
## dimension(s):
##   from to   offset      delta refsys point values x/y
## x    1 53 -79.0417  0.0416667 WGS 84 FALSE   NULL [x]
## y    1 57  2.70833 -0.0416667 WGS 84 FALSE   NULL [y]

precip.mask <- st_crop(precip, narino)

precip

## stars object with 2 dimensions and 1 attribute
## attribute(s):
##             Min. 1st Qu. Median     Mean 3rd Qu. Max. NA's
## precip.tif     0       0    0.7 1.864508     2.3 31.8  257
## dimension(s):
##   from to   offset      delta refsys point values x/y
## x    1 53 -79.0417  0.0416667 WGS 84 FALSE   NULL [x]
## y    1 57  2.70833 -0.0416667 WGS 84 FALSE   NULL [y]

m <- leaflet() %>%
  addTiles() %>%  
  leafem:::addGeoRaster(
      precip.mask,
      opacity = 0.7,                
      colorOptions = colorOptions(palette = c("orange", "yellow", "cyan", "blue"), 
                                  domain = 18:400)
    ) 
m

Capa de precipitación

precip.pts <- st_as_sf(precip.mask, as_points = TRUE, merge = FALSE, long = TRUE)

precip.pts

## Simple feature collection with 1465 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -79.02083 ymin: 0.3541667 xmax: -76.85417 ymax: 2.6875
## Geodetic CRS:  WGS 84
## First 10 features:
##    precip.tif                   geometry
## 1         0.5 POINT (-78.35417 2.645833)
## 2         1.0  POINT (-78.3125 2.645833)
## 3         0.4 POINT (-78.27083 2.645833)
## 4         0.3 POINT (-78.22917 2.645833)
## 5         0.8  POINT (-78.1875 2.645833)
## 6         0.1 POINT (-78.14583 2.645833)
## 7         0.4 POINT (-78.10417 2.645833)
## 8         0.1 POINT (-77.97917 2.645833)
## 9         0.0 POINT (-78.35417 2.604167)
## 10        0.2  POINT (-78.3125 2.604167)

dt = sort(sample(1465, 1465*.7))
train<-precip.pts[dt,]
test<-precip.pts[-dt,]

train

## Simple feature collection with 1025 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -78.9375 ymin: 0.3958333 xmax: -76.85417 ymax: 2.645833
## Geodetic CRS:  WGS 84
## First 10 features:
##    precip.tif                   geometry
## 1         0.5 POINT (-78.35417 2.645833)
## 3         0.4 POINT (-78.27083 2.645833)
## 6         0.1 POINT (-78.14583 2.645833)
## 7         0.4 POINT (-78.10417 2.645833)
## 8         0.1 POINT (-77.97917 2.645833)
## 10        0.2  POINT (-78.3125 2.604167)
## 11        1.0 POINT (-78.27083 2.604167)
## 12        0.2 POINT (-78.22917 2.604167)
## 14        1.4 POINT (-78.14583 2.604167)
## 15        1.4 POINT (-78.10417 2.604167)

longit <- st_coordinates(train)[,1]
latit <- st_coordinates(train)[,2]
rain <- train$precip.tif 

id <- seq(1,1025,1) 

(sitios <- data.frame(id, longit, latit,rain))

