##Taller de Iterpolación

instalacion de datos, SIOL GRIDS

se instalan las librerias necesarias

library(dplyr)
## Warning: package 'dplyr' was built under R version 4.3.3
## 
## 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
library(htmltools)
## Warning: package 'htmltools' was built under R version 4.3.3
library(sf)
## Warning: package 'sf' was built under R version 4.3.3
## Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; sf_use_s2() is TRUE
library(stars)
## Warning: package 'stars' was built under R version 4.3.3
## Loading required package: abind
library(leaflet)
library(gstat)
## Warning: package 'gstat' was built under R version 4.3.3
library(automap)
## Warning: package 'automap' was built under R version 4.3.3
library(raster)
## Loading required package: sp
## Warning: package 'sp' was built under R version 4.3.3
## 
## Attaching package: 'raster'
## The following object is masked from 'package:dplyr':
## 
##     select
library(RColorBrewer)
library(XML)
## Warning: package 'XML' was built under R version 4.3.3
#library(rgdal)
library(dplyr)
library(devtools)
## Warning: package 'devtools' was built under R version 4.3.3
## Loading required package: usethis
## Warning: package 'usethis' was built under R version 4.3.3
library(stars)
library(mapview)
## Warning: package 'mapview' was built under R version 4.3.3
library(RColorBrewer)
library(terra)
## Warning: package 'terra' was built under R version 4.3.3
## terra 1.8.21
#install.packages("gdalUtilities")
library(gdalUtilities)
## 
## Attaching package: 'gdalUtilities'
## The following object is masked from 'package:sf':
## 
##     gdal_rasterize
library(leaflet)

Se crea una coneccion con GDAUTILITIES

devtools::install_github("JoshOBrien/gdalUtilities")
## Skipping install of 'gdalUtilities' from a github remote, the SHA1 (3d87b464) has not changed since last install.
##   Use `force = TRUE` to force installation

Creamos una interface con Soil Grids,, donde especificamos las variables que vamos a reequerir.

url = "https://files.isric.org/soilgrids/latest/data/"
voi = "soc"
depth = "15-30cm"
quantile = "mean"
(variable = paste(url, voi, sep = ""))
## [1] "https://files.isric.org/soilgrids/latest/data/soc"
(layer = paste(variable,depth,quantile, sep = "_"))
## [1] "https://files.isric.org/soilgrids/latest/data/soc_15-30cm_mean"
(vrt_layer = paste(layer, '.vrt', sep = "" )) 
## [1] "https://files.isric.org/soilgrids/latest/data/soc_15-30cm_mean.vrt"

Cargamos la capa del municipio con el que se trabajara (MOCOA)

(stder = st_read("C:/Users/ASUS/Desktop/geomatica/r/mocoa9377/mocoa_9377.shp"))
## Reading layer `mocoa_9377' from data source 
##   `C:\Users\ASUS\Desktop\geomatica\r\mocoa9377\mocoa_9377.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 1 feature and 91 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: 4563568 ymin: 1654181 xmax: 4620518 ymax: 1720503
## Projected CRS: MAGNA-SIRGAS 2018 / Origen-Nacional
## Simple feature collection with 1 feature and 91 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: 4563568 ymin: 1654181 xmax: 4620518 ymax: 1720503
## Projected CRS: MAGNA-SIRGAS 2018 / Origen-Nacional
##   DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CDPMP VERSION       AREA  LATITUD
## 1         86        001      MOCOA      86001    2018 1304637880 1.228575
##    LONGITUD STCTNENCUE STP3_1_SI STP3_2_NO STP3A_RI STP3B_TCN STP4_1_SI
## 1 -76.68436      24015       391     23624      391         0        34
##   STP4_2_NO STP9_1_USO STP9_2_USO STP9_3_USO STP9_4_USO STP9_2_1_M STP9_2_2_M
## 1     23981      18049        527       5424         15         19        411
##   STP9_2_3_M STP9_2_4_M STP9_2_9_M STP9_3_1_N STP9_3_2_N STP9_3_3_N STP9_3_4_N
## 1         95          2          0         41        823        312        799
##   STP9_3_5_N STP9_3_6_N STP9_3_7_N STP9_3_8_N STP9_3_9_N STP9_3_10 STP9_3_99
## 1        190       2754         56          5        117       311        16
##   STVIVIENDA STP14_1_TI STP14_2_TI STP14_3_TI STP14_4_TI STP14_5_TI STP14_6_TI
## 1      18576      12610       4035       1671        179          5         76
##   STP15_1_OC STP15_2_OC STP15_3_OC STP15_4_OC TSP16_HOG STP19_EC_1 STP19_ES_2
## 1      15870        990        509       1207     18556      15146        724
##   STP19_EE_1 STP19_EE_2 STP19_EE_3 STP19_EE_4 STP19_EE_5 STP19_EE_6 STP19_EE_9
## 1      12057       2170        470         10          4         11        424
##   STP19_ACU1 STP19_ACU2 STP19_ALC1 STP19_ALC2 STP19_GAS1 STP19_GAS2 STP19_GAS9
## 1      14482       1388      11469       4401       2714      13021        135
##   STP19_REC1 STP19_REC2 STP19_INT1 STP19_INT2 STP19_INT9 STP27_PERS STPERSON_L
## 1      12676       3194       4155      11580        135      48422        585
##   STPERSON_S STP32_1_SE STP32_2_SE STP34_1_ED STP34_2_ED STP34_3_ED STP34_4_ED
## 1      47837      23870      24552       7099       9060       9359       7939
##   STP34_5_ED STP34_6_ED STP34_7_ED STP34_8_ED STP34_9_ED STP51_PRIM STP51_SECU
## 1       5924       4308       2576       1451        706      14525      18219
##   STP51_SUPE STP51_POST STP51_13_E STP51_99_E Shape_Leng Shape_Area Codigo_Mun
## 1       8370       1743       1437        622   2.475228  0.1057929      86001
##                         geometry
## 1 POLYGON ((4591580 1720503, ...
stder %>% as_tibble()
## # A tibble: 1 × 92
##   DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CDPMP VERSION      AREA LATITUD LONGITUD
##   <chr>      <chr>      <chr>      <chr>        <int>     <dbl>   <dbl>    <dbl>
## 1 86         001        MOCOA      86001         2018    1.30e9    1.23    -76.7
## # ℹ 84 more variables: STCTNENCUE <dbl>, STP3_1_SI <dbl>, STP3_2_NO <dbl>,
## #   STP3A_RI <dbl>, STP3B_TCN <dbl>, STP4_1_SI <dbl>, STP4_2_NO <dbl>,
## #   STP9_1_USO <dbl>, STP9_2_USO <dbl>, STP9_3_USO <dbl>, STP9_4_USO <dbl>,
## #   STP9_2_1_M <dbl>, STP9_2_2_M <dbl>, STP9_2_3_M <dbl>, STP9_2_4_M <dbl>,
## #   STP9_2_9_M <dbl>, STP9_3_1_N <dbl>, STP9_3_2_N <dbl>, STP9_3_3_N <dbl>,
## #   STP9_3_4_N <dbl>, STP9_3_5_N <dbl>, STP9_3_6_N <dbl>, STP9_3_7_N <dbl>,
## #   STP9_3_8_N <dbl>, STP9_3_9_N <dbl>, STP9_3_10 <dbl>, STP9_3_99 <dbl>, …

Reproyectamos a WGS*$ donde se va a trabajar de ahora en adelante

repro = '+proj=igh +lat_0=0 +lon_0=0 +datum=WGS84 +units=m +no_defs'
stder_reproj = st_transform(stder, repro)

Definimos el bounding box

(box = st_bbox(stder_reproj))
##        xmin        ymin        xmax        ymax 
## -8563580.19    96684.14 -8506228.35   163340.79

Guardamos el bbox en una variable

ulx = box$xmin
uly = box$ymax
lrx = box$xmax
lry = box$ymin
(bbx = c(ulx, uly, lrx,lry))
##        xmin        ymax        xmax        ymin 
## -8563580.19   163340.79 -8506228.35    96684.14

se guardan las rutas en variables

sg_url="/vsicurl/https://files.isric.org/soilgrids/latest/data/"
datos = 'soc/soc_15-30cm_mean.vrt'
file = "C:/Users/ASUS/Desktop/geomatica/rsoc_igh_15_30.tif"

Ahora se va a proceder a descargar los datos con los que vamos a trabajar

#gdal_translate(paste0(sg_url,datos), file ,
  #            tr=c(250,250),
   #           projwin=bbx, 
    #         projwin_srs =repro)

se DIviden los datos en 10, para hacer un tipo de “estandarizacion”

(stder_soc_soil = terra::rast(file)/10)
## class       : SpatRaster 
## dimensions  : 267, 229, 1  (nrow, ncol, nlyr)
## resolution  : 250, 250  (x, y)
## extent      : -8563750, -8506500, 96750, 163500  (xmin, xmax, ymin, ymax)
## coord. ref. : Interrupted_Goode_Homolosine 
## source(s)   : memory
## varname     : rsoc_igh_15_30 
## name        : rsoc_igh_15_30 
## min value   :           20.4 
## max value   :          201.9

Hallamos la media de los datos tomoados. (SOC)

(media_soc = mean(values(stder_soc_soil), na.rm = T))
## [1] 81.52724

graficamos los datos en un histograma

par(bg = "black")
terra::hist(stder_soc_soil,
       main = "carbono_org del suelo (15-30).",
       xlab = "g/Kg",
       col = "darkred",
       col.lab = "white",
       col.main = "white",
       col.axis = "white",
       border = "white",
       xaxt = "n",
       yaxt = "n"
       )
axis(1,col = "white", col.axis = "white")
axis(2,col = "white", col.axis = "white")
abline(v = media_soc, col = "green",lwd = 2, lty = 1)

Hacemos un resumen de los datos

summary(stder_soc_soil)
##  rsoc_igh_15_30  
##  Min.   : 20.40  
##  1st Qu.: 51.40  
##  Median : 75.60  
##  Mean   : 81.53  
##  3rd Qu.:113.00  
##  Max.   :201.90  
##  NA's   :170

asignamos el nombre “soc”a la varianble SOC del suelo

(names(stder_soc_soil) <-  "soc")
## [1] "soc"

Se le asignan los valores SOC a la variable

val = values(stder_soc_soil, na.rm = T)

Procedemos a crear una paleta de colores para mapear

orangecyan = colorNumeric(c("orange","yellow2", "darkseagreen", "cyan" ), val,
  na.color = "transparent")
leaflet::leaflet(stder) %>% 
  addTiles() %>% 
  setView(-74, 6, 9) %>% 
   addPolygons(color = "gray", weight = 1.0, smoothFactor = 0.5,
    opacity = 0.5, fillOpacity = 0.10,
    popup = paste("Municipio: ", stder$MPIO_CNMBR)) %>%
  addRasterImage(stder_soc_soil, colors ="Spectral", opacity = 0.8)  %>%
  addLegend(pal = orangecyan, values = val, title = "Soil Organic Carbon (SOC) [g/kg]")
## Warning: sf layer is not long-lat data
## Warning: sf layer has inconsistent datum (+proj=tmerc +lat_0=4 +lon_0=-73 +k=0.9992 +x_0=5000000 +y_0=2000000 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs).
## Need '+proj=longlat +datum=WGS84'

Ahora procedemos a obtener las muestras

set.seed(123446)
geog ="+proj=longlat +datum=WGS84"
(geog.soc = project(stder_soc_soil, geog))
## class       : SpatRaster 
## dimensions  : 268, 232, 1  (nrow, ncol, nlyr)
## resolution  : 0.002236802, 0.002236802  (x, y)
## extent      : -76.92682, -76.40788, 0.8692825, 1.468745  (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +no_defs 
## source(s)   : memory
## name        :       soc 
## min value   :  21.06569 
## max value   : 199.89177

Tomamos muestras aleatorias de 200 puntos

(samples = terra::spatSample(geog.soc, 2000, "random", as.points=TRUE))
##  class       : SpatVector 
##  geometry    : points 
##  dimensions  : 2000, 1  (geometries, attributes)
##  extent      : -76.9257, -76.409, 0.8704009, 1.467627  (xmin, xmax, ymin, ymax)
##  coord. ref. : +proj=longlat +datum=WGS84 +no_defs 
##  names       :   soc
##  type        : <num>
##  values      : 71.67
##                143.2
##                118.7

Lom convertimos a un objeto sf

(muestras <- sf::st_as_sf(samples))
## Simple feature collection with 2000 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -76.9257 ymin: 0.8704009 xmax: -76.409 ymax: 1.467627
## Geodetic CRS:  GEOGCRS["unknown",
##     DATUM["World Geodetic System 1984",
##         ELLIPSOID["WGS 84",6378137,298.257223563,
##             LENGTHUNIT["metre",1]],
##         ID["EPSG",6326]],
##     PRIMEM["Greenwich",0,
##         ANGLEUNIT["degree",0.0174532925199433],
##         ID["EPSG",8901]],
##     CS[ellipsoidal,2],
##         AXIS["longitude",east,
##             ORDER[1],
##             ANGLEUNIT["degree",0.0174532925199433,
##                 ID["EPSG",9122]]],
##         AXIS["latitude",north,
##             ORDER[2],
##             ANGLEUNIT["degree",0.0174532925199433,
##                 ID["EPSG",9122]]]]
## First 10 features:
##          soc                    geometry
## 1   71.67126  POINT (-76.76913 1.281973)
## 2  143.23447   POINT (-76.68189 1.13658)
## 3  118.68003  POINT (-76.8407 0.9777674)
## 4   37.61918   POINT (-76.4269 1.268552)
## 5   86.49920  POINT (-76.87873 1.422891)
## 6  111.73273  POINT (-76.6461 0.9240841)
## 7   43.29821  POINT (-76.75571 1.214868)
## 8   58.80977 POINT (-76.41795 0.9464522)
## 9   67.68050  POINT (-76.85636 1.058292)
## 10  78.52149 POINT (-76.74899 0.9621098)

