CRAN/E | sgsR

sgsR

Structurally Guided Sampling

Installation

About

Structurally guided sampling (SGS) approaches for airborne laser scanning (ALS; LIDAR). Primary functions provide means to generate data-driven stratifications & methods for allocating samples. Intermediate functions for calculating and extracting important information about input covariates and samples are also included. Processing outcomes are intended to help forest and environmental management practitioners better optimize field sample placement as well as assess and augment existing sample networks in the context of data distributions and conditions. ALS data is the primary intended use case, however any rasterized remote sensing data can be used, enabling data-driven stratifications and sampling approaches.

Citation sgsR citation info
github.com/tgoodbody/sgsR
tgoodbody.github.io/sgsR/
Bug report File report

Key Metrics

Version 1.4.5
R ≥ 3.5.0
Published 2024-03-03 26 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks sgsR results
Language en-US

Downloads

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Maintainer

Maintainer

Tristan RH Goodbody

goodbody.t@gmail.com

Authors

Tristan RH Goodbody

aut / cre / cph

Nicholas C Coops

aut

Martin Queinnec

aut

Material

README
NEWS
Reference manual
Package source

Vignettes

Calculating
Sampling
sgsR
Stratification

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

sgsR archive

Depends

R ≥ 3.5.0
methods

Imports

dplyr
ggplot2
sf
terra
tidyr
clhs
SamplingBigData
BalancedSampling
spatstat.geom

Suggests

knitr
rmarkdown
Rfast
testthat ≥ 3.0.0
doParallel
doSNOW
snow
foreach
entropy
roxygen2
covr
RANN
spelling