##        id    longit     latit rain
## 1       1 -78.35417 2.6458333  0.5
## 2       2 -78.27083 2.6458333  0.4
## 3       3 -78.14583 2.6458333  0.1
## 4       4 -78.10417 2.6458333  0.4
## 5       5 -77.97917 2.6458333  0.1
## 6       6 -78.31250 2.6041667  0.2
## 7       7 -78.27083 2.6041667  1.0
## 8       8 -78.22917 2.6041667  0.2
## 9       9 -78.14583 2.6041667  1.4
## 10     10 -78.10417 2.6041667  1.4
## 11     11 -78.02083 2.6041667  0.0
## 12     12 -78.43750 2.5625000  0.2
## 13     13 -78.39583 2.5625000  0.3
## 14     14 -78.35417 2.5625000  0.2
## 15     15 -78.31250 2.5625000  0.6
## 16     16 -78.22917 2.5625000  0.5
## 17     17 -78.18750 2.5625000  0.4
## 18     18 -78.14583 2.5625000  1.7
## 19     19 -78.10417 2.5625000  0.4
## 20     20 -78.02083 2.5625000  0.0
## 21     21 -77.93750 2.5625000  0.0
## 22     22 -78.47917 2.5208333  0.2
## 23     23 -78.43750 2.5208333  0.0
## 24     24 -78.39583 2.5208333  0.0
## 25     25 -78.35417 2.5208333  0.0
## 26     26 -78.27083 2.5208333  0.6
## 27     27 -78.22917 2.5208333  0.3
## 28     28 -78.14583 2.5208333  1.2
## 29     29 -78.10417 2.5208333  0.2
## 30     30 -78.06250 2.5208333  0.1
## 31     31 -78.02083 2.5208333  0.0
## 32     32 -77.97917 2.5208333  0.0
## 33     33 -77.93750 2.5208333  0.0
## 34     34 -78.52083 2.4791667  0.5
## 35     35 -78.47917 2.4791667  0.1
## 36     36 -78.43750 2.4791667  0.0
## 37     37 -78.35417 2.4791667  0.0
## 38     38 -78.27083 2.4791667  0.5
## 39     39 -78.18750 2.4791667  0.0
## 40     40 -78.14583 2.4791667  0.0
## 41     41 -78.10417 2.4791667  0.0
## 42     42 -78.02083 2.4791667  0.0
## 43     43 -77.93750 2.4791667  0.0
## 44     44 -78.39583 2.4375000  0.0
## 45     45 -78.35417 2.4375000  0.0
## 46     46 -78.31250 2.4375000  0.2
## 47     47 -78.18750 2.4375000  0.0
## 48     48 -78.14583 2.4375000  0.0
## 49     49 -78.10417 2.4375000  0.0
## 50     50 -78.06250 2.4375000  0.0
## 51     51 -78.02083 2.4375000  0.0
## 52     52 -77.97917 2.4375000  0.0
## 53     53 -77.93750 2.4375000  0.0
## 54     54 -78.60417 2.3958333  0.2
## 55     55 -78.52083 2.3958333  0.0
## 56     56 -78.47917 2.3958333  0.1
## 57     57 -78.43750 2.3958333  0.1
## 58     58 -78.35417 2.3958333  0.0
## 59     59 -78.31250 2.3958333  0.0
## 60     60 -78.22917 2.3958333  0.0
## 61     61 -78.18750 2.3958333  0.0
## 62     62 -78.06250 2.3958333  0.0
## 63     63 -77.97917 2.3958333  0.0
## 64     64 -77.93750 2.3958333  0.0
## 65     65 -78.60417 2.3541667  0.1
## 66     66 -78.52083 2.3541667  0.0
## 67     67 -78.43750 2.3541667  0.0
## 68     68 -78.39583 2.3541667  0.0
## 69     69 -78.27083 2.3541667  0.0
## 70     70 -78.22917 2.3541667  0.0
## 71     71 -78.18750 2.3541667  0.0
## 72     72 -78.14583 2.3541667  0.0
## 73     73 -78.02083 2.3541667  0.0
## 74     74 -77.97917 2.3541667  0.0
## 75     75 -77.93750 2.3541667  0.0
## 76     76 -77.89583 2.3541667  0.0
## 77     77 -78.60417 2.3125000  0.0
## 78     78 -78.56250 2.3125000  0.0
## 79     79 -78.52083 2.3125000  0.0
## 80     80 -78.47917 2.3125000  0.0
## 81     81 -78.39583 2.3125000  0.0
## 82     82 -78.35417 2.3125000  0.0
## 83     83 -78.31250 2.3125000  0.0
## 84     84 -78.27083 2.3125000  0.0
## 85     85 -78.18750 2.3125000  0.0
## 86     86 -78.14583 2.3125000  0.0
## 87     87 -78.10417 2.3125000  0.0
## 88     88 -78.06250 2.3125000  0.0
## 89     89 -78.02083 2.3125000  0.0
## 90     90 -77.97917 2.3125000  0.0
## 91     91 -77.89583 2.3125000  0.0
## 92     92 -78.64583 2.2708333  0.2
## 93     93 -78.60417 2.2708333  0.0
## 94     94 -78.47917 2.2708333  0.0
## 95     95 -78.39583 2.2708333  0.0
## 96     96 -78.35417 2.2708333  0.0
## 97     97 -78.31250 2.2708333  0.0
## 98     98 -78.27083 2.2708333  0.0
## 99     99 -78.22917 2.2708333  0.0
## 100   100 -78.18750 2.2708333  0.0
## 101   101 -78.14583 2.2708333  0.0
## 102   102 -78.10417 2.2708333  0.0
## 103   103 -78.02083 2.2708333  0.0
## 104   104 -77.97917 2.2708333  0.0
## 105   105 -77.93750 2.2708333  0.0
## 106   106 -77.89583 2.2708333  0.0
## 107   107 -77.47917 2.2708333  1.5
## 108   108 -77.43750 2.2708333  1.0
## 109   109 -78.64583 2.2291667  0.0
## 110   110 -78.60417 2.2291667  0.0
## 111   111 -78.56250 2.2291667  0.0
## 112   112 -78.47917 2.2291667  0.0
## 113   113 -78.39583 2.2291667  0.0
## 114   114 -78.22917 2.2291667  0.0
## 115   115 -78.18750 2.2291667  0.0
## 116   116 -78.14583 2.2291667  0.0
## 117   117 -78.10417 2.2291667  0.0
## 118   118 -78.06250 2.2291667  0.0
## 119   119 -77.97917 2.2291667  0.0
## 120   120 -77.85417 2.2291667  0.0
## 121   121 -78.68750 2.1875000  0.2
## 122   122 -78.64583 2.1875000  0.0
## 123   123 -78.60417 2.1875000  0.0
## 124   124 -78.56250 2.1875000  0.0
## 125   125 -78.52083 2.1875000  0.0
## 126   126 -78.47917 2.1875000  0.0
## 127   127 -78.43750 2.1875000  0.0
## 128   128 -78.39583 2.1875000  0.0
## 129   129 -78.35417 2.1875000  0.0
## 130   130 -78.31250 2.1875000  0.0
## 131   131 -78.27083 2.1875000  0.0
## 132   132 -78.22917 2.1875000  0.0
## 133   133 -78.18750 2.1875000  0.0
## 134   134 -78.14583 2.1875000  0.0
## 135   135 -78.10417 2.1875000  0.0
## 136   136 -78.06250 2.1875000  0.0
## 137   137 -78.02083 2.1875000  0.0
## 138   138 -77.97917 2.1875000  0.0
## 139   139 -77.93750 2.1875000  0.0
## 140   140 -77.85417 2.1875000  0.0
## 141   141 -77.56250 2.1875000  1.4
## 142   142 -77.52083 2.1875000  1.7
## 143   143 -77.47917 2.1875000  1.6
## 144   144 -77.43750 2.1875000  3.4
## 145   145 -78.56250 2.1458333  0.0
## 146   146 -78.47917 2.1458333  0.0
## 147   147 -78.39583 2.1458333  0.0
## 148   148 -78.35417 2.1458333  0.0
## 149   149 -78.31250 2.1458333  0.0
## 150   150 -78.18750 2.1458333  0.0
## 151   151 -78.14583 2.1458333  0.0
## 152   152 -78.10417 2.1458333  0.0
## 153   153 -78.06250 2.1458333  0.0
## 154   154 -78.02083 2.1458333  0.0
## 155   155 -77.97917 2.1458333  0.0
## 156   156 -77.89583 2.1458333  0.0
## 157   157 -77.85417 2.1458333  0.0
## 158   158 -77.81250 2.1458333  0.0
## 159   159 -77.68750 2.1458333  0.0
## 160   160 -77.64583 2.1458333  0.2
## 161   161 -77.47917 2.1458333  2.3
## 162   162 -77.43750 2.1458333  3.3
## 163   163 -77.35417 2.1458333  1.3
## 164   164 -77.31250 2.1458333  1.6
## 165   165 -78.68750 2.1041667  0.2
## 166   166 -78.60417 2.1041667  0.0
## 167   167 -78.56250 2.1041667  0.0
## 168   168 -78.52083 2.1041667  0.0
## 169   169 -78.47917 2.1041667  0.0
## 170   170 -78.39583 2.1041667  0.0
## 171   171 -78.31250 2.1041667  0.0
## 172   172 -78.18750 2.1041667  0.0
## 173   173 -78.10417 2.1041667  0.0
## 174   174 -78.06250 2.1041667  0.0
## 175   175 -78.02083 2.1041667  0.0
## 176   176 -77.97917 2.1041667  0.0
## 177   177 -77.93750 2.1041667  0.0
## 178   178 -77.89583 2.1041667  0.0
## 179   179 -77.85417 2.1041667  0.0
## 180   180 -77.77083 2.1041667  0.0
## 181   181 -77.72917 2.1041667  0.2
## 182   182 -77.68750 2.1041667  0.3
## 183   183 -77.64583 2.1041667  0.8
## 184   184 -77.60417 2.1041667  1.8
## 185   185 -77.56250 2.1041667  2.1
## 186   186 -77.52083 2.1041667  1.3
## 187   187 -77.47917 2.1041667  4.0
## 188   188 -77.35417 2.1041667  1.5
## 189   189 -77.31250 2.1041667  1.8
## 190   190 -78.64583 2.0625000  0.0
## 191   191 -78.60417 2.0625000  0.0
## 192   192 -78.47917 2.0625000  0.0
## 193   193 -78.39583 2.0625000  0.0
## 194   194 -78.22917 2.0625000  0.0
## 195   195 -78.18750 2.0625000  0.0
## 196   196 -78.14583 2.0625000  0.0
## 197   197 -78.10417 2.0625000  0.0
## 198   198 -78.02083 2.0625000  0.0
## 199   199 -77.97917 2.0625000  0.0
## 200   200 -77.93750 2.0625000  0.0
## 201   201 -77.89583 2.0625000  0.0
## 202   202 -77.85417 2.0625000  0.0
## 203   203 -77.81250 2.0625000  0.0
## 204   204 -77.77083 2.0625000  0.0
## 205   