Prganizamos la informacion como un tibble

muestras %>% as_tibble()
## # A tibble: 2,000 × 2
##      soc              geometry
##    <dbl>           <POINT [°]>
##  1  71.7  (-76.76913 1.281973)
##  2 143.    (-76.68189 1.13658)
##  3 119.   (-76.8407 0.9777674)
##  4  37.6   (-76.4269 1.268552)
##  5  86.5  (-76.87873 1.422891)
##  6 112.   (-76.6461 0.9240841)
##  7  43.3  (-76.75571 1.214868)
##  8  58.8 (-76.41795 0.9464522)
##  9  67.7  (-76.85636 1.058292)
## 10  78.5 (-76.74899 0.9621098)
## # ℹ 1,990 more rows

Omintimos los valores NA

(nmuestras <- na.omit(muestras))
## Simple feature collection with 1971 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -76.9257 ymin: 0.8704009 xmax: -76.409 ymax: 1.467627
## Geodetic CRS:  GEOGCRS["unknown",
##     DATUM["World Geodetic System 1984",
##         ELLIPSOID["WGS 84",6378137,298.257223563,
##             LENGTHUNIT["metre",1]],
##         ID["EPSG",6326]],
##     PRIMEM["Greenwich",0,
##         ANGLEUNIT["degree",0.0174532925199433],
##         ID["EPSG",8901]],
##     CS[ellipsoidal,2],
##         AXIS["longitude",east,
##             ORDER[1],
##             ANGLEUNIT["degree",0.0174532925199433,
##                 ID["EPSG",9122]]],
##         AXIS["latitude",north,
##             ORDER[2],
##             ANGLEUNIT["degree",0.0174532925199433,
##                 ID["EPSG",9122]]]]
## First 10 features:
##          soc                    geometry
## 1   71.67126  POINT (-76.76913 1.281973)
## 2  143.23447   POINT (-76.68189 1.13658)
## 3  118.68003  POINT (-76.8407 0.9777674)
## 4   37.61918   POINT (-76.4269 1.268552)
## 5   86.49920  POINT (-76.87873 1.422891)
## 6  111.73273  POINT (-76.6461 0.9240841)
## 7   43.29821  POINT (-76.75571 1.214868)
## 8   58.80977 POINT (-76.41795 0.9464522)
## 9   67.68050  POINT (-76.85636 1.058292)
## 10  78.52149 POINT (-76.74899 0.9621098)

