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Remote Sensing","monthly_downloads":265,"total_dependent_repos":1,"total_dependent_packages":0,"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/\"\n)\n```\n\n# sgsR - structurally guided sampling \u003cimg src=\"man/figures/logo.png\" align=\"right\" width=\"200\" /\u003e\n\n\u003c!-- badges: start --\u003e\n![license](https://img.shields.io/badge/Licence-GPL--3-blue.svg)\n[![R-CMD-check](https://github.com/tgoodbody/sgsR/workflows/R-CMD-check/badge.svg)](https://github.com/tgoodbody/sgsR/actions)\n[![Codecov test coverage](https://codecov.io/gh/tgoodbody/sgsR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/tgoodbody/sgsR?branch=main)\n[![](https://cranlogs.r-pkg.org/badges/sgsR)](https://CRAN.R-project.org/package=sgsR)\n\u003c!-- badges: end --\u003e\n\n## Installation :computer: {.unnumbered}\n\nInstall the stable version of [`sgsR`from CRAN](https://cran.r-project.org/package=sgsR) with:\n\n``` r\ninstall.packages(\"sgsR\")\nlibrary(sgsR)\n```\n\nInstall the most recent development version of [`sgsR` from Github](https://github.com/tgoodbody/sgsR) with:\n\n``` r\ninstall.packages(\"devtools\")\ndevtools::install_github(\"https://github.com/tgoodbody/sgsR\")\nlibrary(sgsR)\n```\n## Citing `sgsR` in literature\n\nOpen access publication: [sgsR: a structurally guided sampling toolbox for LiDAR-based forest inventories](https://doi.org/10.1093/forestry/cpac055)\n\nTo cite `sgsR` use `citation()` from within R with:\n\n```{r}\nprint(citation(\"sgsR\"), bibtex = TRUE)\n```\n\n## Overview\n\n`sgsR` provides a collection of stratification and sampling algorithms that use auxiliary information for allocating sample units over an areal sampling frame. ALS metrics, like those derived from the [`lidR` package](https://cran.r-project.org/package=lidR) are the intended inputs.\n\nOther remotely sensed or auxiliary data can also be used (e.g. optical satellite imagery, climate data, drone-based products).\n\n`sgsR` is being actively developed, so you may encounter bugs. If that happens, [please report your issue here](https://github.com/tgoodbody/sgsR/issues) by providing a reproducible example.\n\n## Example usage :bar_chart: {.unnumbered}\n\n``` r\n#--- Load mraster files ---#\nr \u003c- system.file(\"extdata\", \"mraster.tif\", package = \"sgsR\")\n\n#--- load the mraster using the terra package ---#\nmraster \u003c- terra::rast(r)\n\n#--- apply quantiles algorithm to mraster ---#\nsraster \u003c- strat_quantiles(mraster = mraster$zq90, # use mraster as input for stratification\n                           nStrata = 4) # produce 4 strata\n                        \n#--- apply stratified sampling ---#\nexisting \u003c- sample_strat(sraster = sraster, # use sraster as input for sampling\n                         nSamp = 200, # request 200 samples\n                         mindist = 100, # samples must be 100 m apart\n                         plot = TRUE) # plot output\n\n```\n\n## Resources \u0026 Vignettes :books: {.unnumbered}\n\nCheck out [the package documentation](https://tgoodbody.github.io/sgsR/index.html) to see how you can use `sgsR` functions for your work.\n\n`sgsR` was presented at the ForestSAT 2022 Conference in Berlin. [Slides for the presentation can be found here.](https://tgoodbody.github.io/sgsR-ForestSAT2022/)\n\n## Collaborators :woman: :man: {.unnumbered} \n\nWe are thankful for continued collaboration with academic, private industry, and government institutions to help improve `sgsR`. Special thanks to to:\n\n```{r,echo=FALSE, results = 'asis'}\nlibrary(knitr)\nnames \u003c- c(\"Martin Queinnec\", \"Joanne C. White\", \"Piotr Tompalski\", \"Andrew T. Hudak\", \"Ruben Valbuena\", \"Antoine LeBoeuf\", \"Ian Sinclair\", \"Grant McCartney\", \"Jean-Francois Prieur\", \"Murray Woods\")\n\naff \u003c- c(\"University of British Columbia\", \"Canadian Forest Service\", \"Canadian Forest Service\", \"United States Forest Service\", \"Swedish University of Agricultural Sciences\", \"Ministère des Forêts, de la Faune et des Parcs\", \"Ministry of Northern Development, Mines, Natural Resources and Forestry\", \"Forsite Consultants Ltd.\", \"Université de Sherbrooke\", \" (Retired)\tMinistry of Northern Development, Mines, Natural Resources and Forestry\")\n\ndf \u003c- data.frame(Collaborator = names, Affiliation = aff)\n\nkable(df)\n```\n\n\n## Funding :raised_hands: {.unnumbered}\nDevelopment of `sgsR` was made possible thanks to the financial support of the Canadian Wood Fibre Centre's Forest Innovation Program.\n\n","funding_links":[],"readme_doi_urls":["https://doi.org/10.1093/forestry/cpac055"],"works":{"https://doi.org/10.1093/forestry/cpac055":{"id":"https://openalex.org/W4319453991","doi":"https://doi.org/10.1093/forestry/cpac055","title":"\u003ci\u003esgsR\u003c/i\u003e: a structurally guided sampling toolbox for LiDAR-based forest inventories","display_name":"\u003ci\u003esgsR\u003c/i\u003e: a structurally guided sampling toolbox for LiDAR-based forest inventories","publication_year":2023,"publication_date":"2023-02-06","ids":{"openalex":"https://openalex.org/W4319453991","doi":"https://doi.org/10.1093/forestry/cpac055"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1093/forestry/cpac055","pdf_url":"https://academic.oup.com/forestry/advance-article-pdf/doi/10.1093/forestry/cpac055/49098158/cpac055.pdf","source":{"id":"https://openalex.org/S152552278","display_name":"Forestry: An International Journal of Forest Research","issn_l":"0015-752X","issn":["1464-3626","0015-752X"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311647","https://openalex.org/P4310311648"],"host_organization_lineage_names":["University of Oxford","Oxford University Press"],"type":"journal"},"license":"cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://academic.oup.com/forestry/advance-article-pdf/doi/10.1093/forestry/cpac055/49098158/cpac055.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049217919","display_name":"Tristan R.H. 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