##Taller de Iterpolación
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
## 97 97 -76.74452 1.0090826 42.49902
## 98 98 -76.78926 1.3244717 67.19967
## 99 99 -76.60584 1.4184174 32.65365
## 100 100 -76.63715 0.8771113 114.95205
## 101 101 -76.81834 1.2707885 67.37453
## 102 102 -76.74899 1.4296015 55.98833
## 103 103 -76.60360 1.2998669 53.45612
## 104 104 -76.91004 1.3378926 79.18814
## 105 105 -76.56110 1.4161806 40.81404
## 106 106 -76.53203 1.0023722 113.93743
## 107 107 -76.69531 1.2797357 69.41571
## 108 108 -76.53203 0.9375050 127.25356
## 109 109 -76.85189 1.2864461 73.08084
## 110 110 -76.65952 1.1947372 120.07780
## 111 111 -76.74452 1.4452591 51.20707
## 112 112 -76.80491 1.3490766 67.03595
## 113 113 -76.65952 1.1790796 145.73872
## 114 114 -76.48729 1.4273646 36.41594
## 115 115 -76.77584 1.3468398 76.52350
## 116 116 -76.43361 1.1142123 117.93347
## 117 117 -76.71321 1.2260524 36.32624
## 118 118 -76.70202 0.9263209 120.78541
## 119 119 -76.59689 0.9822410 149.58081
## 120 120 -76.85189 0.9509258 107.76381
## 121 121 -76.89886 0.9419786 81.32713
## 122 122 -76.58795 1.1343436 62.14902
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## 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
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## 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
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## 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
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## 1325 1325 -76.92347 1.1209227 75.09298
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## 1330 1330 -76.58123 1.4161806 35.32905
## 1331 1331 -76.48505 0.9352682 135.70709
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## 1338 1338 -76.65729 1.1388172 142.95236
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## 1340 1340 -76.88768 1.0940811 92.35755
## 1341 1341 -76.68413 1.3938126 55.29843
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## 1344 1344 -76.77136 1.4676271 79.36624
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## 1349 1349 -76.81610 1.4318383 64.38400
## 1350 1350 -76.70873 1.3826286 74.47491
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## 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
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## 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
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## 1366 1366 -76.66847 1.3177613 58.60682
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## 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
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## 1379 1379 -76.43137 0.9956618 52.08791
## 1380 1380 -76.80491 1.0918443 77.23622
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## 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
#)