visualizamos los datos ya limpios

longit <- st_coordinates(nmuestras)[,1]
latit <- st_coordinates(nmuestras)[,2]
soc <- nmuestras$soc
summary(soc)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   24.16   51.69   75.37   80.90  109.74  175.89
length(soc)
## [1] 1971
id <- seq(1,1971,1)
(sitios <- data.frame(id, longit, latit, soc))
##        id    longit     latit       soc
## 1       1 -76.76913 1.2819725  71.67126
## 2       2 -76.68189 1.1365804 143.23447
## 3       3 -76.84070 0.9777674 118.68003
## 4       4 -76.42690 1.2685517  37.61918
## 5       5 -76.87873 1.4228910  86.49920
## 6       6 -76.64610 0.9240841 111.73273
## 7       7 -76.75571 1.2148684  43.29821
## 8       8 -76.41795 0.9464522  58.80977
## 9       9 -76.85636 1.0582923  67.68050
## 10     10 -76.74899 0.9621098  78.52149
## 11     11 -76.78255 1.3513134  73.44880
## 12     12 -76.92123 1.1611852  79.53983
## 13     13 -76.66847 0.9240841 122.96414
## 14     14 -76.76018 1.2439469  87.28555
## 15     15 -76.45597 0.8927689  50.00249
## 16     16 -76.58571 0.9375050 120.91035
## 17     17 -76.73557 1.4564431  67.83961
## 18     18 -76.82952 1.4296015  86.63875
## 19     19 -76.89215 1.0650027  62.55627
## 20     20 -76.67518 0.9978986 156.18198
## 21     21 -76.54768 0.9710570 118.89071
## 22     22 -76.84518 1.1388172  73.17078
## 23     23 -76.57229 0.9129001 120.77886
## 24     24 -76.84741 1.3468398  88.17035
## 25     25 -76.71768 0.8815849 123.10968
## 26     26 -76.67071 1.2976301  49.49654
## 27     27 -76.81163 1.0046090  61.38388
## 28     28 -76.52308 1.3759182  31.87302
## 29     29 -76.69084 0.9330314 122.85299
## 30     30 -76.60584 1.1522380  60.04544
## 31     31 -76.75123 1.3736814  73.32985
## 32     32 -76.81163 1.1567116  68.63271
## 33     33 -76.92123 1.3334190  70.37281
## 34     34 -76.54097 1.0784235 103.33555
## 35     35 -76.50742 1.3446030  27.36186
## 36     36 -76.57005 1.3647342  30.00546
## 37     37 -76.56334 1.1097387 126.24452
## 38     38 -76.52084 1.4586799  53.96438
## 39     39 -76.74228 1.4363119  44.58170
## 40     40 -76.71544 0.9084265 126.01104
## 41     41 -76.44479 1.1880268  66.67337
## 42     42 -76.60360 0.9665834 128.43379
## 43     43 -76.81386 1.2305261  65.86182
## 44     44 -76.52755 1.2886829  38.10500
## 45     45 -76.71321 1.4184174  55.20300
## 46     46 -76.77584 1.2349997  66.69662
## 47     47 -76.41795 1.1835532  82.68179
## 48     48 -76.55663 0.9755306 131.72096
## 49     49 -76.91899 1.2417101 100.89314
## 50     50 -76.78255 1.0717131  80.29574
## 51     51 -76.65505 1.2976301  42.02178
## 52     52 -76.52308 1.1567116 154.92256
## 53     53 -76.71992 1.2439469  87.56034
## 54     54 -76.45597 1.3669710  40.09740
## 55     55 -76.57900 0.9576362 130.87976
## 56     56 -76.59689 0.9419786 128.67300
## 57     57 -76.77360 0.9553994  79.09003
## 58     58 -76.53203 1.1231595  97.68011
## 59     59 -76.76913 1.2260524  66.16808
## 60     60 -76.80939 1.4318383  63.04519
## 61     61 -76.92570 0.9956618  76.07687
## 62     62 -76.87649 1.2349997  89.46719
## 63     63 -76.79597 1.4273646  72.68352
## 64     64 -76.68189 1.0157930 139.53656
## 65     65 -76.61479 0.9755306 135.48688
## 66     66 -76.59466 1.1723692  53.66172
## 67     67 -76.50295 0.9553994 125.50578
## 68     68 -76.49400 1.1231595  80.47469
## 69     69 -76.42690 1.0940811 152.48280
## 70     70 -76.79373 1.2215788  52.03752
## 71     71 -76.67965 1.4497327  39.39433
## 72     72 -76.81163 0.9978986  80.63074
## 73     73 -76.52979 1.1477644  69.00044
## 74     74 -76.89439 1.2551309  95.60816
## 75     75 -76.54321 1.2842093  37.65648
## 76     76 -76.42466 1.2506573  55.61860
## 77     77 -76.54992 1.2752621  31.31278
## 78     78 -76.76242 1.0269770  54.35604
## 79     79 -76.87202 0.9777674  96.12783
## 80     80 -76.74899 1.0493451  88.86375
## 81     81 -76.70873 1.4228910  45.85566
## 82     82 -76.72215 0.9934250 147.63445
## 83     83 -76.86083 0.9442154 105.28221
## 84     84 -76.65281 1.1969740 125.02473
## 85     85 -76.66847 0.9755306 130.33127
## 86     86 -76.80044 0.9039529  57.93962
## 87     87 -76.52308 1.4631535  53.47540
## 88     88 -76.88544 1.0023722  74.33939
## 89     89 -76.75571 1.2349997  79.32888
## 90     90 -76.90110 0.9553994  84.56300
## 91     91 -76.83176 1.0851339  93.01517
## 92     92 -76.51637 1.1723692  67.12978
## 93     93 -76.42242 1.4027598  51.60087
## 94     94 -76.90110 1.1656588  90.43356
## 95     95 -76.73110 1.2148684  36.74587
## 96     96 -76.81610 1.3580238  73.13428
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## 580   580 -76.59689 1.1992108  58.30566
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## 583   583 -76.56110 1.2461837  35.21521
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## 589   589 -76.57900 1.3132877  43.73564
## 590   590 -76.80268 1.1835532  83.84322
## 591   591 -76.48282 1.2909197  28.53158
## 592   592 -76.42690 1.0627659 130.70320
## 593   593 -76.77360 1.0359243  62.96985
## 594   594 -76.92570 0.8994793 104.63481
## 595   595 -76.81610 1.2886829  82.13258
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## 597   597 -76.87649 1.0225034  68.17951
## 598   598 -76.82952 1.4474959  89.85974
## 599   599 -76.80939 1.2842093  72.46776
## 600   600 -76.67965 0.9978986 139.46382
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## 602   602 -76.72215 0.9643466 129.24765
## 603   603 -76.61926 1.0046090 155.98058
## 604   604 -76.74452 1.0068458  55.90574
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## 606   606 -76.71097 1.2484205  81.99209
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## 611   611 -76.88097 1.0023722  80.90614
## 612   612 -76.41795 1.3222349  37.42446
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## 614   614 -76.82505 1.4206542  71.76573
## 615   615 -76.76242 1.1500012  91.42439
## 616   616 -76.78702 1.1500012  76.63188
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## 619   619 -76.87873 1.1052651 100.62801
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## 629   629 -76.50071 1.1678956  83.60531
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## 631   631 -76.80044 1.1947372  80.43123
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## 672   672 -76.57452 1.2640781  35.87701
## 673   673 -76.92347 0.9553994 105.29259
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## 785   785 -76.77136 1.0806603  75.04314
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## 787   787 -76.91899 1.1052651 108.35383
## 788   788 -76.84294 1.4027598  87.60229
## 789   789 -76.42690 0.9196105  37.11956
## 790   790 -76.59466 1.3378926  34.95251
## 791   791 -76.59242 1.1388172  61.42065
## 792   792 -76.60137 1.3311822  33.40133
## 793   793 -76.79149 1.0873707  85.50418
## 794   794 -76.50295 0.9643466 142.62334
## 795   795 -76.56334 1.2752621  27.41068
## 796   796 -76.91676 1.1880268  73.94924
## 797   797 -76.54321 1.0046090 129.18684
## 798   798 -76.82952 1.2640781  92.48818
## 799   799 -76.76465 1.4318383  54.95837
## 800   800 -76.90110 0.8994793  72.56303
## 801   801 -76.63492 1.0739499 134.43477
## 802   802 -76.72215 1.3289453  65.09478
## 803   803 -76.41795 1.2372365  64.26752
## 804   804 -76.65281 1.3289453  71.75179
## 805   805 -76.62150 0.8771113 110.59321
## 806   806 -76.56334 1.3535502  39.93213
## 807   807 -76.85412 1.4251278  64.88915
## 808   808 -76.41124 1.1500012 102.57430
## 809   809 -76.44926 1.1298700  91.93153
## 810   810 -76.62150 1.2685517  30.17308
## 811   811 -76.69307 1.1209227 134.09622
## 812   812 -76.44926 1.2931565  25.18632
## 813   813 -76.85636 1.1097387  83.70240
## 814   814 -76.60808 1.0582923 131.14020
## 815   815 -76.80268 1.2640781  68.10348
## 816   816 -76.64387 1.0627659 131.62984
## 817   817 -76.68860 1.1119755 134.94118
## 818   818 -76.65729 1.0359243 132.47467
## 819   819 -76.53650 1.4430223  36.21616
## 820   820 -76.62150 1.4072334  50.00240
## 821   821 -76.82728 0.9531626  85.05354
## 822   822 -76.86978 0.9889514  79.42289
## 823   823 -76.79597 1.1276331  61.89858
## 824   824 -76.68189 0.8838217 108.61244
## 825   825 -76.54992 1.1746060 141.09480
## 826   826 -76.52979 1.0784235  57.35431
## 827   827 -76.67742 1.2036844  84.84185
## 828   828 -76.66847 0.8704009 124.63813
## 829   829 -76.68860 1.1052651 136.91634
## 830   830 -76.43137 1.2774989  36.14117
## 831   831 -76.76689 0.9129001 148.72316
## 832   832 -76.79820 1.3021037  87.19728
## 833   833 -76.69531 0.9017161 109.92290
## 834   834 -76.63044 0.9822410 130.21530
## 835   835 -76.90110 1.3468398  79.63428
## 836   836 -76.52979 1.1097387 124.70055
## 837   837 -76.55439 1.2193420  39.77078
## 838   838 -76.76242 1.4027598  62.67677
## 839   839 -76.73781 1.0426347  70.95627
## 840   840 -76.65058 1.2976301  36.75211
## 841   841 -76.82057 1.2461837  76.18510
## 842   842 -76.63044 0.9889514 159.09738
## 843   843 -76.76465 1.1969740  73.18105
## 844   844 -76.77360 0.8838217 142.58900
## 845   845 -76.62373 1.2036844 127.46645
## 846   846 -76.44479 1.0403979  35.63892
## 847   847 -76.44032 0.9196105  31.58986
## 848   848 -76.45821 1.0650027 125.17062
## 849   849 -76.46045 1.4497327  47.60018
## 850   850 -76.59689 1.1432908  54.62925
## 851   851 -76.67965 1.4027598  46.81966
## 852   852 -76.72886 1.0985547  78.33990
## 853   853 -76.57900 1.4497327  38.14206
## 854   854 -76.64610 1.3602606  40.91259
## 855   855 -76.83847 1.2618413  90.50723
## 856   856 -76.89662 1.0627659  55.44022
## 857   857 -76.41347 1.4228910  56.46796
## 858   858 -76.84070 1.2730253  65.85321
## 859   859 -76.65058 1.3289453  72.55630
## 860   860 -76.73557 1.1253963 101.38586
## 861   861 -76.62821 1.1209227 139.50220
## 862   862 -76.46045 1.2372365  41.77721
## 863   863 -76.42913 1.3021037  31.83219
## 864   864 -76.54097 1.4631535  48.78714
## 865   865 -76.58347 1.0515819 132.15956
## 866   866 -76.58795 0.9352682 118.49847
## 867   867 -76.63044 1.3826286  39.17178
## 868   868 -76.59689 1.2394733  41.40395
## 869   869 -76.42466 0.9777674  73.29766
## 870   870 -76.85860 1.1097387  81.98550
## 871   871 -76.74228 0.9084265 133.81042
## 872   872 -76.78926 0.9553994  71.18896
## 873   873 -76.64834 0.9039529 124.15213
## 874   874 -76.90557 1.2171052  85.09421
## 875   875 -76.79597 1.1768428  70.71928
## 876   876 -76.91452 1.2842093 117.90481
## 877   877 -76.82057 0.9106633  85.59914
## 878   878 -76.76689 1.4117070  63.55158
## 879   879 -76.53426 1.2707885  42.89328
## 880   880 -76.75347 1.1007915  82.41901
## 881   881 -76.55887 1.1746060 153.01419
## 882   882 -76.56781 1.0471083 126.76463
## 883   883 -76.67742 1.1388172 150.30075
## 884   884 -76.57900 1.1723692  66.21441
## 885   885 -76.66847 0.9173737 114.46560
## 886   886 -76.89439 1.2797357 100.26678
## 887   887 -76.51637 1.0851339  54.58088
## 888   888 -76.57005 1.4296015  44.04178
## 889   889 -76.71768 1.2886829  64.65400
## 890   890 -76.63044 1.4363119  39.34457
## 891   891 -76.68413 1.1567116 143.54059
## 892   892 -76.82952 1.3021037  99.46084
## 893   893 -76.69755 1.2528941  61.63726
## 894   894 -76.48505 0.9419786 133.71259
## 895   895 -76.56334 1.0269770 140.16907
## 896   896 -76.47834 1.0761867 148.58322
## 897   897 -76.77136 1.0336875  57.35328
## 898   898 -76.52755 1.0515819 132.11136
## 899   899 -76.48282 1.2730253  32.70020
## 900   900 -76.50071 1.2059212  66.44604
## 901   901 -76.60360 1.1902636  51.40476
## 902   902 -76.48953 1.1969740  68.38122
## 903   903 -76.41347 0.8726377  