205 -77.68750 2.0625000  0.8
## 206   206 -77.64583 2.0625000  0.7
## 207   207 -77.60417 2.0625000  1.3
## 208   208 -77.52083 2.0625000  1.4
## 209   209 -77.47917 2.0625000  1.8
## 210   210 -77.43750 2.0625000  1.9
## 211   211 -77.39583 2.0625000  1.7
## 212   212 -77.35417 2.0625000  2.0
## 213   213 -78.64583 2.0208333  0.1
## 214   214 -78.60417 2.0208333  0.0
## 215   215 -78.56250 2.0208333  0.0
## 216   216 -78.43750 2.0208333  0.0
## 217   217 -78.35417 2.0208333  0.0
## 218   218 -78.31250 2.0208333  0.0
## 219   219 -78.27083 2.0208333  0.0
## 220   220 -78.22917 2.0208333  0.0
## 221   221 -78.18750 2.0208333  0.0
## 222   222 -78.14583 2.0208333  0.0
## 223   223 -78.10417 2.0208333  0.0
## 224   224 -78.02083 2.0208333  0.0
## 225   225 -77.93750 2.0208333  0.0
## 226   226 -77.81250 2.0208333  0.0
## 227   227 -77.77083 2.0208333  0.0
## 228   228 -77.72917 2.0208333  0.1
## 229   229 -77.64583 2.0208333  0.6
## 230   230 -77.60417 2.0208333  1.0
## 231   231 -77.52083 2.0208333  2.2
## 232   232 -77.47917 2.0208333  1.5
## 233   233 -77.43750 2.0208333  1.8
## 234   234 -77.39583 2.0208333  1.8
## 235   235 -77.35417 2.0208333  2.2
## 236   236 -78.56250 1.9791667  0.1
## 237   237 -78.52083 1.9791667  0.0
## 238   238 -78.47917 1.9791667  0.0
## 239   239 -78.39583 1.9791667  0.0
## 240   240 -78.35417 1.9791667  0.0
## 241   241 -78.27083 1.9791667  0.0
## 242   242 -78.22917 1.9791667  0.0
## 243   243 -78.18750 1.9791667  0.0
## 244   244 -78.14583 1.9791667  0.0
## 245   245 -78.10417 1.9791667  0.0
## 246   246 -78.02083 1.9791667  0.0
## 247   247 -77.93750 1.9791667  0.0
## 248   248 -77.89583 1.9791667  0.0
## 249   249 -77.85417 1.9791667  0.0
## 250   250 -77.81250 1.9791667  0.0
## 251   251 -77.77083 1.9791667  0.1
## 252   252 -77.72917 1.9791667  0.3
## 253   253 -77.68750 1.9791667  0.9
## 254   254 -77.64583 1.9791667  1.1
## 255   255 -77.60417 1.9791667  1.1
## 256   256 -77.56250 1.9791667  0.8
## 257   257 -77.52083 1.9791667  1.9
## 258   258 -77.47917 1.9791667  1.9
## 259   259 -77.39583 1.9791667  1.7
## 260   260 -77.35417 1.9791667  2.9
## 261   261 -77.31250 1.9791667  2.7
## 262   262 -78.56250 1.9375000  0.0
## 263   263 -78.47917 1.9375000  0.0
## 264   264 -78.43750 1.9375000  0.0
## 265   265 -78.31250 1.9375000  0.0
## 266   266 -78.27083 1.9375000  0.0
## 267   267 -78.22917 1.9375000  0.0
## 268   268 -78.18750 1.9375000  0.0
## 269   269 -78.06250 1.9375000  0.0
## 270   270 -78.02083 1.9375000  0.0
## 271   271 -77.97917 1.9375000  0.0
## 272   272 -77.93750 1.9375000  0.0
## 273   273 -77.85417 1.9375000  0.0
## 274   274 -77.81250 1.9375000  0.1
## 275   275 -77.77083 1.9375000  0.2
## 276   276 -77.72917 1.9375000  0.4
## 277   277 -77.68750 1.9375000  0.7
## 278   278 -77.64583 1.9375000  1.0
## 279   279 -77.60417 1.9375000  1.4
## 280   280 -77.56250 1.9375000  1.2
## 281   281 -77.52083 1.9375000  1.2
## 282   282 -77.47917 1.9375000  2.1
## 283   283 -77.43750 1.9375000  1.9
## 284   284 -77.35417 1.9375000  5.1
## 285   285 -77.27083 1.9375000  7.4
## 286   286 -77.22917 1.9375000 11.8
## 287   287 -78.47917 1.8958333  0.0
## 288   288 -78.39583 1.8958333  0.0
## 289   289 -78.35417 1.8958333  0.0
## 290   290 -78.31250 1.8958333  0.0
## 291   291 -78.27083 1.8958333  0.0
## 292   292 -78.22917 1.8958333  0.0
## 293   293 -78.14583 1.8958333  0.0
## 294   294 -78.10417 1.8958333  0.0
## 295   295 -78.06250 1.8958333  0.0
## 296   296 -78.02083 1.8958333  0.0
## 297   297 -77.97917 1.8958333  0.0
## 298   298 -77.93750 1.8958333  0.0
## 299   299 -77.85417 1.8958333  0.0
## 300   300 -77.81250 1.8958333  0.2
## 301   301 -77.72917 1.8958333  0.2
## 302   302 -77.68750 1.8958333  0.9
## 303   303 -77.64583 1.8958333  1.2
## 304   304 -77.60417 1.8958333  1.7
## 305   305 -77.56250 1.8958333  2.0
## 306   306 -77.52083 1.8958333  1.6
## 307   307 -77.39583 1.8958333  4.1
## 308   308 -77.35417 1.8958333  4.4
## 309   309 -77.31250 1.8958333  6.1
## 310   310 -77.27083 1.8958333 11.6
## 311   311 -78.52083 1.8541667  0.0
## 312   312 -78.47917 1.8541667  0.0
## 313   313 -78.35417 1.8541667  0.0
## 314   314 -78.31250 1.8541667  0.0
## 315   315 -78.27083 1.8541667  0.0
## 316   316 -78.22917 1.8541667  0.0
## 317   317 -78.18750 1.8541667  0.0
## 318   318 -78.14583 1.8541667  0.0
## 319   319 -78.10417 1.8541667  0.0
## 320   320 -78.02083 1.8541667  0.0
## 321   321 -77.97917 1.8541667  0.0
## 322   322 -77.89583 1.8541667  0.0
## 323   323 -77.85417 1.8541667  0.0
## 324   324 -77.81250 1.8541667  0.0
## 325   325 -77.77083 1.8541667  0.0
## 326   326 -77.72917 1.8541667  0.4
## 327   327 -77.68750 1.8541667  0.7
## 328   328 -77.64583 1.8541667  1.8
## 329   329 -77.60417 1.8541667  1.7
## 330   330 -77.56250 1.8541667  4.8
## 331   331 -77.52083 1.8541667  5.4
## 332   332 -77.47917 1.8541667  3.9
## 333   333 -77.43750 1.8541667  4.2
## 334   334 -77.39583 1.8541667  5.3
## 335   335 -78.81250 1.8125000  0.0
## 336   336 -78.52083 1.8125000  0.0
## 337   337 -78.47917 1.8125000  0.0
## 338   338 -78.43750 1.8125000  0.0
## 339   339 -78.39583 1.8125000  0.0
## 340   340 -78.35417 1.8125000  0.0
## 341   341 -78.31250 1.8125000  0.0
## 342   342 -78.27083 1.8125000  0.0
## 343   343 -78.22917 1.8125000  0.0
## 344   344 -78.18750 1.8125000  0.0
## 345   345 -78.14583 1.8125000  0.0
## 346   346 -78.10417 1.8125000  0.0
## 347   347 -77.97917 1.8125000  0.0
## 348   348 -77.93750 1.8125000  0.0
## 349   349 -77.89583 1.8125000  0.0
## 350   350 -77.85417 1.8125000  0.0
## 351   351 -77.72917 1.8125000  0.5
## 352   352 -77.64583 1.8125000  0.5
## 353   353 -77.56250 1.8125000  2.0
## 354   354 -77.47917 1.8125000  1.7
## 355   355 -77.43750 1.8125000  2.1
## 356   356 -77.35417 1.8125000  4.1
## 357   357 -78.85417 1.7708333  0.0
## 358   358 -78.81250 1.7708333  0.1
## 359   359 -78.77083 1.7708333  0.0
## 360   360 -78.64583 1.7708333  0.0
## 361   361 -78.60417 1.7708333  0.0
## 362   362 -78.47917 1.7708333  0.0
## 363   363 -78.39583 1.7708333  0.0
## 364   364 -78.35417 1.7708333  0.0
## 365   365 -78.31250 1.7708333  0.0
## 366   366 -78.27083 1.7708333  0.0
## 367   367 -78.22917 1.7708333  0.0
## 368   368 -78.18750 1.7708333  0.0
## 369   369 -78.14583 1.7708333  0.0
## 370   370 -78.10417 1.7708333  0.0
## 371   371 -78.06250 1.7708333  0.0
## 372   372 -78.02083 1.7708333  0.0
## 373   373 -77.93750 1.7708333  0.0
## 374   374 -77.81250 1.7708333  0.0
## 375   375 -77.77083 1.7708333  0.2
## 376   376 -77.72917 1.7708333  0.3
## 377   377 -77.68750 1.7708333  0.6
## 378   378 -77.64583 1.7708333  1.1
## 379   379 -77.47917 1.7708333  1.9
## 380   380 -77.43750 1.7708333  2.1
## 381   381 -77.39583 1.7708333  3.7
## 382   382 -77.35417 1.7708333  5.3
## 383   383 -77.31250 1.7708333  6.4
## 384   384 -78.89583 1.7291667  0.0
## 385   385 -78.85417 1.7291667  0.0
## 386   386 -78.77083 1.7291667  0.1
## 387   387 -78.72917 1.7291667  0.0
## 388   388 -78.68750 1.7291667  0.0
## 389   389 -78.56250 1.7291667  0.0
## 390   390 -78.52083 1.7291667  0.0
## 391   391 -78.43750 1.7291667  0.0
## 392   392 -78.39583 1.7291667  0.0
## 393   393 -78.31250 1.7291667  0.0
## 394   394 -78.27083 1.7291667  0.0
## 395   395 -78.18750 1.7291667  0.0
## 396   396 -78.14583 1.7291667  0.0
## 397   397 -78.06250 1.7291667  0.0
## 398   398 -78.02083 1.7291667  0.0
## 399   399 -77.93750 1.7291667  0.0
## 400   400 -77.89583 1.7291667  0.0
## 401   401 -77.85417 1.7291667  0.0
## 402   402 -77.81250 1.7291667  0.2
## 403   403 -77.77083 1.7291667  0.2
## 404   404 -77.72917 1.7291667  0.4
## 405   405 -77.68750 1.7291667  1.1
## 406   406 -77.64583 1.7291667  1.4
## 407   407 -77.60417 1.7291667  1.7
## 408   408 -77.56250 1.7291667  3.1
## 409   409 -77.52083 1.7291667  3.6
## 410   410 -77.47917 1.7291667  2.9
## 411   411 -77.43750 1.7291667  2.6
## 412   412 -77.39583 1.7291667  4.2
## 413   413 -77.35417 1.7291667  6.5
## 414   414 -78.93750 1.6875000  0.0
## 415   415 -78.89583 1.6875000  0.0
## 416   416 -78.85417 1.6875000  0.0
## 417   417 -78.81250 1.6875000  0.0
## 418   418 -78.77083 1.6875000  0.0
## 419   419 -78.72917 1.6875000  0.0
## 420   420 -78.64583 1.6875000  0.0
## 421   421 -78.60417 1.6875000  0.0
## 422   422 -78.56250 1.6875000  0.0
## 423   423 -78.52083 1.6875000  0.0
## 424   424 -78.47917 1.6875000  0.0
## 425   425 -78.39583 1.6875000  0.0
## 426   426 -78.31250 1.6875000  0.0
## 427   427 -78.27083 1.6875000  0.0
## 428   428 -78.22917 1.6875000  0.0
## 429   429 -78.18750 1.6875000  0.0
## 430   430 -78.14583 1.6875000  0.0
## 431   431 -78.06250 1.6875000  0.0
## 432   432 -78.02083 1.6875000  0.0
## 433   433 -77.97917 1.6875000  0.0
## 434   434 -77.93750 1.6875000  0.0
## 435   435 -77.89583 1.6875000  0.0
## 436   436 -77.81250 1.6875000  0.0
## 437   437 -77.77083 1.6875000  0.1
## 438   438 -77.72917 1.6875000  0.7
## 439   439 -77.64583 1.6875000  1.7
## 440   440 -77.56250 1.6875000  2.0
## 441   441 -77.52083 1.6875000  5.5
## 442   442 -77.47917 1.6875000  3.2
## 443   443 -77.43750 1.6875000  2.8
## 444   444 -77.35417 1.6875000  5.8
## 445   445 -76.97917 1.6875000  3.2
## 446   446 -76.93750 1.6875000  2.2
## 447   447 -78.89583 1.6458333  0.0
## 448   448 -78.85417 1.6458333  0.0
## 449   449 -78.81250 1.6458333  0.0
## 450   450 -78.77083 1.6458333  0.0
## 451   451 -78.68750 1.6458333  0.0
## 452   452 -78.64583 1.6458333  0.0
## 453   453 -78.60417 1.6458333  0.0
## 454   454 -78.56250 1.6458333  0.0
## 455   455 -78.52083 1.6458333  0.0
## 456   456 -78.47917 1.6458333  0.0
## 457   457 -78.43750 1.6458333  0.0
## 458   458 -78.35417 1.6458333  0.0
## 459   459 -78.31250 1.6458333  0.0
## 460   460 -78.22917 1.6458333  0.0
## 461   461 -78.18750 1.6458333  0.0
## 462   462 -78.14583 1.6458333  0.0
## 463   463 -78.06250 1.6458333  0.0
## 464   464 -78.02083 1.6458333  0.0
## 465   465 -77.97917 1.6458333  0.0
## 466   466 -77.93750 1.6458333  0.0
## 467   467 -77.89583 1.6458333  0.0
## 468   468 -77.81250 1.6458333  0.0
## 469   469 -77.64583 1.6458333  1.9
## 470   470 -77.60417 1.6458333  2.3
## 471   471 -77.56250 1.6458333  2.5
## 472   472 -77.52083 1.6458333  3.2
## 473   473 -77.47917 1.6458333  7.9
## 474   474 -77.43750 1.6458333  5.8
## 475   475 -77.31250 1.6458333 10.4
## 476   476 -77.18750 1.6458333 10.1
## 477   477 -77.14583 1.6458333  9.1
## 478   478 -77.10417 1.6458333  7.8
## 479   479 -76.97917 1.6458333  4.0
## 480   480 -76.93750 1.6458333  2.2
## 481   481 -78.89583 1.6041667  0.0
## 482   482 -78.81250 1.6041667  0.0
## 483   483 -78.77083 1.6041667  0.0
## 484   484 -78.72917 1.6041667  0.0
## 485   485 -78.60417 1.6041667  0.0
## 486   486 -78.56250 1.6041667  0.0
## 487   487 -78.43750 1.6041667  0.0
## 488   488 -78.35417 1.6041667  0.0
## 489   489 -78.27083 1.6041667  0.0
## 490   490 -78.18750 1.6041667  0.0
## 491   491 -78.10417 1.6041667  0.0
## 492   492 -78.06250 1.6041667  0.0
## 493   493 -78.02083 1.6041667  0.0
## 494   494 -77.97917 1.6041667  0.0
## 495   495 -77.93750 1.6041667  0.0
## 496   496 -77.81250 1.6041667  0.1
## 497   497 -77.77083 1.6041667  0.3
## 498   498 -77.72917 1.6041667  0.8
## 499   499 -77.64583 1.6041667  1.5
## 500   500 -77.60417 1.6041667  1.7
## 501   501 -77.56250 1.6041667  2.3
## 502   502 -77.52083 1.6041667  2.3
## 503   503 -77.47917 1.6041667  4.9
## 504   504 -77.43750 1.6041667  7.7
## 505   505 -77.39583 1.6041667  9.5
## 506   506 -77.31250 1.6041667  9.2
## 507   507 -77.27083 1.6041667  8.6
## 508   508 -77.18750 1.6041667  4.9
## 509   509 -77.10417 1.6041667  3.7
## 510   510 -77.06250 1.6041667  2.3
## 511   511 -77.02083 1.6041667  2.0
## 512   512 -76.97917 1.6041667  3.0
## 513   513 -76.93750 1.6041667  2.7
## 514   514 -76.89583 1.6041667  1.3
## 515   515 -76.85417 1.6041667  1.4
## 516   516 -78.81250 1.5625000  0.0
## 517   517 -78.77083 1.5625000  0.0
## 518   518 -78.68750 1.5625000  0.0
## 519   519 -78.52083 1.5625000  0.0
## 520   520 -78.43750 1.5625000  0.0
## 521   521 -78.39583 1.5625000  0.0
## 522   522 -78.35417 1.5625000  0.0
## 523   523 -78.31250 1.5625000  0.0
## 524   524 -78.27083 1.5625000  0.0
## 525   525 -78.22917 1.5625000  0.0
## 526   526 -78.18750 1.5625000  0.0
## 527   527 -78.14583 1.5625000  0.0
## 528   528 -78.10417 1.5625000  0.0
## 529   529 -78.06250 1.5625000  0.0
## 530   530 -78.02083 1.5625000  0.0
## 531   531 -77.97917 1.5625000  0.0
## 532   532 -77.93750 1.5625000  0.0
## 533   533 -77.89583 1.5625000  0.0
## 534   534 -77.85417 1.5625000  0.0
## 535   535 -77.81250 1.5625000  0.1
## 536   536 -77.72917 1.5625000  1.6
## 537   537 -77.68750 1.5625000  2.0
## 538   538 -77.64583 1.5625000  2.0
## 539   539 -77.60417 1.5625000  2.1
## 540   540 -77.52083 1.5625000  2.4
## 541   541 -77.47917 1.5625000  3.7
## 542   542 -77.43750 1.5625000  7.8
## 543   543 -77.35417 1.5625000  8.0
## 544   544 -77.31250 1.5625000  5.5
## 545   545 -77.22917 1.5625000  2.9
## 546   546 -77.18750 1.5625000  2.1
## 547   547 -77.14583 1.5625000  1.9
## 548   548 -77.02083 1.5625000  1.8
## 549   549 -76.97917 1.5625000  1.6
## 550   550 -76.93750 1.5625000  1.7
## 551   551 -78.81250 1.5208333  0.0
## 552   552 -78.77083 1.5208333  0.0
## 553   553 -78.68750 1.5208333  0.0
## 554   554 -78.64583 1.5208333  0.0
## 555   555 -78.52083 1.5208333  0.0
## 556   556 -78.27083 1.5208333  0.0
## 557   557 -78.22917 1.5208333  0.0
## 558   558 -78.10417 1.5208333  0.0
## 559   559 -78.06250 1.5208333  0.0
## 560   560 -78.02083 1.5208333  0.0
## 561   561 -77.77083 1.5208333  0.4
## 562   562 -77.68750 1.5208333  2.1
## 563   563 -77.64583 1.5208333  2.1
## 564   564 -77.56250 1.5208333  2.2
## 565   565 -77.52083 1.5208333  3.9
## 566   566 -77.35417 1.5208333  9.0
## 567   567 -77.31250 1.5208333  8.1
## 568   568 -77.27083 1.5208333  7.9
## 569   569 -77.22917 1.5208333  3.3
## 570   570 -77.18750 1.5208333  2.5
## 571   571 -77.10417 1.5208333  2.5
## 572   572 -77.06250 1.5208333  3.0
## 573   573 -77.02083 1.5208333  2.0
## 574   574 -76.93750 1.5208333  1.3
## 575   575 -76.89583 1.5208333  1.2
## 576   576 -78.81250 1.4791667  0.0
## 577   577 -78.77083 1.4791667  0.0
## 578   578 -78.72917 1.4791667  0.0
## 579   579 -78.68750 1.4791667  0.0
## 580   580 -78.64583 1.4791667  0.0
## 581   581 -78.60417 1.4791667  0.0
## 582   582 -78.52083 1.4791667  0.0
## 583   583 -78.47917 1.4791667  0.0
## 584   584 -78.43750 1.4791667  0.0
## 585   585 -78.39583 1.4791667  0.0
## 586   586 -78.31250 1.4791667  0.0
## 587   587 -78.27083 1.4791667  0.0
## 588   588 -78.22917 1.4791667  0.0
## 589   589 -78.18750 1.4791667  0.0
## 590   590 -78.10417 1.4791667  0.0
## 591   591 -78.06250 1.4791667  0.0
## 592   592 -78.02083 1.4791667  0.0
## 593   593 -77.97917 1.4791667  0.0
## 594   594 -77.89583 1.4791667  0.0
## 595   595 -77.85417 1.4791667  0.0
## 596   596 -77.81250 1.4791667  0.1
## 597   597 -77.68750 1.4791667  3.8
## 598   598 -77.64583 1.4791667  3.5
## 599   599 -77.60417 1.4791667  2.7
## 600   600 -77.47917 1.4791667  6.8
## 601   601 -77.39583 1.4791667  6.2
## 602   602 -77.35417 1.4791667  7.8
## 603   603 -77.31250 1.4791667  9.8
## 604   604 -77.27083 1.4791667  7.7
## 605   605 -77.22917 1.4791667  5.4
## 606   606 -77.18750 1.4791667  3.8
## 607   607 -77.10417 1.4791667  4.3
## 608   608 -77.06250 1.4791667  3.9
## 609   609 -77.02083 1.4791667  2.8
## 610   610 -78.81250 1.4375000  0.0
## 611   611 -78.77083 1.4375000  0.0
## 612   612 -78.72917 1.4375000  0.0
## 613   613 -78.68750 1.4375000  0.0
## 614   614 -78.60417 1.4375000  0.0
## 615   615 -78.52083 