title: “Datos del suelo para el departamento de Meta”
author: “Nawel Sebastian Ballesteros Sierra” date: “10/11/2025” output: html_document: toc: true toc_depth: 3 number_sections: true
Introduccion
Este cuaderno de R ilustra cómo descargar los datos de propiedades del suelo a cualquier profundidad desde la plataforma SoilGrids, Estos datos están en estructura Raster con resolución espacial de 250m.
Ventajas de descargar datos de SoildGrids usando Rstudio
Este metodo ofrece varias ventajas sobre otros modos de descarga de datos, ya que es mas adaptable para varios proyectos a la vez y se puede revisar a fondo como se filtraron los datos descargados, como tambien solo tener una aplicacion para no estar importando o exportando
Opciones para descargar los datos
SoilGrids ofrece tres clases de servicios principales para descargarlos:
- Web Mapping Service (WMS): Útil para visualización y exploración general de los datos.
- Web Coverage Service (WCS): La mejor opción para obtener subconjuntos de mapas y usar SoilGrids como entrada para otros modelos.
- Web Distributed Authoring and Versioning (WebDAV): Permite descargar mapas globales completos en formato VRT.
En este cuaderno utilizaremos el servicio WebDAV, que nos permite descargar datos específicos para nuestra región de interés de manera eficiente.
2.Configuraciones
Primero se limpia el espacio de trabajo
rm(list=ls())Instalar las librerias desde la consola no desde el cuaderno
terra, ggplot2, tidyterra, sf, and leaflet
como se instalan
##install.packages(“terra”)
Se llaman las librerias para verificar que esten instaladas correctamente
library(terra)## Warning: package 'terra' was built under R version 4.5.2## terra 1.8.80library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.5.2library(tidyterra)## Warning: package 'tidyterra' was built under R version 4.5.2##
## Adjuntando el paquete: 'tidyterra'## The following object is masked from 'package:stats':
##
## filterlibrary(sf)## Warning: package 'sf' was built under R version 4.5.2## Linking to GEOS 3.13.1, GDAL 3.11.4, PROJ 9.7.0; sf_use_s2() is TRUElibrary(leaflet)## Warning: package 'leaflet' was built under R version 4.5.2library(RColorBrewer)## Warning: package 'RColorBrewer' was built under R version 4.5.2library(gdalUtilities)## Warning: package 'gdalUtilities' was built under R version 4.5.2##
## Adjuntando el paquete: 'gdalUtilities'## The following object is masked from 'package:sf':
##
## gdal_rasterizelibrary(XML)## Warning: package 'XML' was built under R version 4.5.2library(dplyr)## Warning: package 'dplyr' was built under R version 4.5.2##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:terra':
##
## intersect, union## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union2.1 Que es SolilGrids?
SoilGrids es un sistema global de información de suelos desarrollado por ISRIC – World Soil Information. Está diseñado para predecir propiedades y clases de suelos (como textura, carbono orgánico, pH, densidad aparente, etc.) a nivel mundial usando:
-Modelos estadísticos y de machine learning,
-Variables ambientales globales (covariables),
-Y bases de datos de suelos observados.
¿Cómo funciona?
SoilGrids usa datos de todo el mundo (perfiles de suelos reales) y los combina con información ambiental (clima, relieve, cobertura vegetal, etc.) para predecir las propiedades del suelo en cualquier punto del planeta.
Los resultados se entregan en formato raster (imágenes geográficas), con una resolución estándar (por ejemplo, de 250 m o 1 km).
Qué se puede obtener:
Cada celda del mapa contiene valores como:
Carbono orgánico (%)
Textura (arena, limo, arcilla)
pH
Densidad aparente
Capacidad de intercambio catiónico, entre otros.
2.2 Definir las variables de interes
url = "https://files.isric.org/soilgrids/latest/data/"ruta al servidor
Se puede definir la variable de interés, profundidad y estadístico como: soc, phh2o, clay, silt, sand, cec, bdod, cfvo, nitrogen, ocd
voi = "soc"
depth = "15-30cm"
quantile = "mean"
(variable = paste(url, voi, sep=""))## [1] "https://files.isric.org/soilgrids/latest/data/soc"se concatenan las cadenas en el texto
(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"el código crea una dirección (URL) que lleva directamente al archivo virtual VRT, el cual contiene información sobre el carbono orgánico del suelo (SOC) en la capa de 15 a 30 centímetros de profundidad.
Este archivo no guarda todos los datos físicamente, sino que funciona como un enlace inteligente que permite acceder solo a la parte del mapa que necesitas, sin tener que descargar todo el conjunto de datos.
3.Descargar una variable para un departamento en especifico
Tomamos el geopackage de departamento que hemos llevado a travez del curso y lo pegamos en la misma carpeta del cuaderno y lo llamamos
(meta = st_read("meta.gpkg"))## Reading layer `output' from data source
## `C:\Users\nawel\Downloads\GB2\Proyecto 4\meta.gpkg' using driver `GPKG'
## Simple feature collection with 29 features and 11 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -74.9206 ymin: 1.570401 xmax: -71.0749 ymax: 4.860201
## Geodetic CRS: WGS 84## Simple feature collection with 29 features and 11 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -74.9206 ymin: 1.570401 xmax: -71.0749 ymax: 4.860201
## Geodetic CRS: WGS 84
## First 10 features:
## ID_0 ISO NAME_0 ID_1 NAME_1 ID_2 NAME_2 TYPE_2 ENGTYPE_2
## 1 53 COL Colombia 20 Meta 683 Acacías Municipio Municipality
## 2 53 COL Colombia 20 Meta 684 Barranca de Upía Municipio Municipality
## 3 53 COL Colombia 20 Meta 685 Cabuyaro Municipio Municipality
## 4 53 COL Colombia 20 Meta 686 Castilla la Nueva Municipio Municipality
## 5 53 COL Colombia 20 Meta 687 Cumaral Municipio Municipality
## 6 53 COL Colombia 20 Meta 688 El Calvario Municipio Municipality
## 7 53 COL Colombia 20 Meta 689 El Castillo Municipio Municipality
## 8 53 COL Colombia 20 Meta 690 El Dorado Municipio Municipality
## 9 53 COL Colombia 20 Meta 691 Fuente de Oro Municipio Municipality
## 10 53 COL Colombia 20 Meta 692 Granada Municipio Municipality
## NL_NAME_2 VARNAME_2 geom
## 1 <NA> <NA> MULTIPOLYGON (((-73.695 3.8...
## 2 <NA> <NA> MULTIPOLYGON (((-72.8167 4....
## 3 <NA> <NA> MULTIPOLYGON (((-73.0633 4....
## 4 <NA> <NA> MULTIPOLYGON (((-73.51823 3...
## 5 <NA> <NA> MULTIPOLYGON (((-73.0633 4....
## 6 <NA> <NA> MULTIPOLYGON (((-73.6382 4....
## 7 <NA> <NA> MULTIPOLYGON (((-73.7588 3....
## 8 <NA> <NA> MULTIPOLYGON (((-73.86369 3...
## 9 <NA> <NA> MULTIPOLYGON (((-73.4358 3....
## 10 <NA> <NA> MULTIPOLYGON (((-73.7794 3....Cambiamos a la proyeccion de Interrupted Goode Homolosine (IGH) utilizada por SoilGrids.
igh='+proj=igh +lat_0=0 +lon_0=0 +datum=WGS84 +units=m +no_defs'
meta_igh <- st_transform(meta, igh)Obtenemos el bounding box (cuadro delimitador) de nuestro departamento de interés:
(bbox <- st_bbox(meta_igh))## xmin ymin xmax ymax
## -8343808.0 174816.2 -7918248.7 541035.1Definimos los límites en el formato requerido por GDAL (upper left y lower right)
ulx = bbox$xmin
uly = bbox$ymax
lrx = bbox$xmax
lry = bbox$ymin
(bb <- c(ulx, uly, lrx, lry))## xmin ymax xmax ymin
## -8343808.0 541035.1 -7918248.7 174816.2Le indicamos las direcciones para la descarga de datos:
sg_url="/vsicurl/https://files.isric.org/soilgrids/latest/data/"
datos = 'soc/soc_15-30cm_mean.vrt'
file = "soc_igh_15_30.tif"Tenga en cuenta que la siguiente tarea puede tardar varios minutos, solo ejecútela una vez
gdal_translate(paste0(sg_url,datos), file,
tr=c(250,250),
projwin=bb,
projwin_srs=igh)Leemos el archivo descargado y aplicamos el factor de conversión. Según la documentación de SoilGrids, los valores de SOC están en unidades mapeadas y deben dividirse por 10 para obtener gramos por kilogramo (g/kg).
(meta_soc <- terra::rast(file)/10)## class : SpatRaster
## size : 1466, 1704, 1 (nrow, ncol, nlyr)
## resolution : 250, 250 (x, y)
## extent : -8344000, -7918000, 174750, 541250 (xmin, xmax, ymin, ymax)
## coord. ref. : Interrupted_Goode_Homolosine
## source(s) : memory
## varname : soc_igh_15_30
## name : soc_igh_15_30
## min value : 7.4
## max value : 116.54. Exploracion de datos
Generamos un histograma para ver los valores del carbono organico y como este esta distribuido
terra::hist(meta_soc,
main="Distribución del Carbono Orgánico del Suelo en el Meta",
xlab="SOC (g/kg)",
ylab="Frecuencia",
col="#8B7355") # Color tierra## Warning: [hist] a sample of 40% of the cells was used (of which 1% was NA)
Un pequeño resumen estadístico de los datos es util:
summary(meta_soc)## Warning: [summary] used a sample## soc_igh_15_30
## Min. : 7.60
## 1st Qu.: 12.00
## Median : 14.80
## Mean : 20.67
## 3rd Qu.: 20.90
## Max. :112.90
## NA's :835Cambiamos el nombre del atributo para que sea más claro mas adelante:
(names(meta_soc) <- "soc")## [1] "soc"Se extraen los valores válidos (sin NA) para crear la paleta de colores:
valores <- values(meta_soc, na.rm=TRUE)Se crea una paleta de colores geomorfológica para que sea visiblemente mas agradable
orangecyan <- colorNumeric( palette = c("#F4E4C1", "#D4A574", "#8B7355", "#6B8E23", "#2F4F2F"),
domain = valores,
na.color = "transparent")Ahora se puede visualizar el cantidad de carbono orgánico en el departamento del Meta en el sigiente mapa:
leaflet::leaflet(meta) %>%
addTiles() %>%
setView(-73, 3.2, 7.5) %>%
addPolygons(color = "#8B4513", weight = 1.0, smoothFactor = 0.5,
opacity = 0.6, fillOpacity = 0.1) %>%
addRasterImage(meta_soc,
colors = c("#F4E4C1", "#D4A574", "#8B7355", "#6B8E23", "#2F4F2F"),
opacity = 0.7) %>%
addLegend(pal = orangecyan,
values = valores,
title = "Carbono Orgánico<br>del Suelo (SOC)<br>[g/kg]",
position = "bottomright")#5. Visualicion con tidyterra
Esta es una visualizzacion alternativa y es mas personalizable para cada gusto
Se convierte a formato sf para overlay
meta_sf <- st_as_sf(meta)Se utiliza ggplot y tidyterra para generar esta visualizacion
ggplot() +
geom_spatraster(data = meta_soc) +
geom_sf(data = meta_sf, fill = NA, color = "#8B4513", linewidth = 0.8) +
scale_fill_gradientn(
colors = c("#F4E4C1", "#D4A574", "#8B7355", "#6B8E23", "#2F4F2F"),
name = "SOC (g/kg)",
na.value = "transparent"
) +
labs(
title = "Carbono Orgánico del Suelo - Departamento de Meta",
subtitle = "Profundidad: 15-30 cm | Fuente: SoilGrids 250m",
caption = "Elaborado por: Nawel Ballesteros"
) +
theme_minimal() +
theme(
plot.title = element_text(size = 16, face = "bold", hjust = 0.5),
plot.subtitle = element_text(size = 12, hjust = 0.5, color = "gray40"),
plot.caption = element_text(size = 9, color = "gray50"),
legend.position = "right",
legend.key.height = unit(1.5, "cm"),
panel.grid = element_line(color = "gray90", linewidth = 0.),
axis.text = element_text(size = 9)
) +
coord_sf()## <SpatRaster> resampled to 500528 cells.