29.36683
## 904   904 -76.62150 1.2484205  31.34851
## 905   905 -76.78478 1.1231595  89.84430
## 906   906 -76.70873 1.2596045  65.39331
## 907   907 -76.54768 0.9889514 123.92134
## 908   908 -76.58123 1.4318383  41.57658
## 909   909 -76.86531 1.2774989  77.86810
## 910   910 -76.86755 1.1723692 108.81525
## 911   911 -76.65505 1.2640781  50.93987
## 912   912 -76.49624 1.2014476  57.80272
## 913   913 -76.66623 0.9867146 133.48756
## 914   914 -76.67742 1.4407855  42.79990
## 915   915 -76.85636 1.1880268  85.93823
## 916   916 -76.89215 1.0918443  86.71979
## 917   917 -76.65281 0.9844778 129.33421
## 918   918 -76.90333 1.1500012 108.42400
## 919   919 -76.61926 1.1969740 134.88004
## 920   920 -76.44703 1.3915758  64.26398
## 921   921 -76.65952 1.3334190  68.55225
## 922   922 -76.52979 1.1678956  56.02416
## 923   923 -76.53874 0.8950057 116.42846
## 924   924 -76.78255 0.9531626  81.77039
## 925   925 -76.54545 1.4676271  58.91063
## 926   926 -76.82057 1.0582923  72.54884
## 927   927 -76.58571 1.0448715 129.57651
## 928   928 -76.47163 1.2998669  24.87051
## 929   929 -76.50742 1.1298700  51.63507
## 930   930 -76.86083 1.1298700  89.08278
## 931   931 -76.42466 1.3513134  43.84252
## 932   932 -76.65729 1.2372365  32.57055
## 933   933 -76.45374 1.2596045  45.29858
## 934   934 -76.48282 1.2193420  61.57263
## 935   935 -76.48729 1.1947372  60.67779
## 936   936 -76.41347 1.0090826  51.73962
## 937   937 -76.81163 1.2439469  69.33607
## 938   938 -76.72886 1.3088141  74.00818
## 939   939 -76.71544 0.9307946 128.45300
## 940   940 -76.82057 1.2819725  70.62541
## 941   941 -76.41347 1.1835532 101.90462
## 942   942 -76.58795 1.1880268  76.71621
## 943   943 -76.57452 1.1611852  77.58023
## 944   944 -76.51189 1.1030283 132.35876
## 945   945 -76.64834 1.3289453  70.23203
## 946   946 -76.90557 1.2663149 102.20082
## 947   947 -76.50071 1.1567116 100.64962
## 948   948 -76.61255 1.0918443 130.72661
## 949   949 -76.62597 1.1432908 125.48531
## 950   950 -76.51189 0.8704009  45.55083
## 951   951 -76.49400 1.3759182  45.22483
## 952   952 -76.47834 1.3222349  28.81414
## 953   953 -76.66847 0.8994793 117.51498
## 954   954 -76.77136 1.2126316  50.51487
## 955   955 -76.61255 1.2349997  29.28586
## 956   956 -76.59466 1.0873707  65.77286
## 957   957 -76.74899 1.3311822  72.08636
## 958   958 -76.89439 1.3535502 101.90759
## 959   959 -76.67294 1.1656588 141.58766
## 960   960 -76.68860 1.2439469  48.14298
## 961   961 -76.63044 1.2394733  36.16346
## 962   962 -76.69084 1.2551309  71.43262
## 963   963 -76.64610 1.3423662  53.22995
## 964   964 -76.60584 1.3513134  36.96296
## 965   965 -76.83399 1.4161806  92.16048
## 966   966 -76.85860 1.0761867  72.06029
## 967   967 -76.77584 1.1656588 111.21389
## 968   968 -76.68860 1.4049966  54.29757
## 969   969 -76.51860 1.2976301  43.72836
## 970   970 -76.61479 1.2394733  29.54846
## 971   971 -76.49624 1.0761867 121.95513
## 972   972 -76.44255 0.8972425  28.00332
## 973   973 -76.84965 0.8793481  44.61273
## 974   974 -76.71321 1.1634220  62.92276
## 975   975 -76.59689 0.9196105 125.69785
## 976   976 -76.53426 0.8972425 117.16048
## 977   977 -76.51189 1.3759182  33.33954
## 978   978 -76.91676 1.4676271  84.99355
## 979   979 -76.41571 1.0896075 115.99820
## 980   980 -76.78702 0.9464522  69.89173
## 981   981 -76.49176 1.0314507  43.19803
## 982   982 -76.84965 0.9598730  99.49770
## 983   983 -76.64387 1.4228910  39.72286
## 984   984 -76.68189 1.1589484  93.90477
## 985   985 -76.50295 1.3871022  36.85406
## 986   986 -76.62150 1.1075019 134.80765
## 987   987 -76.78031 0.8905321 133.49742
## 988   988 -76.41571 1.3647342  60.12369
## 989   989 -76.58571 1.1835532  78.27805
## 990   990 -76.48058 1.2998669  29.42807
## 991   991 -76.89439 0.8704009  46.00479
## 992   992 -76.87426 1.0135562  68.73071
## 993   993 -76.82281 1.3177613  92.69505
## 994   994 -76.42018 0.9509258  51.48805
## 995   995 -76.65729 1.1723692 151.31924
## 996   996 -76.91452 1.2886829 118.71986
## 997   997 -76.82952 0.9039529  84.67242
## 998   998 -76.59242 1.2461837  33.37549
## 999   999 -76.90557 1.3960494  91.42811
## 1000 1000 -76.86531 1.1432908  62.95665
## 1001 1001 -76.53650 0.9978986 120.29173
## 1002 1002 -76.61255 1.2148684  37.55804
## 1003 1003 -76.91452 0.8972425  68.06784
## 1004 1004 -76.71992 0.9285578 127.44361
## 1005 1005 -76.82505 1.2461837  76.60088
## 1006 1006 -76.86978 1.2193420  84.66582
## 1007 1007 -76.59689 1.4027598  37.13385
## 1008 1008 -76.46045 1.0381611  66.69118
## 1009 1009 -76.53203 1.0896075 138.36926
## 1010 1010 -76.67742 1.0650027 141.81163
## 1011 1011 -76.60808 1.3915758  44.77366
## 1012 1012 -76.58347 0.9218473 126.84025
## 1013 1013 -76.85412 1.0873707  70.09533
## 1014 1014 -76.76689 1.2103948  55.72479
## 1015 1015 -76.82728 1.2484205  68.20142
## 1016 1016 -76.41795 1.2685517  53.75952
## 1017 1017 -76.53426 1.0560555 137.65620
## 1018 1018 -76.49400 1.1052651  90.60418
## 1019 1019 -76.62821 0.9598730 119.77757
## 1020 1020 -76.69307 0.9665834 138.33871
## 1021 1021 -76.62821 0.9218473 119.38457
## 1022 1022 -76.53650 1.4363119  42.92700
## 1023 1023 -76.73110 1.3110509  77.94434
## 1024 1024 -76.58123 0.9061897 128.35039
## 1025 1025 -76.62373 1.0068458 140.86409
## 1026 1026 -76.53874 0.9151369 128.24356
## 1027 1027 -76.53426 1.1075019 127.93124
## 1028 1028 -76.80268 1.2305261  67.81516
## 1029 1029 -76.69531 1.2193420  32.82646
## 1030 1030 -76.61031 0.9688202 129.03020
## 1031 1031 -76.61926 1.2305261  37.17582
## 1032 1032 -76.42690 1.4497327  39.41263
## 1033 1033 -76.80939 1.1276331  94.75424
## 1034 1034 -76.45150 1.3446030  45.17820
## 1035 1035 -76.69307 0.9688202 130.14931
## 1036 1036 -76.66176 1.1611852 144.05467
## 1037 1037 -76.89886 0.9263209  95.95087
## 1038 1038 -76.57676 1.3110509  41.27836
## 1039 1039 -76.77360 1.3088141  79.65295
## 1040 1040 -76.45150 1.2730253  30.39765
## 1041 1041 -76.80491 1.1611852 112.14440
## 1042 1042 -76.90110 1.1164491  75.64946
## 1043 1043 -76.50742 1.3624974  33.14463
## 1044 1044 -76.65729 1.0314507 141.06140
## 1045 1045 -76.44479 1.0180298  30.48322
## 1046 1046 -76.81386 1.0828971  88.76565
## 1047 1047 -76.65505 1.4005230  44.29130
## 1048 1048 -76.78926 1.3065773  92.42916
## 1049 1049 -76.90333 1.2215788  90.43617
## 1050 1050 -76.69979 1.4139438  48.07612
## 1051 1051 -76.82952 0.9375050  99.16493
## 1052 1052 -76.84741 1.2819725  68.52258
## 1053 1053 -76.69307 1.1321068 133.22263
## 1054 1054 -76.54992 1.0314507 144.99391
## 1055 1055 -76.61926 1.2752621  33.28681
## 1056 1056 -76.58571 1.2126316  51.07936
## 1057 1057 -76.73557 0.8793481 122.71274
## 1058 1058 -76.54097 1.2215788  40.90696
## 1059 1059 -76.47387 1.3535502  32.16675
## 1060 1060 -76.60137 1.4005230  32.85384
## 1061 1061 -76.42466 1.1678956  65.79308
## 1062 1062 -76.55216 1.3557870  38.38197
## 1063 1063 -76.60360 1.1589484  73.45311
## 1064 1064 -76.89215 1.3244717 102.39152
## 1065 1065 -76.45374 1.1142123  81.11978
## 1066 1066 -76.74676 1.2103948  54.73608
## 1067 1067 -76.60360 1.4363119  36.94604
## 1068 1068 -76.89439 0.9442154  70.36820
## 1069 1069 -76.71321 1.0157930  95.70343
## 1070 1070 -76.78255 1.3468398  81.93433
## 1071 1071 -76.89215 0.9151369  91.62822
## 1072 1072 -76.84741 1.4542063  67.82803
## 1073 1073 -76.63492 1.0694763 129.96996
## 1074 1074 -76.51189 1.1321068  59.98510
## 1075 1075 -76.91452 1.3580238  81.72684
## 1076 1076 -76.64163 0.9688202 128.07576
## 1077 1077 -76.56558 0.9934250 117.94981
## 1078 1078 -76.63939 1.1164491 123.08450
## 1079 1079 -76.62373 1.3446030  36.09195
## 1080 1080 -76.71097 0.9464522 137.47781
## 1081 1081 -76.51637 1.2171052  41.51431
## 1082 1082 -76.74228 1.1500012  69.60393
## 1083 1083 -76.68413 1.1432908 135.67133
## 1084 1084 -76.42466 1.3289453  31.59943
## 1085 1085 -76.55663 1.1544748 141.38812
## 1086 1086 -76.63939 1.2238156  37.73197
## 1087 1087 -76.77584 1.3647342  67.68294
## 1088 1088 -76.56334 1.2260524  28.60570
## 1089 1089 -76.66623 1.1701324 111.02724
## 1090 1090 -76.65952 1.3960494  36.93032
## 1091 1091 -76.67965 1.0068458 132.17838
## 1092 1092 -76.51189 1.2305261  65.06697
## 1093 1093 -76.73557 1.3334190  79.67004
## 1094 1094 -76.76242 1.1164491  71.94215
## 1095 1095 -76.45374 1.1298700  98.28829
## 1096 1096 -76.89662 0.9755306  87.89841
## 1097 1097 -76.86307 1.1052651  90.84083
## 1098 1098 -76.56110 0.8771113 115.30981
## 1099 1099 -76.77807 1.0381611  67.98309
## 1100 1100 -76.61702 1.0023722 152.27942
## 1101 1101 -76.91676 1.2103948 102.97068
## 1102 1102 -76.44926 1.3915758  62.31953
## 1103 1103 -76.71097 0.8994793 121.44570
## 1104 1104 -76.79373 1.0113194  49.03438
## 1105 1105 -76.55663 1.3334190  37.30032
## 1106 1106 -76.83399 0.9643466  99.44847
## 1107 1107 -76.92570 0.9330314  85.92934
## 1108 1108 -76.58347 1.3535502  34.42430
## 1109 1109 -76.70202 1.3535502  66.15658
## 1110 1110 -76.87202 1.1902636  83.81255
## 1111 1111 -76.60360 1.4586799  33.09357
## 1112 1112 -76.42466 0.9665834  40.73548
## 1113 1113 -76.55439 1.2730253  28.72957
## 1114 1114 -76.41571 0.9106633  40.35115
## 1115 1115 -76.44479 1.1119755  57.74964
## 1116 1116 -76.80491 1.4228910  69.35205
## 1117 1117 -76.87873 1.1298700  93.96245
## 1118 1118 -76.82728 1.0359243  65.34785
## 1119 1119 -76.64610 1.2909197  50.97560
## 1120 1120 -76.84294 1.4296015  80.65946
## 1121 1121 -76.49624 0.9151369 105.94328
## 1122 1122 -76.80044 1.3267085  75.53278
## 1123 1123 -76.69084 1.3155245  67.31898
## 1124 1124 -76.53426 1.1455276 140.49045
## 1125 1125 -76.76018 1.2596045  86.09882
## 1126 1126 -76.70650 1.0292139 150.40335
## 1127 1127 -76.54321 0.9509258 130.01067
## 1128 1128 -76.44479 1.3781550  47.34037
## 1129 1129 -76.58571 1.1343436  61.52792
## 1130 1130 -76.78478 0.9084265 130.84375
## 1131 1131 -76.78478 0.9263209 154.94786
## 1132 1132 -76.43808 0.9464522  32.31495
## 1133 1133 -76.89886 0.8860585  59.56154
## 1134 1134 -76.62150 1.3021037  31.96214
## 1135 1135 -76.44703 0.9375050  38.97902
## 1136 1136 -76.83847 1.0784235  88.61838
## 1137 1137 -76.71321 1.3893390  75.34622
## 1138 1138 -76.86978 1.3065773  70.85699
## 1139 1139 -76.79373 1.0515819 100.44144
## 1140 1140 -76.54545 1.4139438  32.24257
## 1141 1141 -76.75794 0.9397418  83.93510
## 1142 1142 -76.83623 0.9509258  87.42815
## 1143 1143 -76.53650 1.0157930 135.75768
## 1144 1144 -76.79149 0.9464522  67.26097
## 1145 1145 -76.55887 1.1298700 127.96172
## 1146 1146 -76.44032 1.3446030  58.61270
## 1147 1147 -76.69084 1.1634220  58.84122
## 1148 1148 -76.69979 1.2349997  32.86897
## 1149 1149 -76.52755 1.3803918  29.69743
## 1150 1150 -76.82952 1.3088141  97.87846
## 1151 1151 -76.74452 1.3468398  73.92198
## 1152 1152 -76.45374 1.0269770  50.01866
## 1153 1153 -76.47387 1.2327629  56.44406
## 1154 1154 -76.81834 1.3535502  70.35207
## 1155 1155 -76.69307 1.2126316  37.15845
## 1156 1156 -76.50742 1.3848654  47.11224
## 1157 1157 -76.54992 0.9330314 137.73914
## 1158 1158 -76.75794 1.4340751  56.10378
## 1159 1159 -76.44255 1.3356558  41.83453
## 1160 1160 -76.61255 1.1790796 105.40440
## 1161 1161 -76.53426 1.3401294  36.15450
## 1162 1162 -76.82281 1.2349997  68.23306
## 1163 1163 -76.77584 1.3781550  83.34606
## 1164 1164 -76.84294 0.8726377  40.21047
## 1165 1165 -76.63715 1.3334190  53.90693
## 1166 1166 -76.84518 1.1119755  85.63746
## 1167 1167 -76.86755 1.0023722  72.99843
## 1168 1168 -76.60137 1.0090826 137.49440
## 1169 1169 -76.78255 1.1500012  87.52099
## 1170 1170 -76.48058 1.2282892  48.62525