1.4375000  0.0
## 616   616 -78.47917 1.4375000  0.0
## 617   617 -78.43750 1.4375000  0.0
## 618   618 -78.39583 1.4375000  0.0
## 619   619 -78.35417 1.4375000  0.0
## 620   620 -78.31250 1.4375000  0.0
## 621   621 -78.27083 1.4375000  0.0
## 622   622 -78.22917 1.4375000  0.0
## 623   623 -78.10417 1.4375000  0.0
## 624   624 -78.02083 1.4375000  0.0
## 625   625 -77.97917 1.4375000  0.0
## 626   626 -77.85417 1.4375000  0.0
## 627   627 -77.81250 1.4375000  0.1
## 628   628 -77.77083 1.4375000  0.4
## 629   629 -77.72917 1.4375000  2.2
## 630   630 -77.68750 1.4375000  4.0
## 631   631 -77.60417 1.4375000  3.1
## 632   632 -77.52083 1.4375000  6.9
## 633   633 -77.47917 1.4375000  6.5
## 634   634 -77.31250 1.4375000  8.5
## 635   635 -77.27083 1.4375000  9.4
## 636   636 -77.22917 1.4375000  7.2
## 637   637 -77.18750 1.4375000  7.1
## 638   638 -77.14583 1.4375000  6.7
## 639   639 -77.10417 1.4375000  5.8
## 640   640 -77.02083 1.4375000  1.8
## 641   641 -76.97917 1.4375000  1.2
## 642   642 -76.93750 1.4375000  1.0
## 643   643 -78.68750 1.3958333  0.0
## 644   644 -78.64583 1.3958333  0.0
## 645   645 -78.56250 1.3958333  0.0
## 646   646 -78.52083 1.3958333  0.0
## 647   647 -78.47917 1.3958333  0.0
## 648   648 -78.43750 1.3958333  0.0
## 649   649 -78.35417 1.3958333  0.0
## 650   650 -78.27083 1.3958333  0.0
## 651   651 -78.18750 1.3958333  0.0
## 652   652 -78.14583 1.3958333  0.0
## 653   653 -78.10417 1.3958333  0.0
## 654   654 -78.06250 1.3958333  0.0
## 655   655 -78.02083 1.3958333  0.0
## 656   656 -77.97917 1.3958333  0.0
## 657   657 -77.89583 1.3958333  0.4
## 658   658 -77.85417 1.3958333  0.3
## 659   659 -77.64583 1.3958333  2.7
## 660   660 -77.60417 1.3958333  3.9
## 661   661 -77.56250 1.3958333  6.6
## 662   662 -77.43750 1.3958333  5.6
## 663   663 -77.39583 1.3958333  3.3
## 664   664 -77.35417 1.3958333  3.5
## 665   665 -77.31250 1.3958333  6.9
## 666   666 -77.22917 1.3958333  5.3
## 667   667 -77.18750 1.3958333  5.3
## 668   668 -77.10417 1.3958333  4.0
## 669   669 -77.02083 1.3958333  2.7
## 670   670 -76.93750 1.3958333  1.2
## 671   671 -78.68750 1.3541667  0.0
## 672   672 -78.64583 1.3541667  0.0
## 673   673 -78.60417 1.3541667  0.0
## 674   674 -78.56250 1.3541667  0.0
## 675   675 -78.39583 1.3541667  0.0
## 676   676 -78.31250 1.3541667  0.0
## 677   677 -78.22917 1.3541667  0.0
## 678   678 -78.18750 1.3541667  0.0
## 679   679 -77.97917 1.3541667  0.2
## 680   680 -77.89583 1.3541667  0.6
## 681   681 -77.85417 1.3541667  0.1
## 682   682 -77.77083 1.3541667  1.1
## 683   683 -77.68750 1.3541667  2.7
## 684   684 -77.52083 1.3541667  7.1
## 685   685 -77.47917 1.3541667  5.9
## 686   686 -77.43750 1.3541667  5.0
## 687   687 -77.39583 1.3541667  3.0
## 688   688 -77.35417 1.3541667  3.6
## 689   689 -77.27083 1.3541667  3.6
## 690   690 -77.22917 1.3541667  3.0
## 691   691 -77.18750 1.3541667  3.4
## 692   692 -77.14583 1.3541667  3.5
## 693   693 -77.10417 1.3541667  2.3
## 694   694 -77.02083 1.3541667  2.6
## 695   695 -76.97917 1.3541667  1.1
## 696   696 -76.93750 1.3541667  0.8
## 697   697 -78.60417 1.3125000  0.0
## 698   698 -78.56250 1.3125000  0.0
## 699   699 -78.52083 1.3125000  0.0
## 700   700 -78.39583 1.3125000  0.0
## 701   701 -78.31250 1.3125000  0.0
## 702   702 -78.27083 1.3125000  0.0
## 703   703 -78.22917 1.3125000  0.0
## 704   704 -78.10417 1.3125000  0.0
## 705   705 -78.06250 1.3125000  0.8
## 706   706 -77.97917 1.3125000  0.4
## 707   707 -77.93750 1.3125000  0.3
## 708   708 -77.89583 1.3125000  0.6
## 709   709 -77.85417 1.3125000  1.6
## 710   710 -77.81250 1.3125000  0.7
## 711   711 -77.72917 1.3125000  2.3
## 712   712 -77.68750 1.3125000  2.3
## 713   713 -77.64583 1.3125000  2.6
## 714   714 -77.60417 1.3125000  5.9
## 715   715 -77.47917 1.3125000  7.4
## 716   716 -77.35417 1.3125000  2.9
## 717   717 -77.31250 1.3125000  3.2
## 718   718 -77.22917 1.3125000  2.0
## 719   719 -77.14583 1.3125000  2.5
## 720   720 -77.10417 1.3125000  1.6
## 721   721 -77.06250 1.3125000  1.3
## 722   722 -76.93750 1.3125000  0.8
## 723   723 -78.60417 1.2708333  0.0
## 724   724 -78.56250 1.2708333  0.0
## 725   725 -78.52083 1.2708333  0.0
## 726   726 -78.47917 1.2708333  0.0
## 727   727 -78.31250 1.2708333  0.0
## 728   728 -78.27083 1.2708333  0.0
## 729   729 -78.18750 1.2708333  0.0
## 730   730 -78.14583 1.2708333  0.0
## 731   731 -78.06250 1.2708333  0.2
## 732   732 -77.97917 1.2708333  1.7
## 733   733 -77.93750 1.2708333  1.9
## 734   734 -77.89583 1.2708333  1.0
## 735   735 -77.85417 1.2708333  2.5
## 736   736 -77.81250 1.2708333  1.8
## 737   737 -77.77083 1.2708333  2.2
## 738   738 -77.68750 1.2708333  2.2
## 739   739 -77.64583 1.2708333  3.2
## 740   740 -77.60417 1.2708333  4.8
## 741   741 -77.56250 1.2708333  4.0
## 742   742 -77.52083 1.2708333  5.3
## 743   743 -77.43750 1.2708333  3.4
## 744   744 -77.39583 1.2708333  2.6
## 745   745 -77.31250 1.2708333  2.9
## 746   746 -77.27083 1.2708333  2.1
## 747   747 -77.22917 1.2708333  1.5
## 748   748 -77.18750 1.2708333  1.6
## 749   749 -77.10417 1.2708333  1.2
## 750   750 -77.06250 1.2708333  1.0
## 751   751 -78.52083 1.2291667  0.0
## 752   752 -78.47917 1.2291667  0.0
## 753   753 -78.43750 1.2291667  0.0
## 754   754 -78.39583 1.2291667  0.0
## 755   755 -78.35417 1.2291667  0.0
## 756   756 -78.31250 1.2291667  0.0
## 757   757 -78.27083 1.2291667  0.0
## 758   758 -78.22917 1.2291667  0.0
## 759   759 -78.14583 1.2291667  0.0
## 760   760 -78.10417 1.2291667  0.0
## 761   761 -78.06250 1.2291667  0.0
## 762   762 -77.97917 1.2291667  0.7
## 763   763 -77.89583 1.2291667  1.9
## 764   764 -77.85417 1.2291667  2.1
## 765   765 -77.81250 1.2291667  2.1
## 766   766 -77.72917 1.2291667  2.0
## 767   767 -77.64583 1.2291667  3.2
## 768   768 -77.60417 1.2291667  3.2
## 769   769 -77.47917 1.2291667  5.8
## 770   770 -77.39583 1.2291667  2.0
## 771   771 -77.35417 1.2291667  1.7
## 772   772 -77.31250 1.2291667  2.6
## 773   773 -77.22917 1.2291667  2.1
## 774   774 -77.14583 1.2291667  1.2
## 775   775 -77.06250 1.2291667  0.8
## 776   776 -76.97917 1.2291667  1.4
## 777   777 -78.39583 1.1875000  0.0
## 778   778 -78.35417 1.1875000  0.0
## 779   779 -78.27083 1.1875000  0.0
## 780   780 -78.22917 1.1875000  0.0
## 781   781 -78.18750 1.1875000  0.0
## 782   782 -78.10417 1.1875000  0.0
## 783   783 -78.02083 1.1875000  0.8
## 784   784 -77.97917 1.1875000  0.7
## 785   785 -77.93750 1.1875000  1.1
## 786   786 -77.81250 1.1875000  2.0
## 787   787 -77.72917 1.1875000  2.2
## 788   788 -77.68750 1.1875000  2.6
## 789   789 -77.64583 1.1875000  2.5
## 790   790 -77.60417 1.1875000  3.0
## 791   791 -77.56250 1.1875000  2.9
## 792   792 -77.52083 1.1875000  4.3
## 793   793 -77.43750 1.1875000  3.9
## 794   794 -77.35417 1.1875000  1.3
## 795   795 -77.31250 1.1875000  2.2
## 796   796 -77.27083 1.1875000  3.4
## 797   797 -77.18750 1.1875000  1.7
## 798   798 -77.14583 1.1875000  1.2
## 799   799 -77.10417 1.1875000  1.0
## 800   800 -78.27083 1.1458333  0.0
## 801   801 -78.22917 1.1458333  0.0
## 802   802 -78.18750 1.1458333  0.1
## 803   803 -78.14583 1.1458333  1.6
## 804   804 -78.06250 1.1458333  0.4
## 805   805 -78.02083 1.1458333  1.0
## 806   806 -77.89583 1.1458333  2.2
## 807   807 -77.85417 1.1458333  2.3
## 808   808 -77.64583 1.1458333  3.0
## 809   809 -77.52083 1.1458333  4.0
## 810   810 -77.47917 1.1458333  5.8
## 811   811 -77.35417 1.1458333  2.0
## 812   812 -77.31250 1.1458333  2.1
## 813   813 -77.27083 1.1458333  2.1
## 814   814 -77.22917 1.1458333  1.7
## 815   815 -77.18750 1.1458333  1.5
## 816   816 -77.14583 1.1458333  2.1
## 817   817 -77.10417 1.1458333  1.0
## 818   818 -78.18750 1.1041667  0.0
## 819   819 -78.06250 1.1041667  0.6
## 820   820 -78.02083 1.1041667  