6. Muestreo aleatorio del departamento
En esta sección generaremos un conjunto de muestras aleatorias del dataset de SOC, lo cual es útil para:
- Análisis estadísticos
- Validación de modelos
- Estudios de campo
- Análisis de correlación con otras variables
Establecemos un semilla
set.seed(1299)Transformamos el raster a proyeccion geografica WGS84
geog = "+proj=longlat +datum=WGS84"
(geog.soc = project(meta_soc, geog))## class : SpatRaster
## size : 1484, 1767, 1 (nrow, ncol, nlyr)
## resolution : 0.002219061, 0.002219061 (x, y)
## extent : -74.94602, -71.02494, 1.569044, 4.862131 (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +no_defs
## source(s) : memory
## name : soc
## min value : 7.686866
## max value : 113.909142Se ajusta el numero de puntos de muestreo, es a gusto personal
(samples <- terra::spatSample(geog.soc, 2000, "random", as.points=TRUE))## class : SpatVector
## geometry : points
## dimensions : 2000, 1 (geometries, attributes)
## extent : -74.94491, -71.02605, 1.570154, 4.861022 (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +no_defs
## names : soc
## type : <num>
## values : 12.63
## 13.81
## 19.63Transformamos las muestras a formato sf
(muestras <- sf::st_as_sf(samples))## Simple feature collection with 2000 features and 1 field
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -74.94491 ymin: 1.570154 xmax: -71.02605 ymax: 4.861022
## 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 12.62703 POINT (-73.39379 2.508817)
## 2 13.80790 POINT (-73.71555 1.885261)
## 3 19.63049 POINT (-72.98326 2.448902)
## 4 67.23750 POINT (-74.43897 4.414991)
## 5 10.67811 POINT (-71.84489 2.093852)
## 6 12.77386 POINT (-71.42326 3.884635)
## 7 NA POINT (-74.93604 3.23445)
## 8 15.53341 POINT (-71.64073 3.385346)
## 9 10.87906 POINT (-72.53279 4.315133)
## 10 18.04544 POINT (-72.30645 3.367594)Eliminamos lo valores vacios
nmuestras <- na.omit(muestras)Extraemos las coordenadas y valores de SOC:
longit <- st_coordinates(nmuestras)[,1]
latit <- st_coordinates(nmuestras)[,2]
soc <- nmuestras$socNuevamente hacemos un R¿resumen estadístico de las muestras:
summary(soc)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.525 12.215 15.183 20.770 20.957 82.989length(soc)## [1] 1947Se calculan cuántas muestras se perdieron por caer en áreas sin datos
muestras_perdidas <- 2000 - length(soc)
cat("Muestras con datos válidos:", length(soc), "\n")## Muestras con datos válidos: 1947cat("Muestras sin datos (NA):", muestras_perdidas, "\n")## Muestras sin datos (NA): 53Creamos un data frame con las muestras:
id <- seq(1, length(soc), 1)
(sitios <- data.frame(id, longit, latit, soc))## id longit latit soc
## 1 1 -73.39379 2.508817 12.627027
## 2 2 -73.71555 1.885261 13.807898
## 3 3 -72.98326 2.448902 19.630489
## 4 4 -74.43897 4.414991 67.237503
## 5 5 -71.84489 2.093852 10.678108
## 6 6 -71.42326 3.884635 12.773856
## 7 7 -71.64073 3.385346 15.533415
## 8 8 -72.53279 4.315133 10.879059
## 9 9 -72.30645 3.367594 18.045439
## 10 10 -73.39823 4.770040 42.801113
## 11 11 -71.17917 3.012544 9.865023
## 12 12 -71.98691 3.514052 18.913410
## 13 13 -73.94634 4.244123 58.327316
## 14 14 -74.41900 1.976242 15.860669
## 15 15 -74.51885 4.605830 28.884750
## 16 16 -72.19772 3.531804 29.186375
## 17 17 -71.58747 3.935673 11.776837
## 18 18 -73.26952 3.463013 24.181335
## 19 19 -73.47812 3.791434 13.629659
## 20 20 -72.72585 3.884635 13.173020
## 21 21 -74.14161 3.010325 15.594854
## 22 22 -71.14366 4.199742 18.318558
## 23 23 -71.99356 2.138234 9.999767
## 24 24 -73.92415 1.814251 14.526975
## 25 25 -72.25763 4.084350 11.551924
## 26 26 -73.62457 3.079116 11.138087
## 27 27 -72.58605 2.653056 15.498909
## 28 28 -71.09706 3.090211 10.010201
## 29 29 -71.13035 2.151548 11.591968
## 30 30 -72.92779 3.829158 11.313859
## 31 31 -74.03288 3.105744 19.540319
## 32 32 -73.96187 1.658916 12.646704
## 33 33 -71.13701 3.995588 13.289227
## 34 34 -71.69177 2.959286 12.411655
## 35 35 -74.86059 4.756726 18.554726
## 36 36 -72.26429 3.072458 11.763924
## 37 37 -72.41297 2.182615 9.415278
## 38 38 -71.44545 3.520709 12.738675
## 39 39 -73.17632 2.883838 23.268221
## 40 40 -71.93587 3.323212 13.452772
## 41 41 -71.16142 4.701250 17.986324
## 42 42 -72.47510 3.443042 14.565955
## 43 43 -71.83823 2.828362 10.679255
## 44 44 -74.81843 2.371235 23.233925
## 45 45 -74.04176 4.177551 47.713692
## 46 46 -73.34053 3.147907 15.650774
## 47 47 -72.48398 4.592516 21.524437
## 48 48 -71.56307 3.139030 11.387366
## 49 49 -73.48477 2.994791 10.736495
## 50 50 -72.15112 2.526569 11.458094
## 51 51 -74.60984 3.642757 64.811058
## 52 52 -73.09422 4.332885 13.816968
## 53 53 -72.18440 3.549557 18.724812
## 54 54 -74.40346 3.438604 71.830925
## 55 55 -72.08898 2.391207 12.525830
## 56 56 -73.04984 2.850552 11.895268
## 57 57 -72.46844 3.121278 18.031683
## 58 58 -74.20153 4.734535 43.491001
## 59 59 -73.08978 4.763383 17.404598
## 60 60 -71.76944 3.070239 13.431874
## 61 61 -74.28142 2.506598 14.372551
## 62 62 -72.58827 3.582843 18.757214
## 63 63 -74.03954 3.620567 64.818207
## 64 64 -71.87151 3.924578 11.587939
## 65 65 -71.73393 2.082757 9.128140
## 66 66 -71.58747 1.843098 11.867939
## 67 67 -74.40346 4.645773 33.185753
## 68 68 -71.76722 1.714393 11.060143
## 69 69 -71.47430 3.880197 13.962518
## 70 70 -73.00324 2.129357 13.937172
## 71 71 -73.74440 4.144265 34.006035
## 72 72 -74.00847 4.466029 48.223164
## 73 73 -73.14969 1.767650 9.322140
## 74 74 -72.66594 3.347622 12.168643
## 75 75 -74.16602 2.617551 15.191873
## 76 76 -72.39743 3.449699 18.352915
## 77 77 -72.89006 4.106541 13.787618
## 78 78 -71.37001 1.845317 15.546946
## 79 79 -73.98406 2.999229 22.929983
## 80 80 -74.85615 4.051065 19.104771
## 81 81 -72.80796 3.298803 12.339255
## 82 82 -72.74582 2.111605 11.511707
## 83 83 -71.47652 2.497722 11.976504
## 84 84 -73.93746 3.920140 42.179527
## 85 85 -74.08170 2.111605 10.922023
## 86 86 -74.35243 2.435588 15.973155
## 87 87 -73.28728 2.448902 12.058355
## 88 88 -74.20819 3.052487 15.431029
## 89 89 -72.33752 3.427508 13.520188
## 90 90 -72.23988 3.454137 13.866014
## 91 91 -74.78070 1.687764 21.622852
## 92 92 -72.77023 3.261079 13.094805
## 93 93 -73.94856 1.647821 25.339500
## 94 94 -72.86565 2.262501 11.106497
## 95 95 -73.41154 2.309101 10.478009
## 96 96 -72.29536 4.568106 18.113010
## 97 97 -73.95078 2.000652 11.277647
## 98 98 -73.11197 4.794450 21.647945
## 99 99 -72.79021 4.858803 10.201476
## 100 100 -74.10167 4.201961 46.325871
## 101 101 -72.66150 2.573170 19.764017
## 102 102 -74.40790 2.187053 11.527646
## 103 103 -72.96107 3.465232 13.774543
## 104 104 -71.80494 4.057722 13.803032
## 105 105 -74.85393 3.531804 37.130154
## 106 106 -72.21991 4.463810 15.839684
## 107 107 -74.04619 3.196726 38.802681
## 108 108 -72.52170 2.575389 15.159735
## 109 109 -73.57575 4.596954 51.427826
## 110 110 -72.73917 2.983696 16.080715
## 111 111 -72.74361 4.563668 12.863356
## 112 112 -74.13274 4.084350 55.218933
## 113 113 -71.60079 3.045830 8.525004
## 114 114 -74.50110 1.825346 11.734307
## 115 115 -72.83237 4.130951 13.862784
## 116 116 -74.03510 4.332885 62.531193
## 117 117 -73.80876 3.735958 31.836887
## 118 118 -74.38127 2.182615 16.645830
## 119 119 -74.54326 1.583468 18.607460
## 120 120 -73.84648 3.764806 53.496517
## 121 121 -72.18884 2.586484 13.289244
## 122 122 -71.95806 1.703298 12.308593
## 123 123 -71.83601 1.605659 12.152179
## 124 124 -72.22656 3.933454 17.371166
## 125 125 -72.00910 4.459372 15.269954
## 126 126 -73.10975 2.613113 11.768114
## 127 127 -72.81240 4.159799 15.156222
## 128 128 -74.27698 4.031093 63.179592
## 129 129 -72.30201 2.606456 10.254818
## 130 130 -72.34196 4.545915 14.941314
## 131 131 -74.66309 2.002871 14.088641
## 132 132 -74.24591 3.196726 17.191240
## 133 133 -74.76073 4.037750 26.113907
## 134 134 -71.71840 4.565887 12.136090
## 135 135 -73.52472 4.505972 60.646832
## 136 136 -72.51726 2.730723 11.216611
## 137 137 -73.48921 3.886854 20.590473
## 138 138 -74.12608 4.292942 79.693687
## 139 139 -71.92921 3.525147 22.166782
## 140 140 -73.15635 3.119059 14.806067
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## 955 955 -72.19772 1.683326 9.459535