## 1171 1171 -76.82281 1.2059212  73.49409
## 1172 1172 -76.42466 1.4609167  61.26699
## 1173 1173 -76.49847 1.0426347 127.03987
## 1174 1174 -76.67071 1.3848654  57.23053
## 1175 1175 -76.72439 0.8748745 121.78244
## 1176 1176 -76.61926 1.2551309  31.46600
## 1177 1177 -76.70873 1.0157930 152.65050
## 1178 1178 -76.61479 1.3938126  40.09395
## 1179 1179 -76.81386 1.0605291  89.95909
## 1180 1180 -76.43361 1.1365804 104.93459
## 1181 1181 -76.92123 1.3378926  70.08293
## 1182 1182 -76.43361 1.1701324  58.59312
## 1183 1183 -76.58123 0.8994793 126.80337
## 1184 1184 -76.41571 1.0068458  49.28196
## 1185 1185 -76.88991 1.1455276  95.70890
## 1186 1186 -76.60137 0.9173737 131.84726
## 1187 1187 -76.80939 1.3356558  78.37842
## 1188 1188 -76.54768 1.4184174  38.84216
## 1189 1189 -76.67294 1.3759182  67.51329
## 1190 1190 -76.86978 0.9978986  68.84424
## 1191 1191 -76.47387 1.2976301  25.21664
## 1192 1192 -76.50518 0.9732938 143.45438
## 1193 1193 -76.80715 1.0247402  44.24488
## 1194 1194 -76.41571 1.1030283 132.08281
## 1195 1195 -76.90333 1.3938126 102.72036
## 1196 1196 -76.82952 1.0180298  63.10126
## 1197 1197 -76.88320 1.3960494 102.40497
## 1198 1198 -76.65505 0.9844778 127.64633
## 1199 1199 -76.78926 1.0650027  94.28829
## 1200 1200 -76.50742 1.4094702  37.26239
## 1201 1201 -76.71992 1.3267085  73.46068
## 1202 1202 -76.47387 0.9956618  48.50016
## 1203 1203 -76.48058 0.9106633 115.92080
## 1204 1204 -76.79373 1.4251278  68.43034
## 1205 1205 -76.75571 1.4609167  60.47373
## 1206 1206 -76.77136 1.1992108  84.05131
## 1207 1207 -76.50742 0.8860585 113.20871
## 1208 1208 -76.59018 1.2551309  29.26161
## 1209 1209 -76.74676 1.2909197  77.60807
## 1210 1210 -76.56558 1.0851339 121.12138
## 1211 1211 -76.58795 1.3602606  38.30079
## 1212 1212 -76.92123 1.1209227  67.84084
## 1213 1213 -76.68189 1.2238156  30.30435
## 1214 1214 -76.66176 0.9240841 119.57121
## 1215 1215 -76.91004 1.0627659  61.47232
## 1216 1216 -76.44479 1.0650027 138.03241
## 1217 1217 -76.61479 1.1678956 134.95723
## 1218 1218 -76.79373 1.0426347  95.04635
## 1219 1219 -76.60584 0.9106633 121.43761
## 1220 1220 -76.69979 1.0806603 138.58012
## 1221 1221 -76.92570 0.9598730  89.52057
## 1222 1222 -76.74452 1.2931565  76.56078
## 1223 1223 -76.85412 1.4609167  88.05623
## 1224 1224 -76.41795 1.4296015  40.48922
## 1225 1225 -76.50966 1.3915758  39.05966
## 1226 1226 -76.92347 0.9777674 102.31692
## 1227 1227 -76.66623 0.9442154 129.22467
## 1228 1228 -76.76018 1.4653903  62.57698
## 1229 1229 -76.72215 0.9509258 133.30873
## 1230 1230 -76.77360 1.1656588 103.89332
## 1231 1231 -76.65058 0.9688202 135.51996
## 1232 1232 -76.66400 1.1656588 142.66833
## 1233 1233 -76.65281 1.1947372 125.62579
## 1234 1234 -76.91676 1.1142123  79.15366
## 1235 1235 -76.56781 1.1790796  67.36290
## 1236 1236 -76.45150 1.3222349  28.02124
## 1237 1237 -76.91228 1.4206542 103.46423
## 1238 1238 -76.64387 1.3624974  40.74518
## 1239 1239 -76.79597 0.9889514  77.52630
## 1240 1240 -76.54097 1.1164491 133.17514
## 1241 1241 -76.59913 1.1522380  55.15945
## 1242 1242 -76.87873 0.9755306  83.35039
## 1243 1243 -76.88544 1.3222349  88.48276
## 1244 1244 -76.65952 0.9509258 125.54653
## 1245 1245 -76.92347 1.0359243  78.13136
## 1246 1246 -76.44703 1.3043405  27.49151
## 1247 1247 -76.62150 1.2059212 100.17599
## 1248 1248 -76.60137 1.3513134  42.86178
## 1249 1249 -76.91452 1.0560555  73.96940
## 1250 1250 -76.92123 1.4117070  90.64780
## 1251 1251 -76.54545 1.0247402 139.94771
## 1252 1252 -76.81163 1.1969740  77.96394
## 1253 1253 -76.44703 1.2931565  24.16400
## 1254 1254 -76.55887 1.0851339 130.95685
## 1255 1255 -76.74899 1.2394733  67.38319
## 1256 1256 -76.61255 1.1992108 110.17887
## 1257 1257 -76.65952 1.0336875 132.16205
## 1258 1258 -76.89662 1.2528941  96.42560
## 1259 1259 -76.54545 0.9352682 120.20006
## 1260 1260 -76.53203 1.3736814  28.07079
## 1261 1261 -76.55663 1.2215788  38.26816
## 1262 1262 -76.47163 1.4318383  41.11215
## 1263 1263 -76.47610 1.4049966  39.33888
## 1264 1264 -76.73334 1.4542063  47.15495
## 1265 1265 -76.85636 1.1701324  87.03527
## 1266 1266 -76.59466 0.9553994 146.71046
## 1267 1267 -76.79149 1.3446030  72.76142
## 1268 1268 -76.41124 1.4430223  40.98539
## 1269 1269 -76.48729 1.2193420  69.44557
## 1270 1270 -76.83176 0.9129001  91.73047
## 1271 1271 -76.61702 1.2707885  33.88637
## 1272 1272 -76.56334 1.0582923 134.29347
## 1273 1273 -76.62821 0.8726377 115.69908
## 1274 1274 -76.60137 0.9419786 133.04665
## 1275 1275 -76.76913 1.1746060  74.54585
## 1276 1276 -76.56558 1.3378926  37.78928
## 1277 1277 -76.56781 1.3244717  34.38442
## 1278 1278 -76.71321 1.2931565  61.58335
## 1279 1279 -76.52755 1.0627659  64.20431
## 1280 1280 -76.68413 0.9442154 155.28384
## 1281 1281 -76.78926 1.3624974  92.93215
## 1282 1282 -76.59018 1.1321068  53.48284
## 1283 1283 -76.64834 1.4296015  40.18890
## 1284 1284 -76.57229 1.0090826 127.91829
## 1285 1285 -76.84294 1.2864461  75.20287
## 1286 1286 -76.87202 1.2394733 101.73762
## 1287 1287 -76.66176 1.1925004 118.45377
## 1288 1288 -76.46045 1.2640781  45.95341
## 1289 1289 -76.71321 0.9665834 133.28702
## 1290 1290 -76.50518 0.8927689 111.74332
## 1291 1291 -76.48282 1.1947372  62.49507
## 1292 1292 -76.87649 0.9442154  78.65813
## 1293 1293 -76.76465 1.3155245  67.82993
## 1294 1294 -76.46716 1.2528941  39.90511
## 1295 1295 -76.78031 1.2864461  72.48251
## 1296 1296 -76.59913 1.3938126  47.77230
## 1297 1297 -76.84518 1.2103948  74.34487
## 1298 1298 -76.43808 1.1186859 144.01184
## 1299 1299 -76.66176 0.9867146 133.64209
## 1300 1300 -76.50518 1.4407855  53.30082
## 1301 1301 -76.84294 1.1343436  77.93605
## 1302 1302 -76.58347 1.1969740  73.31390
## 1303 1303 -76.84965 1.3311822 100.76994
## 1304 1304 -76.53426 1.1880268 134.28278
## 1305 1305 -76.42690 1.3982862  54.14151
## 1306 1306 -76.84070 1.0157930  63.62624
## 1307 1307 -76.64610 1.2618413  42.12357
## 1308 1308 -76.92123 1.3222349  72.44604
## 1309 1309 -76.75794 1.0538187  77.57584
## 1310 1310 -76.89215 1.3088141  68.42834
## 1311 1311 -76.80268 1.1947372  79.91561
## 1312 1312 -76.78478 1.2238156  55.01699
## 1313 1313 -76.63939 1.2305261  36.35605
## 1314 1314 -76.85412 1.3960494  73.15405
## 1315 1315 -76.42690 1.2953933  31.36292
## 1316 1316 -76.72886 0.9732938 151.58063
## 1317 1317 -76.82057 0.9039529  57.22493
## 1318 1318 -76.55887 1.2349997  36.50025
## 1319 1319 -76.67518 1.0001354 154.21440
## 1320 1320 -76.60584 1.0202666 117.69327
## 1321 1321 -76.83623 1.3982862  82.47913
## 1322 1322 -76.56334 1.4184174  38.66305
## 1323 1323 -76.75571 0.9017161 138.26920
## 1324 1324 -76.74005 1.2596045  87.91495
## 1325 1325 -76.92347 1.1209227  75.09298
## 1326 1326 -76.74899 1.1365804  96.88890
## 1327 1327 -76.89439 1.2081580  74.87420
## 1328 1328 -76.56334 1.4139438  37.61396
## 1329 1329 -76.88544 1.1007915  66.94151
## 1330 1330 -76.58123 1.4161806  35.32905
## 1331 1331 -76.48505 0.9352682 135.70709
## 1332 1332 -76.46716 1.4542063  39.85189
## 1333 1333 -76.66623 1.4139438  63.33560
## 1334 1334 -76.44703 1.1253963  80.68761
## 1335 1335 -76.57452 1.0582923 139.06303
## 1336 1336 -76.61479 1.3781550  34.96782
## 1337 1337 -76.73110 1.1544748  91.22838
## 1338 1338 -76.65729 1.1388172 142.95236
## 1339 1339 -76.90110 0.9442154  73.28722
## 1340 1340 -76.88768 1.0940811  92.35755
## 1341 1341 -76.68413 1.3938126  55.29843
## 1342 1342 -76.71768 1.0157930  82.86521
## 1343 1343 -76.63939 1.3110509  41.49083
## 1344 1344 -76.77136 1.4676271  79.36624
## 1345 1345 -76.61031 1.0068458 154.57567
## 1346 1346 -76.70650 1.2126316  43.65687
## 1347 1347 -76.48282 0.9911882 140.35376
## 1348 1348 -76.65281 0.9196105 124.12588
## 1349 1349 -76.81610 1.4318383  64.38400
## 1350 1350 -76.70873 1.3826286  74.47491
## 1351 1351 -76.86531 1.2484205  78.37751
## 1352 1352 -76.57229 1.2774989  27.66374
## 1353 1353 -76.46268 1.4251278  50.59202
## 1354 1354 -76.87202 1.2014476  72.95644
## 1355 1355 -76.89662 0.9956618  94.23724
## 1356 1356 -76.89662 1.4586799 103.46822
## 1357 1357 -76.71768 1.2842093  70.09167
## 1358 1358 -76.71097 1.1231595 120.66031
## 1359 1359 -76.90557 1.0023722  72.32700
## 1360 1360 -76.70426 1.4072334  61.74836
## 1361 1361 -76.54768 1.0582923 124.16872
## 1362 1362 -76.59018 1.0068458 139.36139
## 1363 1363 -76.45597 1.1902636  64.97015
## 1364 1364 -76.61255 1.0493451 133.28661
## 1365 1365 -76.67965 0.9643466 133.65021
## 1366 1366 -76.66847 1.3177613  58.60682
## 1367 1367 -76.85636 0.9889514  85.00977
## 1368 1368 -76.79149 0.9553994  70.65414
## 1369 1369 -76.75347 1.0471083  79.83747
## 1370 1370 -76.65952 0.9285578 116.82091
## 1371 1371 -76.66176 1.0985547 174.00331
## 1372 1372 -76.51637 1.2909197  29.25436
## 1373 1373 -76.54768 0.9978986 125.29210
## 1374 1374 -76.83847 0.8860585  51.45323
## 1375 1375 -76.79820 0.9956618  69.13733
## 1376 1376 -76.65952 1.3311822  68.12329
## 1377 1377 -76.44032 1.0828971 131.10017
## 1378 1378 -76.60137 1.1164491  45.70087
## 1379 1379 -76.43137 0.9956618  52.08791
## 1380 1380 -76.80491 1.0918443  77.23622
## 1381 1381 -76.72439 1.0493451  62.48583
## 1382 1382 -76.82281 1.2148684  66.44797
## 1383 1383 -76.74452 1.1432908  82.79745
## 1384 1384 -76.47610 0.8838217  60.08617
## 1385 1385 -76.76465 1.0403979  53.58718
## 1386 1386 -76.78702 1.4072334  57.07167
## 1387 1387 -76.81610 1.3356558  75.93457
## 1388 1388 -76.86307 1.1880268  85.05252
## 1389 1389 -76.51413 0.8972425 111.61953
## 1390 1390 -76.82952 1.0336875  64.73221
## 1391 1391 -76.78926 1.0471083  86.47709
## 1392 1392 -76.48058 1.2193420  65.69434
## 1393 1393 -76.84070 1.2484205  73.28719
## 1394 1394 -76.58795 1.0806603  49.57490
## 1395 1395 -76.82952 1.2596045  91.46711
## 1396 1396 -76.78255 1.3602606  85.30996
## 1397 1397 -76.88097 1.0090826  73.52106
## 1398 1398 -76.41347 0.9173737  40.31686
## 1399 1399 -76.88768 1.4564431  91.61095
## 1400 1400 -76.62150 0.9576362 117.92625
## 1401 1401 -76.92570 0.9017161 106.47565
## 1402 1402 -76.58795 0.8905321 114.65177
## 1403 1403 -76.88768 1.4251278  66.59164
## 1404 1404 -76.80044 1.3535502  64.21207
## 1405 1405 -76.74899 1.4542063  59.84396
## 1406 1406 -76.55216 1.0851339 138.20161
## 1407 1407 -76.46268 1.0269770 118.31776
## 1408 1408 -76.68636 1.4296015  42.89641
## 1409 1409 -76.52979 1.2103948  39.84035
## 1410 1410 -76.55887 1.0381611 142.18750
## 1411 1411 -76.42018 1.2484205  68.44836
## 1412 1412 -76.58123 1.2730253  28.63771
## 1413 1413 -76.42690 0.9129001  40.35734
## 1414 1414 -76.84965 1.0202666  69.87063
## 1415 1415 -76.76913 1.3781550  80.04268
## 1416 1416 -76.73110 0.9956618  90.28609
## 1417 1417 -76.64834 1.1343436 128.39302
## 1418 1418 -76.46492 1.1432908  93.90504
## 1419 1419 -76.84741 1.1522380  72.07577
## 1420 1420 -76.72663 0.9978986 150.92897
## 1421 1421 -76.68413 0.9419786 142.74594
## 1422 1422 -76.71321 1.3714446  74.91913
## 1423 1423 -76.61479 0.9263209 111.62005
## 1424 1424 -76.54768 1.2126316  93.24981
## 1425 1425 -76.77136 1.2215788  51.97394
## 1426 1426 -76.79597 1.4184174  67.36264
## 1427 1427 -76.49176 1.4027598  40.75482
## 1428 1428 -76.63492 0.9084265 119.90217
## 1429 1429 -76.65729 0.9486890 115.11956
## 1430 1430 -76.52979 0.9375050 123.15726
## 1431 1431 -76.54545 0.9307946 129.34711
## 1432 1432 -76.92123 1.2730253  86.83543
## 1433 1433 -76.87202 0.9419786  87.68242
## 1434 1434 -76.80715 1.3490766  71.23608
## 1435 1435 -76.52979 1.4117070  34.96621
## 1436 1436 -76.83847 1.0672395  77.46306
## 1437 1437 -76.41124 1.1880268  88.47583
