Structurally Guided Sampling
Overview
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.
fixed - Updated ggplot2 plot$labels field based. From teunbrand #36
fixed - Updated parameter filename for sample_nc() and others to correctly indicate the function outputs samples and not a raster layer. From StumWhere #36
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- WARNING12 OK, 1 WARNING2026-06-08
- OK14 OK2026-04-08
Show 2 earlier changesHide 2 earlier changes
- ERROR13 OK, 1 ERROR2026-04-07
- OK14 OK2026-03-10
Documentation
- Help pages
- 41 (17 internal)includes a package overview page
- Examples that run
- 79%19 run in a plain check · 5 never run
- Exported functions with examples
- 83%
- Documented parameters
- 96%
- Return-value docs
- 100%
- Help pages citing references
- 27%
- sgsR HTML
- Calculating HTML
- Sampling HTML
- Stratification HTML
Downloads
Repository
- PRs merged (all time)
- 93%
- Median days to close, 50 most recently updated closed issues
- 2
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Forks over time
Releases over time
Issues over time
PRs over time
9 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/tgoodbody/sgsr on 2026-10-11.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2025-06-18 · The repository has a site deploy workflow
Show all practicesHide 1 practice
Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 1.5.0Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.4.52024-03-03 · diff ↗
- 1.4.42023-06-13 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 1.4.22023-03-10 · diff ↗ ·
added 4 exports
allocate_existing_equal, allocate_existing_manual, allocate_existing_optim, allocate_existing_prop - 1.4.0
- 1.3.4
- 1.3.32023-01-17 · diff ↗
- 1.3.22022-11-19 · diff ↗
- 1.3.1
- 1.2.0
- 1.0.02022-06-24
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-06-24
- Total releases
- 11 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 4.5 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("sgsR")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.