2.3
## 821   821 -77.97917 1.1041667  2.7
## 822   822 -77.93750 1.1041667  2.0
## 823   823 -77.85417 1.1041667  2.2
## 824   824 -77.81250 1.1041667  2.9
## 825   825 -77.77083 1.1041667  2.9
## 826   826 -77.72917 1.1041667  2.2
## 827   827 -77.68750 1.1041667  2.1
## 828   828 -77.64583 1.1041667  2.8
## 829   829 -77.60417 1.1041667  2.8
## 830   830 -77.52083 1.1041667  3.9
## 831   831 -77.47917 1.1041667  6.2
## 832   832 -77.39583 1.1041667  4.0
## 833   833 -77.31250 1.1041667  2.5
## 834   834 -77.27083 1.1041667  2.1
## 835   835 -77.18750 1.1041667  1.4
## 836   836 -77.14583 1.1041667  2.5
## 837   837 -78.22917 1.0625000  0.0
## 838   838 -78.14583 1.0625000  0.2
## 839   839 -78.10417 1.0625000  1.5
## 840   840 -78.06250 1.0625000  1.9
## 841   841 -77.89583 1.0625000  2.1
## 842   842 -77.85417 1.0625000  2.3
## 843   843 -77.72917 1.0625000  2.8
## 844   844 -77.68750 1.0625000  2.6
## 845   845 -77.60417 1.0625000  3.5
## 846   846 -77.56250 1.0625000  3.8
## 847   847 -77.47917 1.0625000  6.1
## 848   848 -77.43750 1.0625000  5.8
## 849   849 -77.39583 1.0625000  4.4
## 850   850 -77.35417 1.0625000  2.7
## 851   851 -77.31250 1.0625000  2.7
## 852   852 -77.22917 1.0625000  1.6
## 853   853 -77.10417 1.0625000  1.4
## 854   854 -78.18750 1.0208333  0.6
## 855   855 -78.14583 1.0208333  0.8
## 856   856 -78.06250 1.0208333  2.8
## 857   857 -78.02083 1.0208333  2.8
## 858   858 -77.93750 1.0208333  3.9
## 859   859 -77.89583 1.0208333  2.7
## 860   860 -77.85417 1.0208333  2.5
## 861   861 -77.81250 1.0208333  2.1
## 862   862 -77.77083 1.0208333  2.4
## 863   863 -77.72917 1.0208333  3.3
## 864   864 -77.64583 1.0208333  3.2
## 865   865 -77.60417 1.0208333  3.3
## 866   866 -77.56250 1.0208333  3.4
## 867   867 -77.52083 1.0208333  4.3
## 868   868 -77.47917 1.0208333  6.0
## 869   869 -77.43750 1.0208333  6.5
## 870   870 -77.35417 1.0208333  2.2
## 871   871 -77.27083 1.0208333  1.8
## 872   872 -77.18750 1.0208333  2.5
## 873   873 -77.14583 1.0208333  2.1
## 874   874 -77.10417 1.0208333  2.0
## 875   875 -78.18750 0.9791667  0.5
## 876   876 -78.14583 0.9791667  2.8
## 877   877 -78.10417 0.9791667  2.0
## 878   878 -78.02083 0.9791667  2.0
## 879   879 -77.97917 0.9791667  2.4
## 880   880 -77.89583 0.9791667  3.1
## 881   881 -77.81250 0.9791667  2.1
## 882   882 -77.77083 0.9791667  2.5
## 883   883 -77.72917 0.9791667  2.9
## 884   884 -77.68750 0.9791667  3.3
## 885   885 -77.64583 0.9791667  3.1
## 886   886 -77.56250 0.9791667  2.9
## 887   887 -77.47917 0.9791667  4.9
## 888   888 -77.43750 0.9791667  4.7
## 889   889 -77.39583 0.9791667  2.7
## 890   890 -77.35417 0.9791667  1.8
## 891   891 -77.31250 0.9791667  1.5
## 892   892 -77.27083 0.9791667  1.7
## 893   893 -77.18750 0.9791667  1.9
## 894   894 -77.14583 0.9791667  2.5
## 895   895 -77.10417 0.9791667  1.8
## 896   896 -78.14583 0.9375000  2.0
## 897   897 -78.10417 0.9375000  1.8
## 898   898 -78.06250 0.9375000  2.7
## 899   899 -78.02083 0.9375000  2.4
## 900   900 -77.93750 0.9375000  1.9
## 901   901 -77.89583 0.9375000  1.7
## 902   902 -77.81250 0.9375000  2.4
## 903   903 -77.77083 0.9375000  3.0
## 904   904 -77.64583 0.9375000  3.4
## 905   905 -77.60417 0.9375000  3.3
## 906   906 -77.56250 0.9375000  3.2
## 907   907 -77.52083 0.9375000  3.5
## 908   908 -77.47917 0.9375000  4.4
## 909   909 -77.39583 0.9375000  2.1
## 910   910 -77.35417 0.9375000  1.6
## 911   911 -77.31250 0.9375000  1.7
## 912   912 -77.27083 0.9375000  2.9
## 913   913 -77.22917 0.9375000  1.9
## 914   914 -77.18750 0.9375000  1.4
## 915   915 -77.14583 0.9375000  2.0
## 916   916 -77.10417 0.9375000  1.4
## 917   917 -78.02083 0.8958333  4.2
## 918   918 -77.97917 0.8958333  2.1
## 919   919 -77.93750 0.8958333  1.7
## 920   920 -77.85417 0.8958333  2.3
## 921   921 -77.81250 0.8958333  2.7
## 922   922 -77.77083 0.8958333  3.0
## 923   923 -77.68750 0.8958333  3.3
## 924   924 -77.64583 0.8958333  3.3
## 925   925 -77.60417 0.8958333  3.7
## 926   926 -77.56250 0.8958333  3.9
## 927   927 -77.52083 0.8958333  4.2
## 928   928 -77.39583 0.8958333  1.9
## 929   929 -77.35417 0.8958333  1.7
## 930   930 -77.22917 0.8958333  1.3
## 931   931 -77.18750 0.8958333  1.2
## 932   932 -77.14583 0.8958333  1.8
## 933   933 -77.97917 0.8541667  2.7
## 934   934 -77.93750 0.8541667  2.1
## 935   935 -77.85417 0.8541667  2.1
## 936   936 -77.81250 0.8541667  2.7
## 937   937 -77.77083 0.8541667  2.9
## 938   938 -77.72917 0.8541667  3.0
## 939   939 -77.68750 0.8541667  2.9
## 940   940 -77.60417 0.8541667  4.0
## 941   941 -77.39583 0.8541667  1.8
## 942   942 -77.35417 0.8541667  2.0
## 943   943 -77.31250 0.8541667  3.0
## 944   944 -77.27083 0.8541667  2.3
## 945   945 -77.22917 0.8541667  1.2
## 946   946 -77.18750 0.8541667  1.7
## 947   947 -77.89583 0.8125000  2.0
## 948   948 -77.64583 0.8125000  3.0
## 949   949 -77.60417 0.8125000  3.2
## 950   950 -77.47917 0.8125000  2.4
## 951   951 -77.39583 0.8125000  1.6
## 952   952 -77.31250 0.8125000  3.8
## 953   953 -77.27083 0.8125000  3.2
## 954   954 -77.22917 0.8125000  1.6
## 955   955 -77.14583 0.8125000  1.5
## 956   956 -77.64583 0.7708333  2.7
## 957   957 -77.60417 0.7708333  2.8
## 958   958 -77.56250 0.7708333  2.8
## 959   959 -77.52083 0.7708333  2.7
## 960   960 -77.47917 0.7708333  2.3
## 961   961 -77.31250 0.7708333  3.0
## 962   962 -77.27083 0.7708333  2.8
## 963   963 -77.18750 0.7708333  1.6
## 964   964 -77.64583 0.7291667  2.4
## 965   965 -77.60417 0.7291667  2.4
## 966   966 -77.56250 0.7291667  2.3
## 967   967 -77.52083 0.7291667  2.6
## 968   968 -77.47917 0.7291667  3.0
## 969   969 -77.43750 0.7291667  2.5
## 970   970 -77.39583 0.7291667  2.9
## 971   971 -77.22917 0.7291667  1.9
## 972   972 -77.18750 0.7291667  1.7
## 973   973 -77.56250 0.6875000  2.7
## 974   974 -77.52083 0.6875000  3.7
## 975   975 -77.43750 0.6875000  2.5
## 976   976 -77.35417 0.6875000  1.7
## 977   977 -77.31250 0.6875000  1.6
## 978   978 -77.47917 0.6458333  3.9
## 979   979 -77.43750 0.6458333  2.1
## 980   980 -77.39583 0.6458333  1.5
## 981   981 -77.35417 0.6458333  1.3
## 982   982 -77.31250 0.6458333  2.1
## 983   983 -77.27083 0.6458333  1.8
## 984   984 -77.22917 0.6458333  1.2
## 985   985 -77.18750 0.6458333  1.0
## 986   986 -77.43750 0.6041667  2.2
## 987   987 -77.39583 0.6041667  1.3
## 988   988 -77.35417 0.6041667  1.5
## 989   989 -77.31250 0.6041667  2.0
## 990   990 -77.27083 0.6041667  1.4
## 991   991 -77.22917 0.6041667  0.8
## 992   992 -77.14583 0.6041667  0.8
## 993   993 -77.47917 0.5625000  2.5
## 994   994 -77.43750 0.5625000  1.5
## 995   995 -77.39583 0.5625000  1.5
## 996   996 -77.35417 0.5625000  2.1
## 997   997 -77.31250 0.5625000  1.5
## 998   998 -77.27083 0.5625000  1.0
## 999   999 -77.52083 0.5208333  3.6
## 1000 1000 -77.35417 0.5208333  1.8
## 1001 1001 -77.31250 0.5208333  1.2
## 1002 1002 -77.27083 0.5208333  0.6
## 1003 1003 -77.22917 0.5208333  0.8
## 1004 1004 -77.18750 0.5208333  0.8
## 1005 1005 -77.52083 0.4791667  3.6
## 1006 1006 -77.47917 0.4791667  2.2
## 1007 1007 -77.43750 0.4791667  1.7
## 1008 1008 -77.39583 0.4791667  2.1
## 1009 1009 -77.31250 0.4791667  0.8
## 1010 1010 -77.27083 0.4791667  0.8
## 1011 1011 -77.18750 0.4791667  0.8
## 1012 1012 -77.14583 0.4791667  0.7
## 1013 1013 -77.39583 0.4375000  1.7
## 1014 1014 -77.35417 0.4375000  1.1
## 1015 1015 -77.31250 0.4375000  0.7
## 1016 1016 -77.27083 0.4375000  0.8
## 1017 1017 -77.18750 0.4375000  0.7
## 1018 1018 -77.14583 0.4375000  0.7
## 1019 1019 -77.35417 0.3958333  0.7
## 1020 1020 -77.31250 0.3958333  0.6
## 1021 1021 -77.27083 0.3958333  0.7
## 1022 1022 -77.22917 0.3958333  0.7
## 1023 1023 -77.18750 0.3958333  0.7
## 1024 1024 -77.14583 0.3958333  0.7
## 1025 1025 -77.10417 0.3958333  0.7