## 1438 1438 -76.84518 1.4251278  74.57710
## 1439 1439 -76.88991 0.9531626  87.90377
## 1440 1440 -76.78478 1.2797357  70.59871
## 1441 1441 -76.85860 1.0515819  66.37684
## 1442 1442 -76.72663 1.4049966  60.86320
## 1443 1443 -76.70650 0.9844778 138.94873
## 1444 1444 -76.41347 1.2461837  66.85683
## 1445 1445 -76.64834 1.1611852 148.68314
## 1446 1446 -76.69755 1.0560555 135.69614
## 1447 1447 -76.63715 1.4049966  32.94607
## 1448 1448 -76.91228 0.9330314  70.85690
## 1449 1449 -76.48058 0.9486890 119.48382
## 1450 1450 -76.91899 1.1119755 100.91134
## 1451 1451 -76.43137 1.0336875  36.11175
## 1452 1452 -76.75794 1.2774989  85.37543
## 1453 1453 -76.46045 1.1992108  68.94915
## 1454 1454 -76.47610 1.4564431  52.42222
## 1455 1455 -76.52531 1.3513134  35.03564
## 1456 1456 -76.86978 0.9330314  90.70303
## 1457 1457 -76.61031 1.3826286  35.68980
## 1458 1458 -76.51637 1.0828971  57.44585
## 1459 1459 -76.65505 1.0426347 139.27942
## 1460 1460 -76.51860 0.9151369 123.58378
## 1461 1461 -76.88544 0.9084265  75.85014
## 1462 1462 -76.79373 1.1768428  69.02498
## 1463 1463 -76.57676 1.0180298 148.12752
## 1464 1464 -76.46492 0.8748745  59.39243
## 1465 1465 -76.65281 1.1902636 120.58392
## 1466 1466 -76.62821 1.2394733  34.87402
## 1467 1467 -76.76242 0.9129001 146.73909
## 1468 1468 -76.48505 1.2953933  35.65634
## 1469 1469 -76.47610 1.1768428  78.19493
## 1470 1470 -76.80715 0.9218473  93.35054
## 1471 1471 -76.43137 1.1231595 101.89294
## 1472 1472 -76.86978 0.9531626  95.10161
## 1473 1473 -76.73557 1.2103948  77.62731
## 1474 1474 -76.48729 0.9173737 121.66007
## 1475 1475 -76.62821 0.8704009 106.24129
## 1476 1476 -76.52755 1.0381611 147.34543
## 1477 1477 -76.65729 1.1857900 121.74063
## 1478 1478 -76.61702 1.2484205  32.00294
## 1479 1479 -76.58123 1.1656588  77.62702
## 1480 1480 -76.59466 0.9867146 141.12088
## 1481 1481 -76.54992 1.3982862  32.82276
## 1482 1482 -76.68860 1.3311822  67.17406
## 1483 1483 -76.68413 0.9240841 124.97130
## 1484 1484 -76.55439 1.4296015  37.99518
## 1485 1485 -76.85189 1.4318383  80.80052
## 1486 1486 -76.54097 1.0202666 141.59595
## 1487 1487 -76.90557 0.9397418  85.23501
## 1488 1488 -76.60360 1.4228910  34.52147
## 1489 1489 -76.54768 0.8748745 111.20123
## 1490 1490 -76.84965 1.2864461  72.90907
## 1491 1491 -76.48729 1.0426347 130.84364
## 1492 1492 -76.48058 0.9643466 138.66504
## 1493 1493 -76.44255 0.9934250  47.30877
## 1494 1494 -76.55887 1.3490766  35.79067
## 1495 1495 -76.57452 0.9867146 133.88416
## 1496 1496 -76.61926 1.1455276 126.49908
## 1497 1497 -76.47163 1.2394733  45.11207
## 1498 1498 -76.83399 1.2618413  94.08865
## 1499 1499 -76.76018 1.0202666  48.56204
## 1500 1500 -76.74676 1.3043405  74.19858
## 1501 1501 -76.52755 1.1253963  69.75881
## 1502 1502 -76.91004 1.3155245  84.99859
## 1503 1503 -76.55887 1.3065773  37.43796
## 1504 1504 -76.50742 1.4072334  37.71357
## 1505 1505 -76.79149 1.3803918  73.82473
## 1506 1506 -76.74899 1.2998669  79.45279
## 1507 1507 -76.79820 0.9464522  65.61333
## 1508 1508 -76.71544 0.9352682 140.91052
## 1509 1509 -76.77807 1.4296015  59.98917
## 1510 1510 -76.70650 1.3871022  68.04942
## 1511 1511 -76.51413 1.2976301  49.02435
## 1512 1512 -76.55663 0.8838217 113.33447
## 1513 1513 -76.52531 0.9956618 130.06311
## 1514 1514 -76.42690 0.9867146  43.04955
## 1515 1515 -76.50742 1.1142123  86.22203
## 1516 1516 -76.86978 1.2014476  80.11324
## 1517 1517 -76.53650 1.0426347 142.66695
## 1518 1518 -76.81386 1.2931565  85.50196
## 1519 1519 -76.68413 1.4184174  39.26434
## 1520 1520 -76.85860 0.9777674  93.73418
## 1521 1521 -76.46045 0.9263209 122.11048
## 1522 1522 -76.67965 1.0269770 150.76001
## 1523 1523 -76.47610 1.2931565  28.04796
## 1524 1524 -76.84741 1.1343436  60.33120
## 1525 1525 -76.64834 1.3602606  37.50510
## 1526 1526 -76.71321 0.9889514 143.77766
## 1527 1527 -76.53426 1.2484205  53.87725
## 1528 1528 -76.41347 1.3692078  61.09276
## 1529 1529 -76.54992 1.2215788  40.77955
## 1530 1530 -76.66847 1.1701324  65.54572
## 1531 1531 -76.42690 1.2506573  48.49110
## 1532 1532 -76.44926 1.2059212  60.77202
## 1533 1533 -76.72886 1.0471083  64.22032
## 1534 1534 -76.61926 1.1902636 137.14145
## 1535 1535 -76.54321 1.0314507 141.67690
## 1536 1536 -76.45150 0.9710570  41.07781
## 1537 1537 -76.50071 1.0627659 133.20143
## 1538 1538 -76.88320 0.9598730 114.40023
## 1539 1539 -76.42466 0.9509258  51.44579
## 1540 1540 -76.78255 0.9442154  83.03307
## 1541 1541 -76.47163 1.2484205  40.79793
## 1542 1542 -76.70426 1.2730253  79.54344
## 1543 1543 -76.65058 1.2819725  52.06230
## 1544 1544 -76.78255 1.1097387  88.01272
## 1545 1545 -76.50071 1.0426347 128.17500
## 1546 1546 -76.58123 1.0940811 140.89355
## 1547 1547 -76.60584 1.0605291 135.27769
## 1548 1548 -76.64834 1.0135562 144.08852
## 1549 1549 -76.50071 1.0023722 130.02171
## 1550 1550 -76.78255 1.2596045  65.44777
## 1551 1551 -76.90557 1.0090826  63.25220
## 1552 1552 -76.75123 1.3624974  84.14538
## 1553 1553 -76.67965 0.9934250 129.98898
## 1554 1554 -76.55439 1.2640781  30.66419
## 1555 1555 -76.65281 1.1298700 135.93785
## 1556 1556 -76.75347 1.0694763  78.93122
## 1557 1557 -76.69307 1.1992108  41.30115
## 1558 1558 -76.84070 1.2327629  87.82966
## 1559 1559 -76.81163 1.1343436 102.97775
## 1560 1560 -76.61479 1.3199981  33.44456
## 1561 1561 -76.83847 1.2439469  75.41386
## 1562 1562 -76.59466 1.2752621  36.52736
## 1563 1563 -76.81163 0.9464522  68.54468
## 1564 1564 -76.80268 1.2193420  46.41697
## 1565 1565 -76.45374 1.4273646  37.01401
## 1566 1566 -76.71097 1.3938126  65.48846
## 1567 1567 -76.90333 0.9934250  83.75365
## 1568 1568 -76.44032 1.1611852  55.16305
## 1569 1569 -76.89439 1.3043405  61.24369
## 1570 1570 -76.64610 1.0806603 119.97923
## 1571 1571 -76.53203 1.1969740  56.34771
## 1572 1572 -76.59018 1.2998669  30.02600
## 1573 1573 -76.62597 0.8771113 118.11425
## 1574 1574 -76.89215 1.2797357  97.00163
## 1575 1575 -76.84965 0.8882953  73.31264
## 1576 1576 -76.54992 0.9598730 110.90695
## 1577 1577 -76.83847 0.9598730  91.06779
## 1578 1578 -76.41347 1.3826286  60.37022
## 1579 1579 -76.45597 1.3848654  52.68679
## 1580 1580 -76.41124 1.4609167  48.57663
## 1581 1581 -76.80268 1.2976301  81.17046
## 1582 1582 -76.58571 0.9330314 126.75186
## 1583 1583 -76.51189 1.2797357  38.69768
## 1584 1584 -76.68860 1.2238156  29.04212
## 1585 1585 -76.83847 1.4631535  86.15507
## 1586 1586 -76.46939 1.1075019  69.05814
## 1587 1587 -76.48058 1.2528941  37.13626
## 1588 1588 -76.83623 1.4407855  76.20209
## 1589 1589 -76.80715 1.3759182  69.59988
## 1590 1590 -76.91899 1.2215788  94.29546
## 1591 1591 -76.49624 1.4474959  48.04996
## 1592 1592 -76.69755 1.1746060  48.74837
## 1593 1593 -76.86978 1.0851339  90.53748
## 1594 1594 -76.44255 1.4049966  59.05029
## 1595 1595 -76.86978 1.3490766  91.94476
## 1596 1596 -76.81610 1.2439469  68.76572
## 1597 1597 -76.66847 1.3378926  61.09579
## 1598 1598 -76.62150 0.9240841 131.81836
## 1599 1599 -76.45374 0.9375050 121.61627
## 1600 1600 -76.75794 1.2573677  94.63564
## 1601 1601 -76.82728 1.4049966  81.23193
## 1602 1602 -76.41124 1.2953933  33.57775
## 1603 1603 -76.73557 0.9442154 158.13113
## 1604 1604 -76.76689 1.3490766  84.49815
## 1605 1605 -76.57452 0.8905321 108.73158
## 1606 1606 -76.62597 0.9196105 121.04533
## 1607 1607 -76.87873 0.9039529  56.40936
## 1608 1608 -76.57676 1.0963179 141.14478
## 1609 1609 -76.44032 0.9173737  32.29607
## 1610 1610 -76.58123 1.4676271  39.04349
## 1611 1611 -76.89439 1.1209227  82.86351
## 1612 1612 -76.80268 0.9934250  74.76480
## 1613 1613 -76.63044 1.3557870  35.31335
## 1614 1614 -76.51413 1.2238156  50.46502
## 1615 1615 -76.57005 0.9375050 117.63576
## 1616 1616 -76.84741 1.1253963  84.03160
## 1617 1617 -76.46268 1.2103948  73.28645
## 1618 1618 -76.78031 1.4542063  85.65130
## 1619 1619 -76.70202 1.2886829  72.90034
## 1620 1620 -76.48282 1.3132877  29.27989
## 1621 1621 -76.80939 1.2976301  99.28949
## 1622 1622 -76.61479 0.9375050 128.00528
## 1623 1623 -76.50966 1.3401294  26.98825
## 1624 1624 -76.61926 1.3624974  34.78131
## 1625 1625 -76.84070 0.9017161  67.45447
## 1626 1626 -76.81386 0.9800042  86.05566
## 1627 1627 -76.57676 1.0694763 137.83546
## 1628 1628 -76.59913 1.4474959  39.37453
## 1629 1629 -76.80939 1.3244717  66.23311
## 1630 1630 -76.74228 0.8838217 136.89949
## 1631 1631 -76.67742 1.1186859 147.85463
## 1632 1632 -76.60584 1.3423662  44.32383
## 1633 1633 -76.54545 1.3759182  37.78654
## 1634 1634 -76.62150 1.4161806  31.49751
## 1635 1635 -76.62597 1.3334190  49.94456
## 1636 1636 -76.88991 1.1925004 101.36662
## 1637 1637 -76.86978 0.9755306  85.44720
## 1638 1638 -76.46939 1.2752621  33.36278
## 1639 1639 -76.59913 1.3199981  39.53609
## 1640 1640 -76.60808 1.4676271  49.45220
## 1641 1641 -76.57229 1.3781550  39.13297
## 1642 1642 -76.45374 0.9106633  57.05455
## 1643 1643 -76.90110 0.8704009  65.98630
## 1644 1644 -76.79597 1.2976301  86.03439
## 1645 1645 -76.68189 1.3960494  51.31767
## 1646 1646 -76.86531 1.2305261  90.99371
## 1647 1647 -76.42690 1.1343436  96.01814
## 1648 1648 -76.76242 0.9017161 133.10446
## 1649 1649 -76.79149 0.9061897  72.73182
## 1650 1650 -76.64387 1.1656588 136.45634
## 1651 1651 -76.85860 0.9173737  83.05766
## 1652 1652 -76.74899 0.9777674  66.52931
## 1653 1653 -76.90333 0.9173737 111.58147
## 1654 1654 -76.58123 0.8748745 123.70320
## 1655 1655 -76.46939 1.4676271  78.16606
## 1656 1656 -76.74899 1.2528941  90.59544
## 1657 1657 -76.76018 0.9956618  55.04515
## 1658 1658 -76.63268 1.2797357  52.44118
## 1659 1659 -76.42018 1.3893390  50.96976
## 1660 1660 -76.90333 1.4228910  71.84618
## 1661 1661 -76.48505 1.3199981  30.53687
## 1662 1662 -76.72215 1.4631535  63.18011
## 1663 1663 -76.86755 1.0314507  56.73282
## 1664 1664 -76.52084 0.9800042 130.17632
## 1665 1665 -76.80491 1.1365804  83.59331
## 1666 1666 -76.66176 1.0851339 174.99982
## 1667 1667 -76.60584 0.8815849 118.92788
## 1668 1668 -76.92123 1.3669710  86.18633
## 1669 1669 -76.59689 0.9621098 133.80885
## 1670 1670 -76.68189 1.2193420  34.16039
## 1671 1671 -76.92347 1.2260524  74.83470
## 1672 1672 -76.41795 0.9039529  29.44082
## 1673 1673 -76.47834 1.3021037  28.74657
## 1674 1674 -76.88544 0.9419786  58.03448
## 1675 1675 -76.71321 0.9442154 132.91292
## 1676 1676 -76.74228 0.9106633 132.81097
## 1677 1677 -76.74676 1.0739499  75.47935
## 1678 1678 -76.65952 1.1097387 139.27107
## 1679 1679 -76.90110 1.2797357  93.84148
## 1680 1680 -76.68413 1.0560555 149.69800
## 1681 1681 -76.76913 1.1701324  86.55139
## 1682 1682 -76.78478 0.9665834  98.13345
## 1683 1683 -76.84741 0.9397418  98.76366
## 1684 1684 -76.80044 1.0896075  84.14507
## 1685 1685 -76.46268 1.0426347 117.41056
## 1686 1686 -76.81386 0.9777674  93.62834
## 1687 1687 -76.88544 1.0135562  78.08804
## 1688 1688 -76.61031 1.3557870  34.42542
## 1689 1689 -76.47163 1.1007915  63.43884
## 1690 1690 -76.71992 1.0761867  66.12054
## 1691 1691 -76.71992 1.3021037  67.43781
## 1692 1692 -76.68636 1.4161806  40.18542
## 1693 1693 -76.47834 0.8838217  57.23676
## 1694 1694 -76.80491 1.2596045  64.29975
## 1695 1695 -76.85636 1.0448715  64.57632
## 1696 1696 -76.47163 1.4072334  42.94418
## 1697 1697 -76.70202 0.9218473 120.04729
## 1698 1698 -76.46492 1.4586799  55.65627
## 1699 1699 -76.55663 1.3199981  43.85110
## 1700 1700 -76.62150 1.1030283 135.41898
## 1701 1701 -76.74452 0.9330314 155.74876
## 1702 1702 -76.56334 0.8726377 109.94188
## 1703 1703 -76.53203 1.0135562 130.99794
## 1704 1704 -76.59913 1.3423662  36.60495