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## 957 957 -72.27538 2.067224 9.222450
## 958 958 -72.84346 1.956271 10.476305
## 959 959 -73.07647 4.776698 24.211990
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## 961 961 -74.78070 3.724862 42.256084
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## 966 966 -74.25257 1.925204 11.323867
## 967 967 -73.08534 1.982899 12.278864
## 968 968 -73.38713 2.832800 11.111938
## 969 969 -73.10753 2.428931 10.609469
## 970 970 -74.84506 1.916327 16.055311
## 971 971 -71.78053 4.195304 16.513401
## 972 972 -74.45672 2.013966 12.608212
## 973 973 -71.81382 3.605033 9.869691
## 974 974 -71.76278 2.890495 16.379316
## 975 975 -73.97962 3.154564 19.437952
## 976 976 -74.31914 2.930438 15.637665
## 977 977 -74.19265 4.024436 76.174850
## 978 978 -72.35083 2.011747 10.299914
## 979 979 -74.74298 2.861648 67.649429
## 980 980 -74.01735 1.916327 13.328794
## 981 981 -74.26810 4.616925 41.843430
## 982 982 -72.01797 2.990353 15.076180
## 983 983 -72.35971 3.971178 11.783230
## 984 984 -74.78070 4.221932 16.854300
## 985 985 -72.60602 3.547338 11.247387
## 986 986 -73.57353 4.321790 44.147259
## 987 987 -71.16807 1.985118 11.300244
## 988 988 -72.03794 2.626427 14.706287
## 989 989 -74.79846 4.066598 20.182444
## 990 990 -72.53279 1.767650 11.512550
## 991 991 -71.39885 4.847708 16.647970
## 992 992 -72.44181 4.574763 14.781498
## 993 993 -74.31470 1.683326 21.491922
## 994 994 -71.82491 2.093852 11.651777
## 995 995 -73.06759 3.025858 17.723507
## 996 996 -71.43658 3.374251 10.721457
## 997 997 -71.59413 4.510410 16.397827
## 998 998 -73.62679 2.380111 14.623481
## 999 999 -74.66753 3.252202 41.896774
## 1000 1000 -74.82287 2.692999 32.266235
## 1001 1001 -71.69177 1.880822 12.482052
## 1002 1002 -74.75186 2.353483 23.329054
## 1003 1003 -73.54247 4.548134 82.989464
## 1004 1004 -74.09280 2.182615 11.395303
## 1005 1005 -74.41900 3.585062 63.464867
## 1006 1006 -71.48762 2.759571 9.166522
## 1007 1007 -71.94918 3.769244 13.789335
## 1008 1008 -72.89894 2.488845 11.165317
## 1009 1009 -74.19931 3.558433 50.694458
## 1010 1010 -73.45371 4.843269 57.194691
## 1011 1011 -74.31914 4.767821 37.861298
## 1012 1012 -72.74139 2.877181 15.531752
## 1013 1013 -71.30343 4.233028 11.774274
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## 1016 1016 -71.65183 1.763212 11.536151
## 1017 1017 -71.60523 2.464436 9.297276
## 1018 1018 -72.41962 4.832174 13.607121
## 1019 1019 -74.31470 1.765431 12.644412
## 1020 1020 -74.72523 3.025858 56.348953
## 1021 1021 -72.17109 1.794279 11.893785
## 1022 1022 -72.39299 3.742615 9.390006
## 1023 1023 -72.92779 4.170894 20.013144
## 1024 1024 -73.60016 4.639116 57.828541
## 1025 1025 -72.87453 4.676840 20.816065
## 1026 1026 -73.54469 4.803326 63.235840
## 1027 1027 -71.26127 4.545915 15.908647
## 1028 1028 -73.48033 2.127138 12.759770
## 1029 1029 -72.79464 3.407537 16.936455
## 1030 1030 -73.41820 4.858803 55.294643
## 1031 1031 -71.93365 1.876384 9.896214
## 1032 1032 -71.65848 2.051690 9.241492
## 1033 1033 -73.40267 4.694592 50.700603
## 1034 1034 -72.80130 1.696640 12.176812
## 1035 1035 -71.53644 2.668589 10.527440
## 1036 1036 -72.49729 2.120481 10.109295
## 1037 1037 -71.93587 4.743412 18.460032
## 1038 1038 -71.47208 2.149329 12.477787
## 1039 1039 -71.35004 2.595360 12.670485
## 1040 1040 -73.95743 3.582843 18.866226
## 1041 1041 -72.42850 3.895730 13.469584
## 1042 1042 -72.68147 2.655275 15.378614
## 1043 1043 -72.60824 2.286911 13.530913
## 1044 1044 -71.60967 3.094649 8.903605
## 1045 1045 -73.20517 3.487423 42.693874
## 1046 1046 -71.38332 4.645773 16.865582
## 1047 1047 -73.08534 4.039969 12.961881
## 1048 1048 -73.97297 4.335104 56.544498
## 1049 1049 -72.10452 2.220339 9.835653
## 1050 1050 -72.96329 4.534820 20.178984
## 1051 1051 -72.79021 2.655275 13.386916
## 1052 1052 -73.75772 2.806171 14.601995
## 1053 1053 -71.12369 2.069443 14.413922
## 1054 1054 -73.58907 3.218916 20.201233
## 1055 1055 -73.29615 4.071036 27.581413
## 1056 1056 -71.43880 3.032515 9.888143
## 1057 1057 -72.39078 4.834393 19.186663
## 1058 1058 -72.22656 3.909045 12.611827
## 1059 1059 -71.29012 4.335104 14.614909
## 1060 1060 -71.75169 3.795872 18.949823
## 1061 1061 -74.57655 3.820282 65.213539
## 1062 1062 -73.04762 2.211463 10.367799
## 1063 1063 -74.72523 1.885261 14.398715
## 1064 1064 -73.29393 3.187850 16.241037
## 1065 1065 -71.63629 3.163440 14.581248
## 1066 1066 -73.62014 1.818689 12.173464
## 1067 1067 -71.59413 3.573966 11.487689
## 1068 1068 -73.86645 1.630068 11.287162
## 1069 1069 -71.70287 1.883041 10.135242
## 1070 1070 -73.57797 2.096071 10.461389
## 1071 1071 -74.30361 2.928219 19.404051
## 1072 1072 -74.78514 3.154564 46.458187
## 1073 1073 -71.86264 1.670012 12.151771
## 1074 1074 -71.48762 4.159799 11.259568
## 1075 1075 -73.36938 4.672402 45.443127
## 1076 1076 -74.15937 3.609471 53.307941
## 1077 1077 -73.36494 3.363155 16.686522
## 1078 1078 -74.86503 1.765431 14.826218
## 1079 1079 -74.50110 1.692202 19.457937
## 1080 1080 -73.11863 2.000652 12.512669
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## 1082 1082 -73.31612 3.460794 12.792030
## 1083 1083 -73.24289 4.801107 25.427250
## 1084 1084 -73.76659 3.205602 18.436579
## 1085 1085 -74.47004 4.461591 27.745480
## 1086 1086 -74.60762 3.924578 36.296822
## 1087 1087 -74.75186 3.427508 37.293858
## 1088 1088 -72.55055 4.699030 14.651872
## 1089 1089 -73.80654 4.310695 60.276031
## 1090 1090 -71.51646 2.524350 9.156441
## 1091 1091 -74.58543 2.965943 52.977272
## 1092 1092 -74.44563 2.433369 16.504656
## 1093 1093 -73.40489 4.432743 15.364952
## 1094 1094 -73.73109 3.416413 28.087423
## 1095 1095 -74.72301 4.572544 34.910454
## 1096 1096 -73.20295 4.701250 21.877293
## 1097 1097 -74.02844 4.494877 71.711395
## 1098 1098 -74.73410 2.843895 66.628448
## 1099 1099 -73.57353 3.465232 13.722668
## 1100 1100 -73.80432 3.704891 20.520817
## 1101 1101 -73.24511 4.388362 15.322552
## 1102 1102 -73.87533 2.426712 13.864174
## 1103 1103 -73.60682 4.699030 63.475430
## 1104 1104 -71.70287 1.783184 13.662426
## 1105 1105 -72.48841 2.775104 17.827133
## 1106 1106 -73.85092 2.599798 19.968367
## 1107 1107 -72.30201 2.633084 13.265225
## 1108 1108 -72.29757 4.743412 24.251728
## 1109 1109 -71.98247 3.012544 11.135728
## 1110 1110 -72.02685 4.361733 14.745212
## 1111 1111 -74.26366 3.822501 61.253227
## 1112 1112 -74.47225 4.561449 25.164856
## 1113 1113 -72.31977 4.286285 18.073458
## 1114 1114 -74.65422 4.647992 37.030552
## 1115 1115 -71.39442 2.781761 9.377893
## 1116 1116 -71.41217 4.077693 11.132579
## 1117 1117 -73.57797 2.562074 17.579193
## 1118 1118 -72.40631 4.494877 15.538301
## 1119 1119 -71.48096 3.358717 13.749027
## 1120 1120 -73.18298 4.581420 16.692141
## 1121 1121 -71.60079 3.611690 10.265423
## 1122 1122 -74.72967 3.545119 30.633657
## 1123 1123 -71.23242 3.192288 8.977726
## 1124 1124 -74.22372 2.235872 12.643389
## 1125 1125 -72.53058 2.655275 12.420099
## 