Package: GeoThinneR 2.1.1

Jorge Mestre-Tomás

GeoThinneR: Efficient Spatial Thinning of Species Occurrences

Provides efficient geospatial thinning algorithms to reduce the density of coordinate data while maintaining spatial relationships. Implements K-D Tree and brute-force distance-based thinning, as well as grid-based and precision-based thinning methods. For more information on the methods, see Elseberg et al. (2012) <https://hdl.handle.net/10446/86202>.

Authors:Jorge Mestre-Tomás [aut, cre]

GeoThinneR_2.1.1.tar.gz
GeoThinneR_2.1.1.zip(r-4.7)GeoThinneR_2.1.1.zip(r-4.6)GeoThinneR_2.1.1.zip(r-4.5)
GeoThinneR_2.1.1.tgz(r-4.6-any)GeoThinneR_2.1.1.tgz(r-4.5-any)
GeoThinneR_2.1.1.tar.gz(r-4.7-any)GeoThinneR_2.1.1.tar.gz(r-4.6-any)
GeoThinneR_2.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GeoThinneR/json (API)
NEWS

# Install 'GeoThinneR' in R:
install.packages('GeoThinneR', repos = c('https://jmestret.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jmestret/geothinner/issues

Pkgdown/docs site:https://jmestret.github.io

Datasets:
  • caretta - Loggerhead Sea Turtle (_Caretta caretta_) Occurrence Records in the Mediterranean Sea
  • thunnus - Yellowfin Tuna (_Thunnus albacares_) Worldwide Occurrence Records

On CRAN:

Conda:

6.20 score 10 stars 1 packages 15 scripts 379 downloads 20 exports 28 dependencies

Last updated from:df7df872ad. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK206
source / vignettesOK239
linux-release-x86_64OK169
macos-release-arm64OK153
macos-oldrel-arm64OK400
windows-develOK113
windows-releaseOK695
windows-oldrelOK191
wasm-releaseOK145

Exports:as_GeoThinnedas_sfcalculate_spatial_coveragecompute_nearest_neighbor_distancescompute_neighbors_brutecompute_neighbors_kdtreecompute_neighbors_local_kdtreedistance_thinningestimate_k_maxget_trialgrid_thinningis_lonlatlargestlargest_indexlon_lat_to_cartesianmax_thinning_algorithmnew_GeoThinnedprecision_thinningselect_target_pointsthin_points

Dependencies:BHclassclassIntcodetoolsdata.tableDBIdoParalleldotCall64e1071fieldsforeachiteratorsKernSmoothmapsMASSmatrixStatsnaborproxyRColorBrewerRcppRcppEigens2sfspamterraunitsviridisLitewk

Getting started with GeoThinneR

Rendered fromGeoThinneR.Rmdusingknitr::rmarkdownon May 08 2026.

Last update: 2025-11-24
Started: 2024-08-20

Readme and manuals

Help Manual

Help pageTopics
GeoThinned Object Constructor and Methodsas_GeoThinned as_sf as_sf.GeoThinned get_trial get_trial.GeoThinned largest largest.GeoThinned largest_index largest_index.GeoThinned new_GeoThinned plot.GeoThinned print.GeoThinned print.summary.GeoThinned summary.GeoThinned
Calculate Spatial Coverage (Convex Hull Area)calculate_spatial_coverage
Loggerhead Sea Turtle (_Caretta caretta_) Occurrence Records in the Mediterranean Seacaretta
Compute Nearest Neighbor Distancescompute_nearest_neighbor_distances
Compute Neighbors Using Brute-Forcecompute_neighbors_brute
Compute Neighbors Using kd-Treecompute_neighbors_kdtree
Compute Neighbors Using Local kd-Treescompute_neighbors_local_kdtree
Perform Distance-Based Thinningdistance_thinning
Estimate Maximum Neighbors for kd-Tree Thinningestimate_k_max
Perform Grid-Based Thinning of Spatial Pointsgrid_thinning
Check for Longitude/Latitude Coordinatesis_lonlat
Convert Geographic Coordinates to Cartesian Coordinateslon_lat_to_cartesian
Thinning Algorithm for Spatial Datamax_thinning_algorithm
Precision Thinning of Spatial Pointsprecision_thinning
Select Target Number of Points for Spatial Thinningselect_target_points
Spatial Thinning of Pointsthin_points
Yellowfin Tuna (_Thunnus albacares_) Worldwide Occurrence Recordsthunnus