## 1705 1705 -76.79373 0.8748745 133.84367
## 1706 1706 -76.55663 0.9822410 127.22089
## 1707 1707 -76.73110 1.2551309  97.75810
## 1708 1708 -76.59018 1.4184174  33.33863
## 1709 1709 -76.60360 1.3669710  36.46817
## 1710 1710 -76.46716 1.2886829  34.75441
## 1711 1711 -76.74676 0.9800042  51.29382
## 1712 1712 -76.85412 1.2774989  68.76345
## 1713 1713 -76.57452 1.3960494  29.09201
## 1714 1714 -76.79820 1.1030283  68.45177
## 1715 1715 -76.63715 1.2260524  36.31009
## 1716 1716 -76.78926 0.9934250  75.82686
## 1717 1717 -76.91899 0.9442154 105.65202
## 1718 1718 -76.66400 1.3446030  63.39663
## 1719 1719 -76.88768 0.9218473  83.16375
## 1720 1720 -76.48953 0.9732938 133.47310
## 1721 1721 -76.41124 1.1857900 104.27312
## 1722 1722 -76.57676 1.0135562 122.57265
## 1723 1723 -76.88991 1.2953933  96.62476
## 1724 1724 -76.67518 1.4609167  48.67856
## 1725 1725 -76.88768 1.4117070  97.21433
## 1726 1726 -76.74676 1.4564431  58.28326
## 1727 1727 -76.42913 1.4653903  63.62744
## 1728 1728 -76.67965 1.2193420  32.67142
## 1729 1729 -76.71992 1.4474959  57.57748
## 1730 1730 -76.76689 1.3468398  75.75774
## 1731 1731 -76.46492 1.2461837  31.35276
## 1732 1732 -76.55887 1.1925004  50.06507
## 1733 1733 -76.83399 0.8726377 145.09248
## 1734 1734 -76.44703 1.2953933  24.98467
## 1735 1735 -76.88544 1.2193420  80.62184
## 1736 1736 -76.73781 1.3803918  80.97122
## 1737 1737 -76.51637 0.9553994 121.47154
## 1738 1738 -76.68189 1.4005230  59.07062
## 1739 1739 -76.91228 1.2327629  89.75640
## 1740 1740 -76.85636 0.9218473 100.64135
## 1741 1741 -76.82281 1.0940811 101.03239
## 1742 1742 -76.88768 1.3110509  53.36719
## 1743 1743 -76.41571 1.3513134  53.00322
## 1744 1744 -76.68413 1.3289453  65.18069
## 1745 1745 -76.73557 1.4094702  64.62624
## 1746 1746 -76.81610 0.9486890  79.04872
## 1747 1747 -76.85860 1.0269770  73.88396
## 1748 1748 -76.74899 1.0515819  92.43745
## 1749 1749 -76.69084 1.3871022  55.00267
## 1750 1750 -76.59913 1.0560555 133.90445
## 1751 1751 -76.85860 0.9218473 102.63055
## 1752 1752 -76.68636 1.3110509  60.03995
## 1753 1753 -76.69084 1.4273646  38.61521
## 1754 1754 -76.57005 0.9240841 118.97914
## 1755 1755 -76.83623 1.1007915  90.11456
## 1756 1756 -76.84070 1.4094702  82.80157
## 1757 1757 -76.71097 1.1030283 106.40757
## 1758 1758 -76.69307 1.3401294  62.53372
## 1759 1759 -76.42242 1.4676271  53.51928
## 1760 1760 -76.74676 1.0627659  88.64326
## 1761 1761 -76.44479 1.2886829  26.03829
## 1762 1762 -76.44703 1.4385487  40.50500
## 1763 1763 -76.71544 1.0448715  66.53242
## 1764 1764 -76.66176 0.8972425 116.93600
## 1765 1765 -76.81386 0.9822410  91.36074
## 1766 1766 -76.61702 1.2349997  31.51557
## 1767 1767 -76.74005 0.9889514  49.98224
## 1768 1768 -76.52979 1.0023722 118.80879
## 1769 1769 -76.67965 1.0918443 152.30420
## 1770 1770 -76.76018 1.3177613  74.07964
## 1771 1771 -76.59466 1.0851339  67.26989
## 1772 1772 -76.76018 0.9084265 147.29236
## 1773 1773 -76.90110 1.2439469  94.94503
## 1774 1774 -76.71768 1.2126316  38.46752
## 1775 1775 -76.66400 1.0739499 170.71008
## 1776 1776 -76.68189 1.4139438  42.11644
## 1777 1777 -76.69755 1.3759182  72.62403
## 1778 1778 -76.61255 1.3334190  43.10707
## 1779 1779 -76.54321 1.2394733  49.03439
## 1780 1780 -76.50295 0.9352682 117.50478
## 1781 1781 -76.64610 1.2551309  32.32098
## 1782 1782 -76.80044 1.1768428  77.70465
## 1783 1783 -76.46492 1.4340751  36.85678
## 1784 1784 -76.74452 1.1298700 101.61514
## 1785 1785 -76.78255 1.0538187  72.21301
## 1786 1786 -76.80044 1.2305261  63.33729
## 1787 1787 -76.79597 0.9755306  88.37727
## 1788 1788 -76.41571 1.4385487  38.42531
## 1789 1789 -76.63044 1.1276331 139.94510
## 1790 1790 -76.66623 1.1030283 175.89439
## 1791 1791 -76.90333 1.3557870  96.31314
## 1792 1792 -76.68189 1.2036844  98.78479
## 1793 1793 -76.81834 1.0761867  85.51633
## 1794 1794 -76.55663 1.0113194 130.08365
## 1795 1795 -76.55216 1.1678956 110.19962
## 1796 1796 -76.52531 1.3669710  24.88351
## 1797 1797 -76.71097 1.2372365  64.39754
## 1798 1798 -76.64834 1.4430223  37.95317
## 1799 1799 -76.89439 1.1925004  98.73171
## 1800 1800 -76.56110 1.1723692 149.44040
## 1801 1801 -76.68636 1.4609167  42.45278
## 1802 1802 -76.56110 1.3826286  31.18077
## 1803 1803 -76.42913 1.2819725  32.63314
## 1804 1804 -76.73781 1.2707885  69.63678
## 1805 1805 -76.92123 0.9442154 110.15063
## 1806 1806 -76.74452 0.9867146  50.90620
## 1807 1807 -76.76689 1.0873707  72.07758
## 1808 1808 -76.65505 1.1902636 120.88625
## 1809 1809 -76.64163 1.0113194 145.64247
## 1810 1810 -76.61702 1.1231595 141.30998
## 1811 1811 -76.74228 1.3334190  87.91978
## 1812 1812 -76.89662 1.3557870 103.10286
## 1813 1813 -76.90557 0.8927689  60.59950
## 1814 1814 -76.69755 1.1253963 134.07274
## 1815 1815 -76.63939 1.3893390  50.41248
## 1816 1816 -76.56334 1.4407855  53.66312
## 1817 1817 -76.43137 1.1768428  59.99023
## 1818 1818 -76.84070 1.1790796  80.27907
## 1819 1819 -76.89886 1.3669710  87.99934
## 1820 1820 -76.43361 1.3334190  48.58558
## 1821 1821 -76.59466 1.0605291 133.50044
## 1822 1822 -76.56110 1.1835532  66.58945
## 1823 1823 -76.50742 1.1410540  66.94066
## 1824 1824 -76.60137 1.0247402 129.47925
## 1825 1825 -76.44255 1.4676271  50.68774
## 1826 1826 -76.89886 1.0739499  66.49462
## 1827 1827 -76.82952 1.4139438  90.46912
## 1828 1828 -76.71544 1.0403979  55.51748
## 1829 1829 -76.53426 1.2663149  52.25332
## 1830 1830 -76.79149 0.8882953 134.71667
## 1831 1831 -76.87649 1.1947372  81.80553
## 1832 1832 -76.47387 0.9934250  55.96105
## 1833 1833 -76.89215 1.0538187  68.83862
## 1834 1834 -76.55439 1.1388172 127.31570
## 1835 1835 -76.61926 1.4586799  42.01109
## 1836 1836 -76.84294 1.0940811  82.52707
## 1837 1837 -76.83399 1.4430223  83.96535
## 1838 1838 -76.53426 1.0292139 146.73201
## 1839 1839 -76.53650 1.2148684  36.12116
## 1840 1840 -76.57900 1.1231595  61.68072
## 1841 1841 -76.88991 1.0515819  68.33300
## 1842 1842 -76.91452 0.9800042  83.71461
## 1843 1843 -76.80715 1.3177613  69.29253
## 1844 1844 -76.78478 1.4184174  65.11018
## 1845 1845 -76.88991 0.9621098 115.99446
## 1846 1846 -76.81834 0.9419786  89.08530
## 1847 1847 -76.84070 1.2618413  92.06470
## 1848 1848 -76.64387 1.0940811 122.65507
## 1849 1849 -76.72663 1.3311822  68.38522
## 1850 1850 -76.75123 1.3132877  75.16424
## 1851 1851 -76.55887 1.2819725  31.70053
## 1852 1852 -76.71992 1.0963179  78.86840
## 1853 1853 -76.44479 1.1567116  71.46677
## 1854 1854 -76.69307 1.2417101  42.54195
## 1855 1855 -76.71097 0.9934250 138.92809
## 1856 1856 -76.55216 1.4407855  54.23182
## 1857 1857 -76.56334 0.9665834 130.26147
## 1858 1858 -76.45150 0.9039529  40.21712
## 1859 1859 -76.66847 1.1298700 162.73096
## 1860 1860 -76.72663 1.4363119  46.48821
## 1861 1861 -76.83623 1.3714446  67.00936
## 1862 1862 -76.85860 1.1925004  88.16234
## 1863 1863 -76.80491 1.4273646  67.94608
## 1864 1864 -76.52979 1.3960494  29.56012
## 1865 1865 -76.70650 1.2439469  77.56456
## 1866 1866 -76.77807 1.0359243  60.50327
## 1867 1867 -76.75123 1.2484205  79.68768
## 1868 1868 -76.87873 0.9911882  79.82874
## 1869 1869 -76.84965 1.2707885  68.43073
## 1870 1870 -76.68860 0.9307946 125.67400
## 1871 1871 -76.57900 1.1030283 146.23367
## 1872 1872 -76.66623 1.3065773  55.56649
## 1873 1873 -76.60360 1.0202666 134.59866
## 1874 1874 -76.46939 1.2059212  62.60310
## 1875 1875 -76.63268 1.0135562 166.39064
## 1876 1876 -76.42018 1.4340751  39.00145
## 1877 1877 -76.80268 0.9352682  73.84547
## 1878 1878 -76.75794 1.3871022  79.88661
## 1879 1879 -76.74005 1.0694763  84.12098
## 1880 1880 -76.74005 0.9039529 136.15079
## 1881 1881 -76.54321 1.3893390  32.93662
## 1882 1882 -76.84294 1.0135562  53.05326
## 1883 1883 -76.44926 1.4474959  44.29093
## 1884 1884 -76.72663 1.2931565  66.72321
## 1885 1885 -76.47387 1.1052651  70.94941
## 1886 1886 -76.76465 1.4497327  68.64134
## 1887 1887 -76.67742 0.9017161 120.20763
## 1888 1888 -76.83176 0.8927689  54.75532
## 1889 1889 -76.81610 1.3624974  76.23140
## 1890 1890 -76.52531 1.0269770 139.89256
## 1891 1891 -76.44255 1.2260524  57.89386
## 1892 1892 -76.62597 0.9173737 116.80207
## 1893 1893 -76.51860 1.3938126  36.80867
## 1894 1894 -76.72663 1.2528941  90.21586
## 1895 1895 -76.92123 0.9643466  94.36109
## 1896 1896 -76.76465 1.3915758  83.41542
## 1897 1897 -76.55887 1.3155245  47.79644
## 1898 1898 -76.86083 1.1656588  99.66944
## 1899 1899 -76.47834 1.3647342  40.68314
## 1900 1900 -76.92123 1.3982862  89.74344
## 1901 1901 -76.86531 1.0135562  79.68741
## 1902 1902 -76.91004 0.8950057  63.20779
## 1903 1903 -76.81163 1.1947372  75.61398
## 1904 1904 -76.68860 1.0493451 145.82898
## 1905 1905 -76.51637 1.1880268  83.67252
## 1906 1906 -76.72439 0.9956618 145.97443
## 1907 1907 -76.69755 1.4296015  47.53672
## 1908 1908 -76.49400 1.1209227  78.44769
## 1909 1909 -76.84965 1.0985547  94.48054
## 1910 1910 -76.60584 1.2998669  54.53189
## 1911 1911 -76.86083 1.0784235  91.49652
## 1912 1912 -76.90110 0.9665834  80.88435
## 1913 1913 -76.92123 1.2238156  80.34182
## 1914 1914 -76.67742 1.0403979 141.89828
## 1915 1915 -76.70202 1.3177613  57.69677
## 1916 1916 -76.51860 1.0963179 107.84864
## 1917 1917 -76.73110 1.2596045  88.44214
## 1918 1918 -76.88991 1.4027598  76.81284
## 1919 1919 -76.42466 1.0471083  38.81554
## 1920 1920 -76.61926 1.1231595 140.73045
## 1921 1921 -76.82281 1.2260524  65.67455
## 1922 1922 -76.82952 1.2506573  63.51500
## 1923 1923 -76.65058 1.1343436 138.47310
## 1924 1924 -76.74228 1.3982862  81.55414
## 1925 1925 -76.42242 1.4273646  47.43181
## 1926 1926 -76.47834 1.3356558  30.81592
## 1927 1927 -76.71992 1.1365804  77.08329
## 1928 1928 -76.76465 0.8860585 135.62360
## 1929 1929 -76.53874 1.0985547 125.59341
## 1930 1930 -76.60360 0.9218473 118.57493
## 1931 1931 -76.51637 0.9106633 117.12396
## 1932 1932 -76.88320 1.3222349  82.82511
## 1933 1933 -76.90781 1.1611852  92.21897
## 1934 1934 -76.42466 0.9240841  37.00332
## 1935 1935 -76.44479 1.0314507  33.09624
## 1936 1936 -76.62373 1.2238156  36.27327
## 1937 1937 -76.61702 1.3692078  38.28862
## 1938 1938 -76.87426 1.2193420  84.95472
## 1939 1939 -76.49847 0.9621098 133.76114
## 1940 1940 -76.75571 0.9419786  75.76863
## 1941 1941 -76.71321 1.1656588  64.62032
## 1942 1942 -76.77360 0.8793481 145.97537
## 1943 1943 -76.60808 1.4542063  40.99196
## 1944 1944 -76.91004 0.9934250  77.50910
## 1945 1945 -76.82281 0.9889514  89.80939
## 1946 1946 -76.41571 1.1589484  70.32701
## 1947 1947 -76.54768 0.8905321 110.85426
## 1948 1948 -76.69979 1.1321068 141.14439
## 1949 1949 -76.67294 1.3334190  66.53024
## 1950 1950 -76.65505 0.9285578 115.76692
## 1951 1951 -76.53650 1.1746060 142.01985
## 1952 1952 -76.54097 1.3043405  29.54926
## 1953 1953 -76.87873 1.2171052  84.26084
## 1954 1954 -76.55439 1.2506573  42.60048
## 1955 1955 -76.61702 1.1410540 132.35461
## 1956 1956 -76.53426 1.3826286  30.20011
## 1957 1957 -76.88097 1.4564431  75.72691
## 1958 1958 -76.86978 0.9397418  88.82999
## 1959 1959 -76.55216 1.4049966  30.73825
## 1960 1960 -76.62150 0.9911882 145.63335
## 1961 1961 -76.85636 1.3893390  78.52272
## 1962 1962 -76.42466 0.9151369  42.44919
## 1963 1963 -76.81610 1.1186859  87.33209
## 1964 1964 -76.45821 0.9777674  35.30670
## 1965 1965 -76.78031 0.8771113 128.67766
## 1966 1966 -76.42690 0.9956618  47.01833
## 1967 1967 -76.86755 1.1790796  95.02135
## 1968 1968 -76.65505 0.9106633 121.38211
## 1969 1969 -76.68636 1.3155245  62.87183
## 1970 1970 -76.45374 1.4586799  50.82256
## 1971 1971 -76.77360 1.2417101  77.34621