1126 1126 -71.28568 3.482985 14.403322
## 1127 1127 -71.57638 2.624208 8.973774
## 1128 1128 -73.05649 3.480766 20.022259
## 1129 1129 -74.75851 3.678262 24.816414
## 1130 1130 -73.14969 3.400880 14.304785
## 1131 1131 -71.31453 1.989556 12.881170
## 1132 1132 -73.38048 1.951832 12.667870
## 1133 1133 -71.82270 3.278831 15.252990
## 1134 1134 -71.32119 2.142672 13.953797
## 1135 1135 -71.96028 1.974023 11.569482
## 1136 1136 -73.70446 4.264094 57.443607
## 1137 1137 -71.49871 3.902387 15.634153
## 1138 1138 -73.88198 3.256641 22.986755
## 1139 1139 -73.57575 1.705517 12.530674
## 1140 1140 -74.29473 2.932658 14.206681
## 1141 1141 -71.27681 2.262501 11.994106
## 1142 1142 -72.01353 3.902387 12.097090
## 1143 1143 -73.87089 4.408333 43.060925
## 1144 1144 -72.86122 4.190865 11.514341
## 1145 1145 -73.57575 3.294365 18.141626
## 1146 1146 -71.78497 3.525147 20.334726
## 1147 1147 -72.71920 3.811406 10.208963
## 1148 1148 -72.85234 4.858803 26.080040
## 1149 1149 -71.42105 4.268533 14.954747
## 1150 1150 -72.55277 3.063582 12.105076
## 1151 1151 -72.20881 2.624208 12.074530
## 1152 1152 -73.38491 4.401676 19.931618
## 1153 1153 -74.63868 2.229215 13.914689
## 1154 1154 -74.39681 2.195929 14.158707
## 1155 1155 -73.00324 4.794450 21.038523
## 1156 1156 -71.58526 3.267736 12.428164
## 1157 1157 -73.01655 2.293568 13.211411
## 1158 1158 -74.03066 3.347622 16.752626
## 1159 1159 -74.06617 3.445261 24.313234
## 1160 1160 -71.43658 3.966740 13.104127
## 1161 1161 -74.74520 3.318774 36.968365
## 1162 1162 -72.76358 2.311320 14.019055
## 1163 1163 -73.79322 2.062785 12.183435
## 1164 1164 -72.68369 1.721050 9.654686
## 1165 1165 -73.24289 4.834393 28.198677
## 1166 1166 -73.22070 3.782558 16.888554
## 1167 1167 -71.40551 2.184834 12.000559
## 1168 1168 -74.84062 4.031093 19.567612
## 1169 1169 -74.64090 2.402302 15.906316
## 1170 1170 -72.34196 1.638945 11.447824
## 1171 1171 -71.95140 4.514848 18.476908
## 1172 1172 -74.24147 3.482985 79.474464
## 1173 1173 -71.54309 4.026655 14.402857
## 1174 1174 -72.67481 3.605033 17.210712
## 1175 1175 -72.19328 4.259656 20.926935
## 1176 1176 -72.17996 4.208618 16.463326
## 1177 1177 -73.52250 1.749898 15.603533
## 1178 1178 -73.88198 1.876384 10.763961
## 1179 1179 -72.18218 3.296584 14.290307
## 1180 1180 -72.59715 2.932658 12.011742
## 1181 1181 -72.83459 4.159799 18.367897
## 1182 1182 -73.78435 2.031719 10.474604
## 1183 1183 -74.62537 3.997807 30.179585
## 1184 1184 -74.60318 1.898575 18.534214
## 1185 1185 -73.38935 3.720424 12.379533
## 1186 1186 -74.36796 4.756726 50.446590
## 1187 1187 -74.66753 1.914108 13.242553
## 1188 1188 -71.83823 2.235872 10.130711
## 1189 1189 -72.21547 1.809812 10.426847
## 1190 1190 -74.43453 3.520709 57.997494
## 1191 1191 -71.30787 2.635303 11.885785
## 1192 1192 -73.77769 4.102103 25.097973
## 1193 1193 -74.06395 2.790638 18.661993
## 1194 1194 -73.80654 3.707110 25.381317
## 1195 1195 -71.60523 3.915702 13.793768
## 1196 1196 -74.47225 1.623411 19.213749
## 1197 1197 -74.42565 3.247764 32.689041
## 1198 1198 -73.38048 3.802530 13.200820
## 1199 1199 -71.63186 3.993369 16.066547
## 1200 1200 -73.04318 3.607252 20.644346
## 1201 1201 -73.04540 4.497096 14.878846
## 1202 1202 -72.57718 3.802530 10.415281
## 1203 1203 -71.76056 2.069443 9.468458
## 1204 1204 -71.50981 1.760993 14.465199
## 1205 1205 -74.35464 1.974023 17.374887
## 1206 1206 -71.36113 3.070239 13.602489
## 1207 1207 -71.36335 3.693796 13.238965
## 1208 1208 -73.46924 3.056925 12.735599
## 1209 1209 -72.67925 3.775901 14.149593
## 1210 1210 -74.70082 3.944550 21.940815
## 1211 1211 -72.00688 3.178973 9.724955
## 1212 1212 -72.60380 1.834222 11.015250
## 1213 1213 -74.15049 3.039172 16.756516
## 1214 1214 -72.83237 3.664948 14.641360
## 1215 1215 -72.77467 2.692999 22.794044
## 1216 1216 -73.06981 3.178973 11.225937
## 1217 1217 -74.46116 2.857209 20.939240
## 1218 1218 -72.23766 3.962302 19.206348
## 1219 1219 -72.52614 1.576811 9.709113
## 1220 1220 -73.77325 4.284066 69.458443
## 1221 1221 -71.53866 3.480766 11.395060
## 1222 1222 -72.02241 4.823298 19.938650
## 1223 1223 -74.89166 2.957067 66.810814
## 1224 1224 -73.32722 4.352857 15.757480
## 1225 1225 -72.56164 1.829784 9.630703
## 1226 1226 -71.72728 4.335104 15.775423
## 1227 1227 -71.75834 4.190865 18.037319
## 1228 1228 -73.06315 2.961505 16.945770
## 1229 1229 -74.85615 4.823298 25.670828
## 1230 1230 -72.44403 2.934877 15.344940
## 1231 1231 -71.18361 4.246342 13.269756
## 1232 1232 -74.23925 3.325431 21.342867
## 1233 1233 -73.45371 3.593938 11.603152
## 1234 1234 -72.28648 2.717409 16.104330
## 1235 1235 -73.81097 3.605033 14.317471
## 1236 1236 -73.50474 3.527366 14.662355
## 1237 1237 -73.27174 3.840254 26.513823
## 1238 1238 -73.56022 3.454137 14.179914
## 1239 1239 -72.36193 2.244748 9.289315
## 1240 1240 -72.19328 2.759571 10.799522
## 1241 1241 -71.67402 4.488220 12.723300
## 1242 1242 -72.19328 2.364578 10.231194
## 1243 1243 -73.82651 3.929016 42.932140
## 1244 1244 -73.59794 3.469670 17.969778
## 1245 1245 -73.80432 1.574592 12.115425
## 1246 1246 -71.90036 3.911264 13.893274
## 1247 1247 -71.57638 2.169300 9.510612
## 1248 1248 -73.87311 4.847708 36.107536
## 1249 1249 -72.74804 1.714393 10.194656
## 1250 1250 -74.61649 3.334308 54.271362
## 1251 1251 -71.70952 3.054706 9.643577
## 1252 1252 -72.79464 2.570951 10.521723
## 1253 1253 -72.18440 4.747850 16.598106
## 1254 1254 -74.64756 4.703469 28.653145
## 1255 1255 -71.87151 3.192288 9.696009
## 1256 1256 -74.49888 4.113198 70.962326
## 1257 1257 -74.72523 4.006683 23.392399
## 1258 1258 -72.79021 1.665573 10.141397
## 1259 1259 -73.58019 2.071662 15.597954
## 1260 1260 -71.38332 2.045033 12.420853
## 1261 1261 -72.75470 3.385346 17.064764
## 1262 1262 -71.53200 1.854194 10.257293
## 1263 1263 -72.47732 4.774479 14.789950
## 1264 1264 -73.74440 2.943753 14.392958
## 1265 1265 -71.82048 3.658291 18.599298
## 1266 1266 -74.04176 1.763212 14.919744
## 1267 1267 -71.61410 2.025061 13.153346
## 1268 1268 -74.74076 1.769869 17.053320
## 1269 1269 -73.89086 3.327650 47.542686
## 1270 1270 -73.97075 2.038376 13.527659
## 1271 1271 -74.38127 4.636897 37.366234
## 1272 1272 -72.72585 2.136014 11.563254
## 1273 1273 -72.37968 3.491861 12.923582
## 1274 1274 -71.99578 2.994791 13.628058
## 1275 1275 -73.40711 4.805545 55.609936
## 1276 1276 -74.56324 1.703298 14.489160
## 1277 1277 -71.47430 3.460794 8.874367
## 1278 1278 -73.76216 2.717409 15.374843
## 1279 1279 -74.41012 4.035531 76.721024
## 1280 1280 -73.39823 3.476328 25.697195
## 1281 1281 -73.33610 4.634678 22.498114
## 1282 1282 -71.27237 4.162018 12.474026
## 1283 1283 -74.27698 2.668589 15.255863
## 1284 1284 -73.28062 4.681278 19.285364
## 1285 1285 -72.92779 3.900168 15.504038
## 1286 1286 -72.00688 4.765602 16.938063
## 1287 1287 -72.31755 3.968959 13.293073
## 1288 1288 -71.83601 3.172316 11.217112
## 1289 1289 -73.64454 2.659713 17.127871
## 1290 1290 -72.23544 2.628646 10.238887
## 1291 1291 -71.37223 4.219713 13.262365
## 1292 1292 -71.20358 4.565887 19.025640
## 1293 1293 -73.46702 2.801733 13.730880
## 1294 1294 -74.34133 2.027280 15.372182
## 1295 1295 -74.91829 2.147110 18.951284
## 1296 1296 -72.15999 4.197523 14.413457
## 1297 1297 -72.65706 3.147907 13.159275
## 1298 1298 -74.66531 3.440823 49.087551
## 1299 1299 -74.29917 3.221136 19.781990
## 1300 1300 -72.67925 4.750069 18.291544
## 1301 1301 -74.32136 4.814422 41.999084
## 1302 1302 -72.65484 1.940737 10.916755
## 1303 1303 -74.75186 3.336527 34.808815
## 1304 1304 -74.02844 4.639116 43.929409
## 1305 1305 -71.75390 2.983696 