sgsR - structurally guided sampling

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sgsR is designed to implement structurally guided sampling approaches for enhanced forest inventories. The package was designed to function using rasterized airborne laser scanning (ALS; Lidar) metrics to allow for stratification of forested areas based on structure.

If you aren’t working with ALS data, any remote sensing data sets in a raster format (e.g. optical satellite imagery, climate data, drone-based products) can be used as inputs to help guide your environmental sampling needs.

sgsR is being actively developed, so you may encounter bugs. If that happens, please report your issue here by providing a reproducible example.

Installation :computer:

Install the stable version of sgsRfrom CRAN with:


Install the most recent development version of sgsR from Github with:


Example usage :bar_chart:

#--- Load mraster files ---#
r <- system.file("extdata", "mraster.tif", package = "sgsR")

#--- load the mraster using the terra package ---#
mraster <- terra::rast(r)

#--- apply quantiles algorithm to mraster ---#
sraster <- strat_quantiles(mraster = mraster$zq90, # use mraster as input for stratification
                           nStrata = 4) # produce 4 strata
#--- apply stratified sampling ---#
existing <- sample_strat(sraster = sraster, # use sraster as input for sampling
                         nSamp = 200, # request 200 samples
                         mindist = 100, # samples must be 100 m apart
                         plot = TRUE) # plot output

Resources & Vignettes :books:

Check out the package documentation to see how you can use sgsR functions for your work.

sgsR was presented at the ForestSAT 2022 Conference in Berlin. Slides for the presentation can be found here.

Collaborators :woman: :man:

We are thankful for continued collaboration with academic, private industry, and government institutions to help improve sgsR. Special thanks to to:

Collaborator Affiliation
Martin Queinnec University of British Columbia
Joanne C. White Canadian Forest Service
Piotr Tompalski Canadian Forest Service
Andrew T. Hudak United States Forest Service
Ruben Valbuena Swedish University of Agricultural Sciences
Antoine LeBoeuf Ministère des Forêts, de la Faune et des Parcs
Ian Sinclair Ministry of Northern Development, Mines, Natural Resources and Forestry
Grant McCartney Forsite Consultants Ltd.
Jean-Francois Prieur Université de Sherbrooke
Murray Woods (Retired) Ministry of Northern Development, Mines, Natural Resources and Forestry

Funding :raised_hands:

Development of sgsR was made possible thanks to the financial support of the Canadian Wood Fibre Centre’s Forest Innovation Program.