id

##    [1]    1    2    3    4    5    6    7    8    9   10   11   12   13   14
##   [15]   15   16   17   18   19   20   21   22   23   24   25   26   27   28
##   [29]   29   30   31   32   33   34   35   36   37   38   39   40   41   42
##   [43]   43   44   45   46   47   48   49   50   51   52   53   54   55   56
##   [57]   57   58   59   60   61   62   63   64   65   66   67   68   69   70
##   [71]   71   72   73   74   75   76   77   78   79   80   81   82   83   84
##   [85]   85   86   87   88   89   90   91   92   93   94   95   96   97   98
##   [99]   99  100  101  102  103  104  105  106  107  108  109  110  111  112
##  [113]  113  114  115  116  117  118  119  120  121  122  123  124  125  126
##  [127]  127  128  129  130  131  132  133  134  135  136  137  138  139  140
##  [141]  141  142  143  144  145  146  147  148  149  150  151  152  153  154
##  [155]  155  156  157  158  159  160  161  162  163  164  165  166  167  168
##  [169]  169  170  171  172  173  174  175  176  177  178  179  180  181  182
##  [183]  183  184  185  186  187  188  189  190  191  192  193  194  195  196
##  [197]  197  198  199  200  201  202  203  204  205  206  207  208  209  210
##  [211]  211  212  213  214  215  216  217  218  219  220  221  222  223  224
##  [225]  225  226  227  228  229  230  231  232  233  234  235  236  237  238
##  [239]  239  240  241  242  243  244  245  246  247  248  249  250  251  252
##  [253]  253  254  255  256  257  258  259  260  261  262  263  264  265  266
##  [267]  267  268  269  270  271  272  273  274  275  276  277  278  279  280
##  [281]  281  282  283  284  285  286  287  288  289  290  291  292  293  294
##  [295]  295  296  297  298  299  300  301  302  303  304  305  306  307  308
##  [309]  309  310  311  312  313  314  315  316  317  318  319  320  321  322
##  [323]  323  324  325  326  327  328  329  330  331  332  333  334  335  336
##  [337]  337  338  339  340  341  342  343  344  345  346  347  348  349  350
##  [351]  351  352  353  354  355  356  357  358  359  360  361  362  363  364
##  [365]  365  366  367  368  369  370  371  372  373  374  375  376  377  378
##  [379]  379  380  381  382  383  384  385  386  387  388  389  390  391  392
##  [393]  393  394  395  396  397  398  399  400  401  402  403  404  405  406
##  [407]  407  408  409  410  411  412  413  414  415  416  417  418  419  420
##  [421]  421  422  423  424  425  426  427  428  429  430  431  432  433  434
##  [435]  435  436  437  438  439  440  441  442  443  444  445  446  447  448
##  [449]  449  450  451  452  453  454  455  456  457  458  459  460  461  462
##  [463]  463  464  465  466  467  468  469  470  471  472  473  474  475  476
##  [477]  477  478  479  480  481  482  483  484  485  486  487  488  489  490
##  [491]  491  492  493  494  495  496  497  498  499  500  501  502  503  504
##  [505]  505  506  507  508  509  510  511  512  513  514  515  516  517  518
##  [519]  519  520  521  522  523  524  525  526  527  528  529  530  531  532
##  [533]  533  534  535  536  537  538  539  540  541  542  543  544  545  546
##  [547]  547  548  549  550  551  552  553  554  555  556  557  558  559  560
##  [561]  561  562  563  564  565  566  567  568  569  570  571  572  573  574
##  [575]  575  576  577  578  579  580  581  582  583  584  585  586  587  588
##  [589]  589  590  591  592  593  594  595  596  597  598  599  600  601  602
##  [603]  603  604  605  606  607  608  609  610  611  612  613  614  615  616
##  [617]  617  618  619  620  621  622  623  624  625  626  627  628  629  630
##  [631]  631  632  633  634  635  636  637  638  639  640  641  642  643  644
##  [645]  645  646  647  648  649  650  651  652  653  654  655  656  657  658
##  [659]  659  660  661  662  663  664  665  666  667  668  669  670  671  672
##  [673]  673  674  675  676  677  678  679  680  681  682  683  684  685  686
##  [687]  687  688  689  690  691  692  693  694  695  696  697  698  699  700
##  [701]  701  702  703  704  705  706  707  708  709  710  711  712  713  714
##  [715]  715  716  717  718  719  720  721  722  723  724  725  726  727  728
##  [729]  729  730  731  732  733  734  735  736  737  738  739  740  741  742
##  [743]  743  744  745  746  747  748  749  750  751  752  753  754  755  756
##  [757]  757  758  759  760  761  762  763  764  765  766  767  768  769  770
##  [771]  771  772  773  774  775  776  777  778  779  780  781  782  783  784
##  [785]  785  786  787  788  789  790  791  792  793  794  795  796  797  798
##  [799]  799  800  801  802  803  804  805  806  807  808  809  810  811  812
##  [813]  813  814  815  816  817  818  819  820  821  822  823  824  825  826
##  [827]  827  828  829  830  831  832  833  834  835  836  837  838  839  840
##  [841]  841  842  843  844  845  846  847  848  849  850  851  852  853  854
##  [855]  855  856  857  858  859  860  861  862  863  864  865  866  867  868
##  [869]  869  870  871  872  873  874  875  876  877  878  879  880  881  882
##  [883]  883  884  885  886  887  888  889  890  891  892  893  894  895  896
##  [897]  897  898  899  900  901  902  903  904  905  906  907  908  909  910
##  [911]  911  912  913  914  915  916  917  918  919  920  921  922  923  924
##  [925]  925  926  927  928  929  930  931  932  933  934  935  936  937  938
##  [939]  939  940  941  942  943  944  945  946  947  948  949  950  951  952
##  [953]  953  954  955  956  957  958  959  960  961  962  963  964  965  966
##  [967]  967  968  969  970  971  972  973  974  975  976  977  978  979  980
##  [981]  981  982  983  984  985  986  987  988  989  990  991  992  993  994
##  [995]  995  996  997  998  999 1000 1001 1002 1003 1004 1005 1006 1007 1008
## [1009] 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022
## [1023] 1023 1024 1025

m <- leaflet() %>%
  addTiles() %>%  
  leafem:::addGeoRaster(
      precip.mask,
      opacity = 0.7,                
      colorOptions = colorOptions(palette = c("orange", "yellow", "cyan", "blue"), 
                                  domain = 15:400)
    ) %>%
  addMarkers(lng=sitios$longit,lat=sitios$latit, popup=sitios$rain, clusterOptions = markerClusterOptions())
m 