10.127219
## 1306 1306 -72.47732 4.654649 24.358204
## 1307 1307 -73.07868 2.997010 18.570333
## 1308 1308 -71.72062 3.332089 10.508797
## 1309 1309 -73.43817 4.095446 16.595615
## 1310 1310 -73.78213 2.173739 14.251697
## 1311 1311 -72.96773 2.311320 13.969295
## 1312 1312 -72.32198 3.596157 20.235527
## 1313 1313 -73.54913 4.239685 24.909233
## 1314 1314 -73.03208 2.881619 15.521281
## 1315 1315 -73.02321 1.940737 9.841280
## 1316 1316 -71.80050 4.399457 20.566521
## 1317 1317 -74.31692 1.922985 12.160017
## 1318 1318 -71.71174 3.951207 11.562561
## 1319 1319 -74.44341 1.896356 12.219772
## 1320 1320 -73.01433 2.726285 12.741426
## 1321 1321 -71.84267 2.606456 11.575456
## 1322 1322 -74.60540 1.716612 16.314342
## 1323 1323 -73.74662 1.876384 16.654842
## 1324 1324 -72.35305 3.842473 19.208097
## 1325 1325 -74.85837 3.028077 57.485374
## 1326 1326 -72.23322 4.204180 15.972669
## 1327 1327 -73.40711 3.139030 12.648396
## 1328 1328 -72.95664 1.618973 10.959704
## 1329 1329 -73.51362 2.127138 12.101087
## 1330 1330 -71.50093 2.584265 11.324026
## 1331 1331 -72.34639 4.579201 16.562857
## 1332 1332 -72.41297 2.801733 12.488796
## 1333 1333 -72.88784 2.173739 9.998153
## 1334 1334 -72.89894 3.187850 12.312410
## 1335 1335 -73.03208 4.772259 15.831314
## 1336 1336 -71.30343 2.408959 9.472843
## 1337 1337 -73.06537 3.409756 27.624641
## 1338 1338 -72.21325 2.238091 9.845567
## 1339 1339 -73.68893 2.697437 12.850874
## 1340 1340 -73.43151 2.908248 13.156001
## 1341 1341 -72.95885 1.714393 11.565244
## 1342 1342 -71.37001 3.877978 11.657711
## 1343 1343 -73.26730 4.426086 23.451803
## 1344 1344 -74.42344 3.578404 77.248016
## 1345 1345 -73.47146 4.037750 20.763824
## 1346 1346 -71.49206 2.018404 10.107688
## 1347 1347 -73.10531 4.048845 16.010660
## 1348 1348 -74.57211 3.514052 56.923466
## 1349 1349 -74.31470 4.481562 53.811325
## 1350 1350 -73.67561 4.841050 54.369514
## 1351 1351 -73.39823 4.565887 33.631947
## 1352 1352 -74.27920 1.947394 14.142020
## 1353 1353 -71.62964 4.672402 10.338976
## 1354 1354 -72.25097 2.435588 12.270281
## 1355 1355 -72.31089 1.998433 9.851340
## 1356 1356 -72.25541 1.803155 10.723902
## 1357 1357 -74.75629 1.867508 14.312884
## 1358 1358 -72.57052 3.673824 15.699404
## 1359 1359 -71.59413 3.940111 12.927398
## 1360 1360 -71.50315 1.741022 11.538144
## 1361 1361 -74.27254 2.271377 14.340888
## 1362 1362 -72.24210 2.182615 10.247714
## 1363 1363 -74.18156 2.810609 15.408500
## 1364 1364 -73.26287 2.959286 11.143037
## 1365 1365 -73.66674 3.409756 16.879631
## 1366 1366 -71.38998 3.301022 12.483477
## 1367 1367 -72.86122 4.583639 15.418226
## 1368 1368 -74.15271 4.281847 81.506996
## 1369 1369 -71.53644 3.784777 15.581858
## 1370 1370 -73.16301 3.336527 15.486435
## 1371 1371 -72.73251 4.042188 14.064070
## 1372 1372 -72.84124 2.322416 11.231046
## 1373 1373 -71.81604 1.732145 12.907743
## 1374 1374 -73.58241 4.252999 32.355927
## 1375 1375 -73.08090 3.107963 12.570647
## 1376 1376 -74.33689 2.284692 14.681787
## 1377 1377 -74.74520 1.601221 18.255711
## 1378 1378 -74.17046 2.932658 15.110177
## 1379 1379 -74.76073 3.585062 43.968868
## 1380 1380 -74.51885 1.867508 11.776434
## 1381 1381 -73.78878 3.008106 15.083749
## 1382 1382 -72.36193 4.809984 12.252502
## 1383 1383 -73.43817 4.847708 53.632652
## 1384 1384 -73.39823 4.861022 51.331989
## 1385 1385 -72.23988 3.724862 11.880164
## 1386 1386 -71.50315 4.461591 15.857022
## 1387 1387 -74.77405 2.386768 19.321968
## 1388 1388 -74.30139 2.007309 13.699297
## 1389 1389 -73.44039 1.914108 16.959156
## 1390 1390 -74.57655 4.228589 34.063648
## 1391 1391 -72.77689 3.356498 15.418011
## 1392 1392 -74.05729 2.244748 11.714421
## 1393 1393 -72.39743 2.353483 15.254115
## 1394 1394 -71.54531 1.780965 15.897558
## 1395 1395 -72.56164 2.049471 11.474440
## 1396 1396 -73.59794 4.505972 56.165855
## 1397 1397 -71.40773 3.684919 12.899659
## 1398 1398 -71.91368 3.156783 8.685421
## 1399 1399 -71.90924 4.443838 13.723139
## 1400 1400 -73.72665 4.321790 68.946800
## 1401 1401 -73.17632 2.697437 14.083592
## 1402 1402 -74.89166 2.113824 20.232077
## 1403 1403 -72.89894 3.323212 15.447094
## 1404 1404 -74.19487 2.147110 13.235174
## 1405 1405 -73.25621 3.891292 29.108740
## 1406 1406 -72.77245 4.268533 21.685768
## 1407 1407 -72.37524 1.942956 13.027674
## 1408 1408 -74.45450 3.860225 72.937943
## 1409 1409 -74.02179 3.966740 62.852345
## 1410 1410 -72.57496 2.033938 10.909290
## 1411 1411 -72.18884 3.269955 13.186406
## 1412 1412 -72.94110 4.208618 16.706585
## 1413 1413 -74.14827 1.658916 11.322401
## 1414 1414 -74.38349 1.585687 20.857594
## 1415 1415 -74.10833 2.728504 25.003025
## 1416 1416 -73.50031 4.257437 19.359434
## 1417 1417 -71.82491 1.663354 14.559668
## 1418 1418 -73.76437 1.807593 13.518637
## 1419 1419 -71.98469 2.985915 11.560964
## 1420 1420 -72.08676 4.386143 13.134599
## 1421 1421 -72.94332 4.694592 19.047903
## 1422 1422 -73.47368 3.957864 17.255787
## 1423 1423 -71.50315 4.683497 13.864784
## 1424 1424 -71.37666 4.423867 16.536674
## 1425 1425 -74.51664 2.393426 20.201735
## 1426 1426 -73.36716 1.967366 11.598100
## 1427 1427 -71.92477 3.691577 15.805171
## 1428 1428 -74.37905 2.198148 14.754628
## 1429 1429 -72.08454 4.486001 21.405790
## 1430 1430 -74.43453 2.606456 18.759632
## 1431 1431 -74.44341 2.457778 13.249665
## 1432 1432 -73.28728 4.208618 13.894156
## 1433 1433 -71.13479 2.007309 11.345707
## 1434 1434 -72.13336 1.592344 9.740583
## 1435 1435 -71.96250 3.724862 11.919599
## 1436 1436 -73.53803 2.446683 13.382832
## 1437 1437 -72.42184 3.964521 12.120106
## 1438 1438 -72.59937 3.261079 11.833293
## 1439 1439 -73.02321 1.951832 9.606927
## 1440 1440 -74.32358 2.970382 13.153407
## 1441 1441 -74.52329 3.247764 52.219978
## 1442 1442 -71.36779 2.588703 11.204884
## 1443 1443 -71.64517 2.353483 9.946143
## 1444 1444 -71.46986 3.502956 12.683450
## 1445 1445 -71.53644 1.616754 11.142562
## 1446 1446 -73.13194 2.653056 14.180444
## 1447 1447 -73.71334 2.850552 12.643107
## 1448 1448 -71.90924 1.971804 9.300570
## 1449 1449 -74.21484 2.533226 17.329844
## 1450 1450 -72.87231 4.474905 13.135245
## 1451 1451 -71.96693 2.653056 14.131760
## 1452 1452 -74.35021 1.721050 10.588357
## 1453 1453 -74.77405 2.919343 61.723549
## 1454 1454 -73.28062 2.408959 18.014071
## 1455 1455 -72.04238 4.335104 11.487350
## 1456 1456 -73.18964 1.769869 11.955957
## 1457 1457 -74.09280 2.537665 19.780836
## 1458 1458 -72.81462 2.187053 10.732808
## 1459 1459 -72.84346 4.805545 16.592680
## 1460 1460 -73.16301 3.008106 15.542991
## 1461 1461 -73.13194 3.545119 15.930659
## 1462 1462 -72.18440 4.297380 12.692783
## 1463 1463 -71.31231 3.751491 13.962075
## 1464 1464 -73.56910 3.134592 12.287781
## 1465 1465 -72.25097 4.472686 15.801991
## 1466 1466 -71.49206 4.437181 15.394033
## 1467 1467 -72.57274 4.126513 17.016954
## 1468 1468 -73.34497 1.854194 12.167771
## 1469 1469 -74.68307 2.950410 64.241188
## 1470 1470 -72.76358 2.883838 15.182827
## 1471 1471 -73.55800 4.761164 43.021469
## 1472 1472 -72.83015 2.710751 14.544522
## 1473 1473 -72.36858 3.447480 12.197751
## 1474 1474 -74.71635 2.582046 32.258720
## 1475 1475 -73.51140 2.468874 12.887613
## 1476 1476 -71.57638 1.614535 12.942855
## 1477 1477 -73.20073 3.951207 15.796189
## 1478 1478 -74.10833 1.572373 14.699777
## 1479 1479 -73.35607 1.843098 13.534394
## 1480 1480 -71.14588 1.729926 12.049978
## 1481 1481 -74.35908 2.801733 22.320072
## 1482 1482 -73.48699 4.605830 57.822979
## 1483 1483 -71.81160 4.539258 10.883075
## 1484 1484 -73.59794 2.002871 12.526947
## 1485 1485 -74.26810 2.757352 12.609455
## 1486 1486 -74.44341 3.383127 69.413582
## 1487 1487 -71.14366 2.408959 10.090137
## 1488 1488 -71.62298 3.715986 14.956438
## 1489 1489 -71.49871 2.144891 13.031115
## 1490 1490 -73.97518 4.692373 47.525524
## 1491 1491 -74.49001 4.230808 26.787394
## 1492 1492 -71.16142 4.128732 15.112840
## 1493 1493 -73.89530 1.749898 14.663901
## 1494 1494 -71.09706 4.264094 10.356969
## 1495 1495 -72.37968 4.312914 12.122183
## 1496 1496 -72.67925 2.431150 15.767693
## 1497 1497 -74.17268 2.506598 17.193790
## 1498 1498 -74.75851 4.636897 18.231153
## 1499 1499 -72.49063 4.039969 19.084045
## 1500 1500 -74.76073 4.514848 22.908398
## 1501 1501 -73.22070 3.170097 24.599318
## 1502 1502 -74.91163 3.272174 24.044298
## 1503 1503 -72.10230 1.929642 9.448696
## 1504 1504 -74.78514 4.390581 17.848019
## 1505 1505 -72.22213 2.249187 9.935327
## 1506 1506 -73.19408 2.282473 13.536278
## 1507 1507 -74.06839 2.897153 21.579718
## 1508 1508 -73.33610 4.091008 13.811018
## 1509 1509 -73.33388 2.826143 10.759258
## 1510 1510 -74.41456 3.090211 23.526321
## 1511 1511 -73.46258 1.885261 13.712147
## 1512 1512 -72.43738 2.131576 10.247260
## 1513 1513 -74.30361 3.105744 16.394009
## 1514 1514 -71.20580 2.768447 12.113040
## 1515 1515 -73.75106 2.950410 11.715981
## 1516 1516 -74.64978 4.077693 22.909487
## 1517 1517 -74.58986 3.534023 72.982712
## 1518 1518 -72.32642 2.621989 11.004436
## 1519 1519 -74.81399 3.269955 59.102680
## 1520 1520 -71.69843 4.752288 16.257812
## 1521 1521 -72.09120 1.612316 10.040392
## 1522 1522 -72.73029 4.201961 14.716407
## 1523 1523 -72.00466 4.368390 10.314534
## 1524 1524 -74.21041 2.739599 16.219147
## 1525 1525 -73.54469 2.854990 13.851740
## 1526 1526 -74.25701 3.929016 66.932724
## 1527 1527 -74.83840 3.511833 43.580597
## 1528 1528 -71.92033 4.226370 13.591428
## 1529 1529 -74.30804 3.134592 16.572433
## 1530 1530 -74.21041 1.574592 12.736512
## 1531 1531 -71.62742 3.795872 11.988839
## 1532 1532 -71.94031 3.318774 13.884139
## 1533 1533 -71.50315 3.920140 15.789460
## 1534 1534 -72.48841 4.845489 16.004934
## 1535 1535 -74.03510 2.599798 17.213118
## 1536 1536 -71.29012 2.127138 11.465276
## 1537 1537 -74.75851 2.704094 30.455975
## 1538 1538 -74.70969 1.985118 15.571043
## 1539 1539 -73.31390 3.591719 11.837730
## 1540 1540 -74.51220 3.325431 31.288214
## 1541 1541 -74.24591 4.319571 51.916111
## 1542 1542 -74.51664 1.840879 13.865992
## 1543 1543 -71.94031 3.418632 19.619198
## 1544 1544 -74.78292 4.295161 16.717691
## 1545 1545 -72.09342 1.738802 9.840746
## 1546 1546 -74.83174 2.180396 24.149099
## 1547 1547 -72.22878 3.764806 15.302431
## 1548 1548 -73.95965 3.021420 24.004519
## 1549 1549 -72.33752 2.289130 9.369491
## 1550 1550 -74.57433 3.185631 31.669857
## 1551 1551 -71.64739 3.862444 15.168865
## 1552 1552 -71.62964 2.641960 9.011715
## 1553 1553 -72.33530 2.897153 10.584746
## 1554 1554 -71.64073 2.344606 9.572022
## 1555 1555 -74.54770 4.264094 20.682083
## 1556 1556 -72.19328 3.582843 19.587616
## 1557 1557 -73.04096 4.632459 20.986719
## 1558 1558 -73.84426 2.435588 14.419860
## 1559 1559 -72.44181 2.655275 12.239847
## 1560 1560 -73.00102 2.100510 13.208123
## 1561 1561 -74.37018 2.573170 18.010956
## 1562 1562 -71.96915 4.217494 15.483035
## 1563 1563 -71.81604 3.935673 11.498622
## 1564 1564 -74.49001 4.357295 52.711674
## 1565 1565 -73.01877 2.506598 12.542507
## 1566 1566 -72.21991 2.835019 10.155407
## 1567 1567 -71.71840 3.252202 9.757005
## 1568 1568 -73.14748 2.957067 22.279800
## 1569 1569 -74.25701 2.965943 17.053932
## 1570 1570 -71.12591 3.443042 13.877776
## 1571 1571 -71.58304 4.213056 13.781379
## 1572 1572 -71.56528 3.660510 11.894747
## 1573 1573 -74.01957 4.235247 56.117325
## 1574 1574 -73.95743 4.654649 55.434597
## 1575 1575 -71.64295 2.326854 9.843844
## 1576 1576 -72.61934 3.988931 13.956613
## 1577 1577 -73.62901 2.142672 14.244698
## 1578 1578 -74.74076 2.788419 64.391663
## 1579 1579 -74.72523 4.008902 20.253958
## 1580 1580 -74.41012 3.875759 68.813889
## 1581 1581 -71.75169 2.661932 8.748465
## 1582 1582 -71.93143 4.576982 13.634257
## 1583 1583 -72.81018 3.305460 10.753823
## 1584 1584 -73.83316 2.138234 14.881870
## 1585 1585 -72.90116 2.357921 12.871737
## 1586 1586 -72.82571 4.539258 19.709160
## 1587 1587 -74.28585 4.328447 50.956135
## 1588 1588 -73.26287 1.607878 13.337037
## 1589 1589 -74.24591 2.375673 17.105513
## 1590 1590 -71.78941 4.505972 19.275793
## 1591 1591 -73.61126 2.879400 10.699209
## 1592 1592 -72.94554 4.468248 18.292229
## 1593 1593 -72.96773 2.131576 9.955206
## 1594 1594 -71.59413 2.932658 11.966825
## 1595 1595 -74.23260 4.157579 74.858521
## 1596 1596 -74.45228 3.644976 55.042141
## 1597 1597 -72.63265 2.313539 14.350894
## 1598 1598 -73.27840 3.460794 11.855000
## 1599 1599 -72.63931 3.649414 13.157887
## 1600 1600 -73.03874 4.843269 17.255959
## 1601 1601 -72.15334 3.303241 31.794704
## 1602 1602 -72.05348 2.830581 11.476135
## 1603 1603 -72.41297 3.587281 10.600494
## 1604 1604 -71.60523 4.137608 15.396341
## 1605 1605 -72.68369 4.565887 22.801399
## 1606 1606 -74.20375 3.858006 48.515392
## 1607 1607 -72.28204 4.419429 13.353795
## 1608 1608 -74.42122 2.499941 16.841839
## 1609 1609 -74.66753 3.509614 64.346054
## 1610 1610 -72.95885 2.453340 10.857601
## 1611 1611 -71.81826 1.687764 14.698245
## 1612 1612 -73.98184 4.246342 54.512432
## 1613 1613 -72.24432 3.600595 13.288464
## 1614 1614 -73.83095 1.878603 12.472037
## 1615 1615 -72.88119 3.050268 16.379152
## 1616 1616 -72.67925 2.735161 15.309385
## 1617 1617 -74.66309 1.814251 14.982714
## 1618 1618 -71.78497 2.189272 10.064429
## 1619 1619 -74.49223 3.793653 52.433399
## 1620 1620 -73.26287 4.004464 15.600390
## 1621 1621 -73.58241 4.663525 55.375813
## 1622 1622 -71.09262 3.312117 16.786119
## 1623 1623 -71.49427 4.488220 17.837990
## 1624 1624 -73.03874 4.499315 17.318630
## 1625 1625 -74.68307 2.393426 19.707649
## 1626 1626 -71.42326 3.700453 10.425506
## 1627 1627 -73.62235 4.543696 62.836861
## 1628 1628 -72.77911 3.611690 10.302498
## 1629 1629 -74.36352 3.434165 40.609379
## 1630 1630 -73.78878 3.332089 19.058010
## 1631 1631 -72.88563 2.517693 10.314281
## 1632 1632 -72.31755 4.377267 16.679934
## 1633 1633 -74.31470 2.202586 11.888203
## 1634 1634 -72.57496 2.198148 10.246488
## 1635 1635 -72.61712 2.431150 12.143527
## 1636 1636 -73.00324 4.505972 14.968016
## 1637 1637 -71.73171 3.638319 11.709913
## 1638 1638 -74.48335 4.368390 57.155712
## 1639 1639 -74.60318 4.752288 39.697159
## 1640 1640 -73.89974 3.056925 25.473652
## 1641 1641 -74.40568 1.709955 21.251133
## 1642 1642 -74.23260 3.687138 65.922249
## 1643 1643 -74.06839 4.832174 31.122156
## 1644 1644 -73.66008 1.827565 15.218976
## 1645 1645 -74.80068 4.395019 23.134918
## 1646 1646 -71.26127 2.608675 12.926293
## 1647 1647 -71.33672 3.642757 12.383164
## 1648 1648 -73.71112 4.459372 58.893639
## 1649 1649 -73.82651 1.601221 16.049582
## 1650 1650 -74.81177 2.133795 18.270403
## 1651 1651 -73.34497 1.896356 12.698497
## 1652 1652 -71.88927 2.045033 10.691607
## 1653 1653 -72.96329 4.395019 16.309763
## 1654 1654 -71.46099 2.289130 11.518920
## 1655 1655 -74.28585 2.879400 17.927069
## 1656 1656 -74.72079 3.642757 50.390743
## 1657 1657 -73.00324 2.178177 10.980316
## 1658 1658 -73.58463 3.079116 16.342720
## 1659 1659 -73.38491 4.361733 19.134325
## 1660 1660 -74.70969 4.543696 23.416306
## 1661 1661 -74.76517 4.532601 28.061234
## 1662 1662 -74.16159 1.676669 13.377119
## 1663 1663 -73.78878 4.801107 59.872143
## 1664 1664 -73.29171 2.326854 11.306333