Ahora vamos a visualizar las muestras

m <- leaflet() %>%
  addTiles() %>%  
  addMarkers(lng=sitios$longit,lat=sitios$latit, popup=sitios$soc, clusterOptions = markerClusterOptions())
m 

ahora vamos a guardar la data

sf::st_write(nmuestras, "C:/Users/ASUS/Desktop/geomatica/r/soc_stder.gpkg", driver = "GPKG", append = F)
## Deleting layer `soc_stder' using driver `GPKG'
## Writing layer `soc_stder' to data source 
##   `C:/Users/ASUS/Desktop/geomatica/r/soc_stder.gpkg' using driver `GPKG'
## Writing 1971 features with 1 fields and geometry type Point.

————————————————————————===================================

##INTERPOLACION ##Cargamos los datos con los que vamos a trabajar

list.files(path = "C:/Users/ASUS/Desktop/geomatica/codes", pattern = "soc_stder.gpkg")
## [1] "soc_stder.gpkg"
getwd()
## [1] "C:/Users/ASUS/Desktop/geomatica/codes"

Cargamos los datos descargados de soil grids

samples = sf::st_read("C:/Users/ASUS/Desktop/geomatica/codes/soc_stder.gpkg")
## Reading layer `soc_stder' from data source 
##   `C:\Users\ASUS\Desktop\geomatica\codes\soc_stder.gpkg' using driver `GPKG'
## Simple feature collection with 1971 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -76.9257 ymin: 0.8704009 xmax: -76.409 ymax: 1.467627
## Geodetic CRS:  +proj=longlat +datum=WGS84 +no_defs
samples
## Simple feature collection with 1971 features and 1 field
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -76.9257 ymin: 0.8704009 xmax: -76.409 ymax: 1.467627
## Geodetic CRS:  +proj=longlat +datum=WGS84 +no_defs
## First 10 features:
##          soc                        geom
## 1   71.67126  POINT (-76.76913 1.281973)
## 2  143.23447   POINT (-76.68189 1.13658)
## 3  118.68003  POINT (-76.8407 0.9777674)
## 4   37.61918   POINT (-76.4269 1.268552)
## 5   86.49920  POINT (-76.87873 1.422891)
## 6  111.73273  POINT (-76.6461 0.9240841)
## 7   43.29821  POINT (-76.75571 1.214868)
## 8   58.80977 POINT (-76.41795 0.9464522)
## 9   67.68050  POINT (-76.85636 1.058292)
## 10  78.52149 POINT (-76.74899 0.9621098)

Cargamos el municipio a trabajar

mocoa = sf::st_read("C:/Users/ASUS/Desktop/geomatica/r/mocoa9377/mocoa_WGS84.shp")
## Reading layer `mocoa_WGS84' from data source 
##   `C:\Users\ASUS\Desktop\geomatica\r\mocoa9377\mocoa_WGS84.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 1 feature and 91 fields
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -76.92165 ymin: 0.8685284 xmax: -76.41003 ymax: 1.467315
## Geodetic CRS:  WGS 84

visualizamos los datos

summary(samples)
##       soc                    geom     
##  Min.   : 24.16   POINT        :1971  
##  1st Qu.: 51.69   epsg:NA      :   0  
##  Median : 75.37   +proj=long...:   0  
##  Mean   : 80.90                       
##  3rd Qu.:109.74                       
##  Max.   :175.89

Graficamos los datos

par(bg = "seashell3")
hist(samples$soc,
       main = "carbono_org del suelo (15-30).",
       xlab = "g/Kg",
       col = "salmon4",
       col.lab = "black",
       col.main = "black",
       col.axis = "black",
       border = "black",
       xaxt = "n",
       yaxt = "n"
       )
axis(1,col = "black", col.axis = "black")
axis(2,col = "black", col.axis = "black")
abline(v = media_soc, col = "aquamarine4",lwd = 3, lty = 1)

Redondeamos los datos

samples$soc = round(samples$soc, 2)
pal = colorNumeric(
  c("#FFFF00", "#FFD700", "#FFA500", "#FF4500", "#8B0000"),
  # colors depend on the count variable
  domain = samples$soc,
  )

realizamos el primer mapeo de los datos

leaflet() %>%
  addPolygons(
    data = mocoa,
    color = "blue",
    opacity = 1,
    weight = 1,
    fillOpacity = 0.2) %>%
 addCircleMarkers(
    data = samples,
    radius= 1.5, 
    label = ~soc,
    color = ~pal(soc),
    fillOpacity = 1,
    stroke = F
  ) %>%
  addLegend(
    data = samples,
    pal = pal,
    values = ~soc,
    position = "bottomleft",
    title = "SOC:",
    opacity = 0.9) %>%
  addProviderTiles("Esri.WorldTopoMap")

Dfinimos G1 como un objeto gstat con la formula de la interpolacion IDW

g1 = gstat(formula = soc ~ 1, data = samples)
(rrr =terra::rast(xmin=-76.92165, xmax=-76.41003, ymin=0.8685284, ymax=1.467315, nrows=370, ncols = 329, vals = 1, crs = "epsg:4326"))
## class       : SpatRaster 
## dimensions  : 370, 329, 1  (nrow, ncol, nlyr)
## resolution  : 0.001555076, 0.001618342  (x, y)
## extent      : -76.92165, -76.41003, 0.8685284, 1.467315  (xmin, xmax, ymin, ymax)
## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
## source(s)   : memory
## name        : lyr.1 
## min value   :     1 
## max value   :     1

Lo convertimos a un objeto stars

stars.rrr <- stars::st_as_stars(rrr)

Interpolamos los valores de SOC al modelo definido en G1(IDW)

z1 = predict(g1, stars.rrr)
## [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  24.72375 61.58555 79.94251 81.30464 99.45864 171.9205      0
## var1.var         NA       NA       NA      NaN       NA       NA 121730
## dimension(s):
##   from  to offset     delta refsys x/y
## x    1 329 -76.92  0.001555 WGS 84 [x]
## y    1 370  1.467 -0.001618 WGS 84 [y]

seleccionamos el primer atributo para cambiarle el nombre

a = which(is.na(z1[[1]]))
z1[[1]][a] = 0.0
z1
## stars object with 2 dimensions and 2 attributes
## attribute(s):
##                Min.  1st Qu.   Median     Mean  3rd Qu.     Max.   NA's
## var1.pred  24.72375 61.58555 79.94251 81.30464 99.45864 171.9205      0
## var1.var         NA       NA       NA      NaN       NA       NA 121730
## dimension(s):
##   from  to offset     delta refsys x/y
## x    1 329 -76.92  0.001555 WGS 84 [x]
## y    1 370  1.467 -0.001618 WGS 84 [y]
names(z1) = "soc"

Creamos la paleta de colores

paleta = colorNumeric(palette = c("#FF4500", "#FF8C00", "#FFA07A", "#FFD700"), domain = range(z1[[1]], na.rm = TRUE), na.color = "transparent")
range(z1[[1]], na.rm = TRUE)
## [1]  24.72375 171.92045
rango_z1 <- range(z1[[1]], na.rm = TRUE)
rango_z1
## [1]  24.72375 171.92045

Mapeamos el IDW

m <- leaflet() %>%
  addTiles() %>%  
  leafem:::addGeoRaster(
      z1,
      opacity = 0.7,                
      colorNumeric = colorNumeric(palette = c("#FF4500", "#FF8C00", "#FFA07A", "#FFD700"), 
                                  domain = z1$soc, na.rm = TRUE))%>%
   addCircleMarkers(
    data = samples,
    radius= 1.5, 
    label = ~soc,
    color = ~paleta(soc),
    fillOpacity = 1,
    stroke = F
     ) %>%
  addPolygons(
    data = mocoa,
    color = "blue",
    opacity = 1,
    weight = 1,
    fillOpacity = 0.2)%>%
  addMiniMap(toggleDisplay = TRUE)%>%
    addLegend("topleft", pal=paleta, values= z1$soc,
    title = "IDW SOC interpolation [%]",
    opacity = 0.9
    ) %>% 
   addProviderTiles("Esri.WorldTopoMap")
## Warning in paleta(soc): Some values were outside the color scale and will be
## treated as NA

## Warning in paleta(soc): Some values were outside the color scale and will be
## treated as NA
## Warning in write_stars.stars(x, dsn = fl): all but first attribute are ignored
m  

Ahora creamos un variograma de la muestra Samples

ok = variogram(soc ~ 1, data=samples)
plot(ok)

Elegimos el variograma que se ajuste mas al modelo

val_ok = automap::autofitVariogram(soc ~ 1, as(samples, "Spatial"))
plot(val_ok)

ajustamos la varieable y el variograma

val_ok$var_model
##   model      psill    range kappa
## 1   Nug   44.05032  0.00000   0.0
## 2   Ste 3186.93497 89.71633   0.4

Hacemos la interpolacion OK

#g2 = gstat(formula = soc ~ 1, model = v_mod_ok$var_model, data = samples)
#z2= predict(g2, stars.rrr)
#g2 = gstat(formula = soc ~ 1, model = val_ok$var_model, data = samples)
#z2= predict(g2, stars.rrr)

Cambiamos el nombre del primer atributo

#a <- which(is.na(z2[[1]]))
#z2[[1]][a] = 0.0
#names(z2) = "soc"

mapeamos la interpolacion por el metodo OK

#m <- leaflet() %>%
#  addTiles() %>%  
 # leafem:::addGeoRaster(
  #    z2,
   #   opacity = 0.7,                
    #  colorNumeric = colorNumeric(palette = c("#FF4500", "#FF8C00", "#FFA07A", "#FFD700"), 
                 #                 domain = z2$soc, na.rm = TRUE)
  #  ) %>%
  # addCircleMarkers(
  #  data = samples,
   # radius= 1.5, 
#    label = ~soc,
 #   color = ~paleta(soc),
  #  fillOpacity = 1,
 #   stroke = F
#  ) %>%
 #   addLegend("bottomright", pal = paleta, values= z2$soc,
 #   title = "OK SOC interpolation [%]"
  #  )
#m

##VALIDACION CRUZADA

Ejecutamos el siguiente codigo en la consola para llevar a cabo la validacion cruzada

##cv2 = gstat.cv(g2)

Sacamos el error cuadratico de la interpolacion IDW

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

Sacamos el error medio cuadratico de la interpolacion OK

#sqrt(sum((cv2$var1.pred - cv2$observed)^2) / nrow(cv2))

###Conclusiones ## la interpolacion de krigin ordinaria es mas efectiva que la interpolacion IDW en terminos de exactitud, como lo deja ver su RMSE que es menor al calculado para la interpolacion IDW ##La interpolacion es una herrmienta muy util en el manejo de variables espaciales, ya que nos permite hacer la prediccion de puntos basado en muestras tomadas

#write_stars(
 # z1, dsn = "C:/Users/ASUS/Desktop/geomatica/r/IDW_soc_stder.tif", layer = 1)
#write_stars(
 # z2, dsn = "C:/Users/ASUS/Desktop/geomatica/r/OK_soc_stder.tif", layer = 1
#)