Digital elevation model

(dem = read_stars("/cloud/project/nuevodemnarino.tif"))

## stars object with 2 dimensions and 1 attribute
## attribute(s):
##                     Min. 1st Qu. Median     Mean 3rd Qu. Max.  NA's
## nuevodemnarino.tif    -4      58    663 1145.102    2148 4597 36656
## dimension(s):
##   from  to   offset       delta refsys point values x/y
## x    1 262 -79.0167  0.00833333 WGS 84 FALSE   NULL [x]
## y    1 279  2.68333 -0.00833333 WGS 84 FALSE   NULL [y]

pal.dem <- colorNumeric(palette = c("forestgreen", "green", "yellow", "brown", "lightcyan"), domain = 500:4000, na.color = "transparent")

m <- leaflet() %>%
  addTiles() %>%  
  leafem:::addGeoRaster(
      dem,
      opacity = 0.7,                
      colorOptions = colorOptions(palette = c("forestgreen", "green", "yellow",  "brown",         "lightcyan"), 
                                  domain = 500:4000)
    ) %>%
  addMarkers(lng=sitios$longit,lat=sitios$latit, popup=sitios$rain, clusterOptions = markerClusterOptions()) %>%
  addLegend("bottomright", pal = pal.dem, values= dem$nuevodemnarino.tif,
    title = "Elevation")

## Warning in pal(c(r[1], cuts, r[2])): Some values were outside the color scale
## and will be treated as NA

m

st_crs(dem) <- st_crs(train)

(train = st_join(train, st_as_sf(dem)))

## Simple feature collection with 1025 features and 2 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -78.9375 ymin: 0.3958333 xmax: -76.85417 ymax: 2.645833
## Geodetic CRS:  WGS 84
## First 10 features:
##    precip.tif nuevodemnarino.tif                   geometry
## 1         0.5                  1 POINT (-78.35417 2.645833)
## 3         0.4                  1 POINT (-78.27083 2.645833)
## 6         0.1                  1 POINT (-78.14583 2.645833)
## 7         0.4                  1 POINT (-78.10417 2.645833)
## 8         0.1                  1 POINT (-77.97917 2.645833)
## 10        0.2                  1  POINT (-78.3125 2.604167)
## 11        1.0                  1 POINT (-78.27083 2.604167)
## 12        0.2                  1 POINT (-78.22917 2.604167)
## 14        1.4                  1 POINT (-78.14583 2.604167)
## 15        1.4                  1 POINT (-78.10417 2.604167)

train = train[!is.na(train$nuevodemnarino), ]

names(train) <- c("precip", "elev", "geometry")

train

## Simple feature collection with 1019 features and 2 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -78.9375 ymin: 0.3958333 xmax: -76.85417 ymax: 2.645833
## Geodetic CRS:  WGS 84
## First 10 features:
##    precip elev                   geometry
## 1     0.5    1 POINT (-78.35417 2.645833)
## 3     0.4    1 POINT (-78.27083 2.645833)
## 6     0.1    1 POINT (-78.14583 2.645833)
## 7     0.4    1 POINT (-78.10417 2.645833)
## 8     0.1    1 POINT (-77.97917 2.645833)
## 10    0.2    1  POINT (-78.3125 2.604167)
## 11    1.0    1 POINT (-78.27083 2.604167)
## 12    0.2    1 POINT (-78.22917 2.604167)
## 14    1.4    1 POINT (-78.14583 2.604167)
## 15    1.4    1 POINT (-78.10417 2.604167)

IDW

g1 = gstat(formula = precip ~ 1, data = train)

z1 = predict(g1, dem)

## [inverse distance weighted interpolation]

z1

## stars object with 2 dimensions and 2 attributes
## attribute(s):
##                    Min.   1st Qu.    Median     Mean  3rd Qu. Max.  NA's
## var1.pred  1.445036e-10 0.1493455 0.8082083 1.408223 2.329824 11.8 36656
## var1.var             NA        NA        NA      NaN       NA   NA 73098
## dimension(s):
##   from  to   offset       delta refsys point values x/y
## x    1 262 -79.0167  0.00833333 WGS 84    NA   NULL [x]
## y    1 279  2.68333 -0.00833333 WGS 84    NA   NULL [y]

z1 = z1["var1.pred",,]
names(z1) = "precipitation"

b = seq(1, 200, 1)
plot(z1, breaks = b, col = hcl.colors(length(b)-1, "Spectral"), reset = FALSE)
plot(st_geometry(train), pch = 3, add = TRUE)
contour(z1, breaks = b, add = TRUE)

v_emp_ok = variogram(precip ~ 1, data=train)

plot(v_emp_ok)

v_mod_ok = autofitVariogram(precip ~ 1, as(train, "Spatial"))

plot(v_mod_ok)

v_mod_ok$var_model

##   model    psill    range kappa
## 1   Nug  0.00000    0.000   0.0
## 2   Ste 30.38808 1348.683   0.4

g2 = gstat(formula = precip ~ 1, model = v_mod_ok$var_model, data = train)
z2= predict(g2, dem)

## [using ordinary kriging]

z2 = z2["var1.pred",,]
names(z2) = "precip"

b = seq(1, 200, 1)
plot(z2, breaks = b, col = hcl.colors(length(b)-1, "Spectral"), reset = FALSE)
plot(st_geometry(train), pch = 3, add = TRUE)
contour(z2, breaks = b, add = TRUE)

Universal Kriging

v_emp_uk = variogram(precip ~ elev, train)
train.sp = as(train, "Spatial")
v_mod_uk = autofitVariogram(precip ~ elev, train.sp)

plot(v_emp_ok, model = v_mod_ok$var_model, ylim = c(0, 20), main = "OK")

plot(v_emp_uk, model = v_mod_uk$var_model, ylim = c(0, 20), main = "UK")

g3 = gstat(formula = precip ~ elev, model = v_mod_uk$var_model, data = train.sp)

names(dem)

## [1] "nuevodemnarino.tif"

names(dem) <- "elev"

z3 = predict(g3, dem)

## [using universal kriging]

z3 = z3["var1.pred",,]
names(z3) = "precipitation"

b = seq(1, 200, 1)
plot(z3, breaks = b, col = hcl.colors(length(b)-1, "Spectral"), reset = FALSE)
plot(st_geometry(train), pch = 3, add = TRUE)
contour(z3, breaks = b, add = TRUE)

Qualitative assessment of results

paleta <- colorNumeric(palette = c("orange", "yellow", "lightcyan", "blue", "darkblue"), domain = 10:400, na.color = "transparent")

colores <- colorOptions(palette = c("orange", "yellow", "lightcyan", "blue", "darkblue"), domain = 10:400, na.color = "transparent")

m <- leaflet() %>%
  addTiles() %>%  
  addGeoRaster(z1, opacity = 0.7, colorOptions = colores, group="IDW") %>%
  addGeoRaster(z2, colorOptions = colores, opacity = 0.7, group= "OK")  %>%
  addGeoRaster(z3, colorOptions = colores, opacity = 0.7, group= "UK")  %>%
  # Add layers controls
  addLayersControl(
    overlayGroups = c("UK", "OK", "IDW"),
    options = layersControlOptions(collapsed = FALSE)
  ) %>% 
  
    addLegend("bottomright", pal = paleta, values= z1$precipitation,
    title = "Precipitation (2019)"
  )

## Warning in pal(c(r[1], cuts, r[2])): Some values were outside the color scale
## and will be treated as NA

m 

Cross validation

cv1 = gstat.cv(g1)

## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]
## [inverse distance weighted interpolation]

cv1 = st_as_sf(cv1)

bubble(as(cv1[, "residual"], "Spatial"))

sqrt(sum((cv1$var1.pred - cv1$observed)^2) / nrow(cv1))

## [1] 0.923583

Bibliografia Lizarazo, I., 2022. Spatial interpolation of climate data. Available at https://rpubs.com/ials2un/clim_interp.