## 1665 1665 -73.03430 3.165659 14.432101
## 1666 1666 -71.46543 3.593938 12.553116
## 1667 1667 -71.61410 2.979258 8.969501
## 1668 1668 -71.27903 1.603440 11.721741
## 1669 1669 -74.67863 3.101306 43.117649
## 1670 1670 -74.30804 1.727707 11.041524
## 1671 1671 -73.80432 2.928219 20.479265
## 1672 1672 -74.33911 1.996214 14.856538
## 1673 1673 -71.72728 4.614706 14.744425
## 1674 1674 -74.20153 4.217494 79.791496
## 1675 1675 -72.69479 4.612487 14.887278
## 1676 1676 -71.42770 2.178177 11.538966
## 1677 1677 -73.91527 2.757352 14.905247
## 1678 1678 -72.89672 3.185631 13.054669
## 1679 1679 -72.10230 2.730723 13.747856
## 1680 1680 -73.06537 2.985915 17.971073
## 1681 1681 -71.97581 1.965147 11.199406
## 1682 1682 -72.11561 4.674621 11.207152
## 1683 1683 -74.87390 3.090211 50.930828
## 1684 1684 -72.86787 4.155360 13.504461
## 1685 1685 -73.03208 3.134592 15.410975
## 1686 1686 -71.58082 4.466029 19.604757
## 1687 1687 -74.47447 2.779542 23.362219
## 1688 1688 -74.63868 3.866882 52.108089
## 1689 1689 -74.84506 3.360936 36.733414
## 1690 1690 -73.35163 3.491861 14.030415
## 1691 1691 -71.79829 2.586484 12.246421
## 1692 1692 -73.65120 2.739599 14.349851
## 1693 1693 -72.90560 4.665745 12.438827
## 1694 1694 -72.72807 4.636897 12.366897
## 1695 1695 -72.69479 4.747850 20.712175
## 1696 1696 -73.85092 2.511036 22.180946
## 1697 1697 -74.61871 4.204180 19.909134
## 1698 1698 -71.33450 1.942956 11.224239
## 1699 1699 -72.10230 2.005090 10.243495
## 1700 1700 -72.61712 1.916327 9.991824
## 1701 1701 -73.39379 2.681904 12.944840
## 1702 1702 -72.56386 1.805374 9.155994
## 1703 1703 -74.70082 4.841050 22.072960
## 1704 1704 -74.72079 2.928219 47.547020
## 1705 1705 -74.00625 2.255844 10.508078
## 1706 1706 -73.48477 4.798888 56.709179
## 1707 1707 -73.24511 3.875759 15.589735
## 1708 1708 -74.78292 2.273596 19.043163
## 1709 1709 -74.69194 2.231434 19.243237
## 1710 1710 -71.25018 3.318774 13.269437
## 1711 1711 -71.35669 4.215275 13.111211
## 1712 1712 -72.97661 1.874165 10.799370
## 1713 1713 -72.19994 1.665573 9.072062
## 1714 1714 -73.08756 2.739599 11.309499
## 1715 1715 -72.66594 3.207821 15.143399
## 1716 1716 -71.73171 2.133795 11.420588
## 1717 1717 -71.64517 4.448277 19.789900
## 1718 1718 -74.43009 4.224151 58.704296
## 1719 1719 -71.55197 4.501534 16.235548
## 1720 1720 -73.22514 2.970382 15.630555
## 1721 1721 -71.52978 4.459372 17.438519
## 1722 1722 -74.69638 4.676840 34.986813
## 1723 1723 -73.75550 4.461591 74.865013
## 1724 1724 -71.31009 3.809187 24.545137
## 1725 1725 -71.98247 4.592516 15.093578
## 1726 1726 -71.83823 4.710126 14.296528
## 1727 1727 -73.71777 2.082757 12.319357
## 1728 1728 -74.63868 3.234450 56.503281
## 1729 1729 -73.16079 2.777323 11.947110
## 1730 1730 -72.20215 4.372828 18.449453
## 1731 1731 -73.95078 3.940111 42.416389
## 1732 1732 -72.80574 3.460794 16.468321
## 1733 1733 -72.48176 2.346825 12.663782
## 1734 1734 -71.94696 3.691577 19.668119
## 1735 1735 -73.45371 3.562871 17.841686
## 1736 1736 -71.84932 3.815844 12.808943
## 1737 1737 -72.64375 4.723440 18.455252
## 1738 1738 -71.21023 3.955645 14.145196
## 1739 1739 -73.75994 4.104322 35.003933
## 1740 1740 -71.57194 2.329073 9.196219
## 1741 1741 -72.34417 1.900794 10.885989
## 1742 1742 -73.50918 3.458575 16.178099
## 1743 1743 -74.50332 2.866086 26.926868
## 1744 1744 -71.70509 3.085773 8.967725
## 1745 1745 -72.01353 3.258860 17.095650
## 1746 1746 -71.23464 4.827736 18.935200
## 1747 1747 -73.28506 4.659087 17.366705
## 1748 1748 -72.90782 3.028077 10.299122
## 1749 1749 -73.54469 2.440026 12.832067
## 1750 1750 -74.59208 1.572373 15.957654
## 1751 1751 -74.43009 4.028874 60.808376
## 1752 1752 -74.51220 1.734364 17.975328
## 1753 1753 -73.17410 3.360936 25.713457
## 1754 1754 -74.58099 3.005887 32.146629
## 1755 1755 -74.72523 2.546541 25.652323
## 1756 1756 -74.52773 4.572544 21.024523
## 1757 1757 -71.10150 3.496299 12.719352
## 1758 1758 -71.36557 4.738974 17.133537
## 1759 1759 -72.22213 2.582046 12.079788
## 1760 1760 -73.08312 1.612316 13.786138
## 1761 1761 -71.74059 2.333511 13.106888
## 1762 1762 -71.65627 2.539884 14.596324
## 1763 1763 -71.97359 3.214478 10.264338
## 1764 1764 -71.52978 3.909045 13.119211
## 1765 1765 -72.51282 3.895730 15.430334
## 1766 1766 -74.50110 4.190865 25.478979
## 1767 1767 -72.95220 2.056128 11.139996
## 1768 1768 -73.87977 2.326854 13.273615
## 1769 1769 -72.49507 4.264094 16.309992
## 1770 1770 -72.64819 2.657494 12.811031
## 1771 1771 -71.82048 2.932658 11.686326
## 1772 1772 -73.58019 4.168675 19.219511
## 1773 1773 -71.73615 3.267736 11.168964
## 1774 1774 -74.66309 3.021420 59.052574
## 1775 1775 -72.12449 4.699030 16.866695
## 1776 1776 -74.61871 1.585687 16.297626
## 1777 1777 -71.60301 1.825346 12.797262
## 1778 1778 -71.95362 2.613113 9.179770
## 1779 1779 -74.48779 2.049471 11.846092
## 1780 1780 -74.36796 4.255218 58.049801
## 1781 1781 -74.12386 1.592344 14.288239
## 1782 1782 -71.20136 3.198945 11.567268
## 1783 1783 -72.99436 4.652430 17.027889
## 1784 1784 -72.64597 3.864663 16.062559
## 1785 1785 -71.74947 3.471889 13.618755
## 1786 1786 -71.85376 1.998433 10.188046
## 1787 1787 -73.47368 2.142672 13.336649
## 1788 1788 -74.43231 2.548760 15.127444
## 1789 1789 -74.41900 2.058347 11.988623
## 1790 1790 -73.97962 2.886057 19.291136
## 1791 1791 -73.80654 2.673027 16.969584
## 1792 1792 -71.25462 3.352060 10.693420
## 1793 1793 -72.49063 4.226370 11.760996
## 1794 1794 -74.47225 4.548134 30.246290
## 1795 1795 -74.66087 1.741022 14.208759
## 1796 1796 -71.30565 1.989556 13.167849
## 1797 1797 -74.00847 2.892714 19.498194
## 1798 1798 -71.78941 1.860851 10.818524
## 1799 1799 -71.52756 3.241107 11.527934
## 1800 1800 -73.76216 3.172316 21.038546
## 1801 1801 -73.58685 3.170097 22.396526
## 1802 1802 -72.89006 3.782558 13.263363
## 1803 1803 -73.77547 3.345403 14.328484
## 1804 1804 -72.31089 4.614706 18.833750
## 1805 1805 -73.55578 3.944550 11.870148
## 1806 1806 -72.33308 4.501534 16.780340
## 1807 1807 -72.10895 4.206399 11.545960
## 1808 1808 -73.83538 4.738974 69.834625
## 1809 1809 -74.76295 4.579201 36.848026
## 1810 1810 -73.93746 4.019998 71.323845
## 1811 1811 -71.36113 1.716612 12.429375
## 1812 1812 -74.74964 2.657494 35.165928
## 1813 1813 -72.64375 3.536242 16.625677
## 1814 1814 -73.91527 2.715190 16.709208
## 1815 1815 -74.19709 2.837238 13.626547
## 1816 1816 -71.94252 3.420851 19.836628
## 1817 1817 -73.78656 4.843269 58.154076
## 1818 1818 -73.86201 2.187053 15.775246
## 1819 1819 -73.64011 3.795872 29.792086
## 1820 1820 -74.67419 2.180396 15.992970
## 1821 1821 -71.74725 3.966740 14.697520
## 1822 1822 -73.90196 1.871946 18.343090
## 1823 1823 -71.91368 3.403099 15.776126
## 1824 1824 -72.43294 2.659713 12.924703
## 1825 1825 -73.57132 3.840254 23.083189
## 1826 1826 -74.53217 3.651633 52.282345
## 1827 1827 -71.92477 3.977835 10.895131
## 1828 1828 -73.99516 3.434165 21.047016
## 1829 1829 -74.17268 3.984493 61.074612
## 1830 1830 -73.63123 1.729926 13.087823
## 1831 1831 -71.42548 4.330666 11.407921
## 1832 1832 -71.89592 3.143468 9.338528
## 1833 1833 -74.49445 1.661135 11.932673
## 1834 1834 -74.53217 3.638319 52.517929
## 1835 1835 -71.96693 2.380111 12.964470
## 1836 1836 -71.82935 2.808390 11.103954
## 1837 1837 -72.72585 3.411975 16.492626
## 1838 1838 -72.21325 3.662729 24.896544
## 1839 1839 -73.89086 3.201164 21.001865
## 1840 1840 -73.41154 2.788419 14.077147
## 1841 1841 -71.91146 4.821079 21.963840
## 1842 1842 -72.48841 4.559230 13.579518
## 1843 1843 -73.81763 4.694592 64.879990
## 1844 1844 -72.43738 