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Remote Sensing","monthly_downloads":593,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"\n---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, echo = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/\"\n)\n```\n\n# FORTLS \u003cimg src=\"man/figures/logo.png\" align=\"right\" alt=\"\" width=\"250\" /\u003e\n\n\u003c!-- badges: start --\u003e\n![license](https://img.shields.io/badge/Licence-GPL--3-blue.svg)\n[![CRAN Status](https://www.r-pkg.org/badges/version/FORTLS)](https://cran.r-project.org/package=FORTLS){.FORTLS-release}\n[![DOI](https://zenodo.org/badge/DOI/10.3390/IECF2020-08066.svg)](https://doi.org/10.1016/j.envsoft.2022.105337)\n\u003c!-- badges: end --\u003e\n\n## Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes\nProcess automation of point cloud data derived from terrestrial-based technologies such as Terrestrial Laser Scanner (TLS) or Simultaneous Localization and Mapping (SLAM). 'FORTLS' enables (i) detection of trees and estimation of tree-level attributes (e.g. diameters and heights), (ii) estimation of stand-level variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories (FIs) at stand-level, and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. 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