Removes or flags records within a radius around the geographic centroids of political countries and provinces. Poorly geo-referenced occurrence records in biological databases are often erroneously geo-referenced to centroids.
cc_cen(
x,
lon = "decimalLongitude",
lat = "decimalLatitude",
species = "species",
buffer = 1000,
geod = TRUE,
test = "both",
ref = NULL,
verify = FALSE,
value = "clean",
verbose = TRUE
)data.frame. Containing geographical coordinates and species names.
character string. The column with the longitude coordinates. Default = “decimalLongitude”.
character string. The column with the latitude coordinates. Default = “decimalLatitude”.
character string. The column with the species identity. Only required if verify = TRUE.
numerical. The buffer around each province or country centroid, where records should be flagged as problematic. Units depend on geod. Default = 1 kilometre.
logical. If TRUE the radius around each capital is calculated based on a sphere, buffer is in meters and independent of latitude. If FALSE the radius is calculated assuming planar coordinates and varies slightly with latitude. Default = TRUE. See https://seethedatablog.wordpress.com/ for detail and credits.
a character string. Specifying the details of the test. One of c(“both”, “country”, “provinces”). If both tests for country and province centroids.
SpatVector (geometry: polygons). Providing the geographic
gazetteer. Can be any SpatVector (geometry: polygons), but the structure
must be identical to countryref. Default =
countryref.
logical. If TRUE records are only flagged if they are the only record in a given species flagged close to a given reference. If FALSE, the distance is the only criterion
character string. Defining the output value. See value.
logical. If TRUE reports the name of the test and the number of records flagged.
Depending on the ‘value’ argument, either a data.frame
containing the records considered correct by the test (“clean”) or a logical vector (“flagged”), with TRUE = test passed and FALSE = test failed/potentially problematic . Default = “clean”.
See https://ropensci.github.io/CoordinateCleaner/ for more details and tutorials.
x <- data.frame(species = letters[1:10],
decimalLongitude = c(runif(99, -180, 180), -47.92),
decimalLatitude = c(runif(99, -90,90), -15.78))
cc_cen(x, geod = FALSE)
#> Testing country centroids
#> Removed 0 records.
#> species decimalLongitude decimalLatitude
#> 1 a -80.117973 84.73346278
#> 2 b -150.314870 -4.96314263
#> 3 c 114.164298 -9.75687656
#> 4 d -179.501954 -34.32877343
#> 5 e 100.880128 87.69825437
#> 6 f 97.653524 -31.08186764
#> 7 g 128.583223 -6.15427041
#> 8 h -73.025403 -48.01443740
#> 9 i -57.643663 -87.11257262
#> 10 j 160.709490 11.13592226
#> 11 a -21.526743 73.09101444
#> 12 b -106.848146 -80.31919001
#> 13 c 24.294796 -82.62730182
#> 14 d -170.466418 -5.04496987
#> 15 e 44.695590 37.18092000
#> 16 f 141.397599 -17.30995644
#> 17 g -155.490826 26.40372074
#> 18 h -107.814463 4.59085596
#> 19 i -26.100594 -52.48535566
#> 20 j 169.709933 -70.70254130
#> 21 a -168.139657 37.44108883
#> 22 b 76.581345 31.51530876
#> 23 c 7.764866 -80.78003534
#> 24 d 86.649973 32.90821271
#> 25 e 62.707324 80.42738705
#> 26 f 50.874331 39.03524831
#> 27 g -151.298703 19.89860498
#> 28 h 135.906451 61.30135022
#> 29 i 132.512965 -12.80095002
#> 30 j 167.434586 76.76003720
#> 31 a -98.363469 -22.62017336
#> 32 b -107.398760 -25.52855516
#> 33 c 6.885513 -57.87162099
#> 34 d -177.170159 -11.47118174
#> 35 e -150.857791 33.49739152
#> 36 f -36.519207 -4.22892299
#> 37 g 126.549355 -53.96362037
#> 38 h -68.119510 21.01818438
#> 39 i -37.123970 -89.34731633
#> 40 j -91.204867 82.79178652
#> 41 a -153.831221 17.02384563
#> 42 b -120.950591 -36.02571492
#> 43 c -142.509162 34.38694493
#> 44 d 132.141901 -85.23362737
#> 45 e 112.841568 78.41850901
#> 46 f -157.678945 -13.67248292
#> 47 g 86.245317 -0.19446070
#> 48 h 35.658711 -3.86531645
#> 49 i 88.153584 -19.67081947
#> 50 j -177.490025 31.27194636
#> 51 a -108.693367 -14.41911230
#> 52 b 164.451001 -63.79531573
#> 53 c -113.357662 20.21660466
#> 54 d -29.871296 -22.67649744
#> 55 e -108.431172 70.06840083
#> 56 f 171.152162 4.83691917
#> 57 g 28.443290 -10.95948487
#> 58 h -147.960564 -71.57354346
#> 59 i -107.091535 79.95430975
#> 60 j -36.395100 26.56643552
#> 61 a -41.164075 48.20956907
#> 62 b -179.801978 -21.46838197
#> 63 c -92.028851 54.57875215
#> 64 d 176.201852 63.85686748
#> 65 e -116.814253 8.35694329
#> 66 f -147.116536 0.63303293
#> 67 g -1.393278 88.78517716
#> 68 h 145.147163 22.10401618
#> 69 i -54.926877 -15.33905384
#> 70 j -149.956991 -75.43789620
#> 71 a -108.384318 -28.40116376
#> 72 b 178.412941 53.10053639
#> 73 c 178.411017 -80.40162661
#> 74 d 103.278296 -19.96637229
#> 75 e -20.953208 -1.68670538
#> 76 f 40.383791 73.69891264
#> 77 g -170.101908 -16.41104951
#> 78 h -5.078075 -0.07514565
#> 79 i -8.359452 -41.37990199
#> 80 j -61.785090 -9.58382123
#> 81 a 48.752210 -74.84960445
#> 82 b -51.982581 62.52990307
#> 83 c 77.737603 22.25423091
#> 84 d -87.433279 -4.38172647
#> 85 e -162.894112 77.88373404
#> 86 f 73.267237 -60.24757274
#> 87 g 24.558292 76.52620800
#> 88 h 119.963393 69.76859688
#> 89 i -110.345063 -61.32852158
#> 90 j 74.815371 62.27256523
#> 91 a -87.026155 7.89889194
#> 92 b 104.278707 9.00750533
#> 93 c 8.051585 -29.77534766
#> 94 d -139.279972 66.84292224
#> 95 e -49.402088 81.41322752
#> 96 f 115.020627 7.51022694
#> 97 g -78.040879 -64.33531506
#> 98 h -43.440122 -63.92073804
#> 99 i -64.159266 -6.76189046
#> 100 j -47.920000 -15.78000000
if (FALSE) {
cc_inst(x, value = "flagged", buffer = 50000) #geod = T
}