4.572544 14.773277
## 1845 1845 -73.87533 1.869727 12.880237
## 1846 1846 -71.30787 2.229215 13.098261
## 1847 1847 -72.02463 3.895730 11.237541
## 1848 1848 -74.66975 4.654649 21.860413
## 1849 1849 -72.83681 4.381705 24.767971
## 1850 1850 -74.84506 4.217494 15.948186
## 1851 1851 -73.57353 3.656072 17.030317
## 1852 1852 -71.82713 4.477124 17.543833
## 1853 1853 -72.32198 3.010325 24.065102
## 1854 1854 -74.25479 3.516271 51.501034
## 1855 1855 -72.85456 2.286911 16.388763
## 1856 1856 -71.43880 3.139030 11.588144
## 1857 1857 -73.11863 2.051690 11.233335
## 1858 1858 -72.74804 2.992572 17.367653
## 1859 1859 -72.84568 2.175958 17.220476
## 1860 1860 -71.26127 2.590922 9.094190
## 1861 1861 -72.14224 4.841050 17.338461
## 1862 1862 -74.14161 1.641164 14.080678
## 1863 1863 -71.25905 1.863070 11.279452
## 1864 1864 -71.73171 1.869727 14.251741
## 1865 1865 -74.47447 2.195929 14.744287
## 1866 1866 -71.32784 2.717409 12.414330
## 1867 1867 -72.10895 3.465232 24.560631
## 1868 1868 -71.56085 4.497096 26.458254
## 1869 1869 -72.66150 1.692202 9.935849
## 1870 1870 -71.51646 4.550353 13.445147
## 1871 1871 -72.91447 4.512629 15.221107
## 1872 1872 -71.82713 4.013340 13.143682
## 1873 1873 -72.19106 2.735161 21.604622
## 1874 1874 -71.56972 3.374251 10.602596
## 1875 1875 -72.30423 1.920766 9.261039
## 1876 1876 -74.78070 2.641960 22.550619
## 1877 1877 -73.10753 2.029500 13.333582
## 1878 1878 -74.76517 2.468874 19.604694
## 1879 1879 -71.22577 2.555417 9.450292
## 1880 1880 -72.42184 3.480766 15.850276
## 1881 1881 -72.12005 4.292942 18.610176
## 1882 1882 -74.43675 4.468248 58.124477
## 1883 1883 -74.88500 1.610097 15.958184
## 1884 1884 -71.64739 3.130154 13.464158
## 1885 1885 -71.29678 1.887480 11.210527
## 1886 1886 -74.06617 2.104948 10.618467
## 1887 1887 -72.77245 2.730723 14.845860
## 1888 1888 -74.05507 4.124294 47.136639
## 1889 1889 -71.65848 4.694592 12.648518
## 1890 1890 -71.17917 2.781761 11.721109
## 1891 1891 -72.37524 4.532601 24.836445
## 1892 1892 -73.82651 4.346200 54.145126
## 1893 1893 -72.89450 3.944550 19.351156
## 1894 1894 -74.12164 2.699656 15.372428
## 1895 1895 -74.76961 3.849130 23.945494
## 1896 1896 -74.21928 3.380908 55.248310
## 1897 1897 -73.79766 3.684919 20.604292
## 1898 1898 -74.92938 2.346825 19.993374
## 1899 1899 -71.79829 3.245545 10.850687
## 1900 1900 -73.40267 4.545915 25.916990
## 1901 1901 -71.46765 3.731520 12.608622
## 1902 1902 -71.24796 1.674450 11.375448
## 1903 1903 -73.46258 4.064379 11.351521
## 1904 1904 -71.27903 2.335730 14.215415
## 1905 1905 -71.23908 4.352857 13.300705
## 1906 1906 -74.52107 2.402302 18.580097
## 1907 1907 -73.15191 3.940111 18.714811
## 1908 1908 -72.87231 4.670183 14.719774
## 1909 1909 -72.86787 3.660510 17.337627
## 1910 1910 -72.27760 3.742615 15.809905
## 1911 1911 -73.04984 4.463810 14.944636
## 1912 1912 -73.24289 4.694592 18.504526
## 1913 1913 -72.14668 4.332885 16.326406
## 1914 1914 -74.45228 4.581420 24.584879
## 1915 1915 -72.84124 2.302444 10.241172
## 1916 1916 -72.28870 3.196726 17.597120
## 1917 1917 -74.60096 4.297380 27.425880
## 1918 1918 -74.46338 3.105744 22.893799
## 1919 1919 -72.25097 2.315758 14.793596
## 1920 1920 -74.22372 1.594563 11.553076
## 1921 1921 -73.23402 1.951832 11.391229
## 1922 1922 -71.20802 3.172316 9.737391
## 1923 1923 -74.44341 4.732316 40.541870
## 1924 1924 -74.14161 3.982274 43.833336
## 1925 1925 -73.19629 3.418632 15.179044
## 1926 1926 -72.39299 3.380908 14.312943
## 1927 1927 -71.52090 4.166456 15.102504
## 1928 1928 -74.62981 4.448277 17.668100
## 1929 1929 -74.79180 2.402302 25.310387
## 1930 1930 -73.91971 2.542103 13.651091
## 1931 1931 -74.49666 4.228589 23.107948
## 1932 1932 -71.43214 3.968959 15.312312
## 1933 1933 -72.58161 2.482188 14.251781
## 1934 1934 -73.07203 2.448902 12.696348
## 1935 1935 -74.00403 3.758148 59.990269
## 1936 1936 -71.64073 2.224777 9.045694
## 1937 1937 -72.74361 2.781761 11.236289
## 1938 1938 -74.56324 2.657494 69.316780
## 1939 1939 -72.45513 2.919343 14.344971
## 1940 1940 -73.28949 2.786199 11.627152
## 1941 1941 -72.37968 3.638319 15.772854
## 1942 1942 -73.13638 4.838831 20.341915
## 1943 1943 -71.50759 3.440823 11.767985
## 1944 1944 -74.10389 3.298803 14.541970
## 1945 1945 -71.73393 3.933454 17.437393
## 1946 1946 -72.37080 1.820908 11.661358
## 1947 1947 -71.67624 4.175332 13.949284Por ultimo graficamos las muestras
m <- leaflet() %>%
addTiles() %>%
addMarkers(lng=sitios$longit,lat=sitios$latit, popup=sitios$soc, clusterOptions = markerClusterOptions())
m7. Guardar las muestras
La función sf::st_write() guarda los datos espaciales en diversos formatos. En este caso usamos GeoPackage (GPKG), que es:
- Un formato abierto y estándar
- Eficiente para datos vectoriales
- Compatible con múltiples software GIS
- Puede almacenar múltiples capas en un solo archivo
sf::st_write(nmuestras, "data/soc_meta.gpkg", driver = "GPKG",
append = FALSE)## Deleting layer `soc_meta' using driver `GPKG'
## Writing layer `soc_meta' to data source `data/soc_meta.gpkg' using driver `GPKG'
## Writing 1947 features with 1 fields and geometry type Point.¿Qué hace append = FALSE?
El parámetro append = FALSE indica que si el archivo ya existe, debe ser sobrescrito completamente. Si usáramos append = TRUE, se agregarían los datos al archivo existente sin eliminar el contenido previo. Usar FALSE asegura que siempre tenemos actualizados nuestros datos.
8. Referencia
Este trabajo se hizo en base de:
Lizarazo, I. 2025. How to download soil data from SoilGrids. Disponible en: https://rpubs.com/ials2un/downloadSoilGrids
Adaptación para el departamento de Meta:
- Autor: Nawel Sebastian Ballesteros Sierra
- Fecha: Noviembre 10, 2025
- Variables analizadas: Carbono Orgánico del Suelo (SOC), profundidad 15-30 cm
- Área de estudio: Departamento de Meta, Colombia
Fuente de datos:
- SoilGrids 250m v2.0. ISRIC - World Soil Information. https://www.isric.org/explore/soilgrids
Cita sugerida: Sierra Ballesteros, N.S. 2025. Análisis de carbono orgánico del suelo en el departamento de Meta usando datos de SoilGrids.
Información de la sesión de R (útil para reproducibilidad)
sessionInfo()## R version 4.5.1 (2025-06-13 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 26200)
##
## Matrix products: default
## LAPACK version 3.12.1
##
## locale:
## [1] LC_COLLATE=Spanish_Latin America.utf8
## [2] LC_CTYPE=Spanish_Latin America.utf8
## [3] LC_MONETARY=Spanish_Latin America.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=Spanish_Latin America.utf8
##
## time zone: America/Bogota
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] dplyr_1.1.4 XML_3.99-0.19 gdalUtilities_1.2.5
## [4] RColorBrewer_1.1-3 leaflet_2.2.3 sf_1.0-21
## [7] tidyterra_0.7.2 ggplot2_4.0.0 terra_1.8-80
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.10 generics_0.1.4 tidyr_1.3.1 class_7.3-23
## [5] KernSmooth_2.23-26 digest_0.6.37 magrittr_2.0.4 evaluate_1.0.5
## [9] grid_4.5.1 fastmap_1.2.0 jsonlite_2.0.0 e1071_1.7-16
## [13] DBI_1.2.3 purrr_1.2.0 crosstalk_1.2.2 scales_1.4.0
## [17] codetools_0.2-20 jquerylib_0.1.4 cli_3.6.5 rlang_1.1.6
## [21] units_1.0-0 withr_3.0.2 cachem_1.1.0 tools_4.5.1
## [25] vctrs_0.6.5 R6_2.6.1 png_0.1-8 proxy_0.4-27
## [29] lifecycle_1.0.4 classInt_0.4-11 htmlwidgets_1.6.4 pkgconfig_2.0.3
## [33] pillar_1.11.1 bslib_0.9.0 gtable_0.3.6 glue_1.8.0
## [37] data.table_1.17.8 Rcpp_1.1.0 xfun_0.54 tibble_3.3.0
## [41] tidyselect_1.2.1 rstudioapi_0.17.1 knitr_1.50 farver_2.1.2
## [45] htmltools_0.5.8.1 rmarkdown_2.30 labeling_0.4.3 compiler_4.5.1
## [49] S7_0.2.0