A curated list of open technology projects to sustain a stable climate, energy supply, biodiversity and natural resources.

FORTLS

Detect and segment individual tree from remotely sensed data.
https://github.com/molina-valero/fortls

Category: Biosphere
Sub Category: Forest Remote Sensing

Keywords

forest-inventory forest-monitoring lidar-point-cloud

Last synced: about 19 hours ago
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Repository metadata

Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes

README.Rmd

          
---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/"
)
```

# FORTLS 


![license](https://img.shields.io/badge/Licence-GPL--3-blue.svg)
[![CRAN Status](https://www.r-pkg.org/badges/version/FORTLS)](https://cran.r-project.org/package=FORTLS){.FORTLS-release}
[![DOI](https://zenodo.org/badge/DOI/10.3390/IECF2020-08066.svg)](https://doi.org/10.1016/j.envsoft.2022.105337)


## Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes
Process 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. (2022, ).

# Install `FORTLS 1.2.0` (Beta version)

Get the latest released version of FORTLS from GitHub (included in the devel branch)

```r
remotes::install_github("Molina-Valero/FORTLS", ref = "devel", dependencies = TRUE)
```


# Acknowledgements 

**FORTLS** it is being developed at [University of Santiago de Compostela](https://www.usc.gal/en).

Development of the `FORTLS` package is being possible thanks to the following projects:

* Modelling the effects of intensity of perturbation on the structure of natural forests and their carbon stocks by using data from the National Forestry Inventory (AL2016-76769-C2-2-R) supported by the Spanish Ministry of Science and Innovation.
* Development of the Galician continuous forest inventory (2020-CP031) supported by the Regional Government of Galicia.
* Design of forest monitoring systems on a regional scale (ED431F 2020/02) supported by the Regional Government of Galicia.


        

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Last synced: 7 days ago

Total Commits: 653
Total Committers: 6
Avg Commits per committer: 108.833
Development Distribution Score (DDS): 0.277

Commits in past year: 112
Committers in past year: 1
Avg Commits per committer in past year: 112.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Juan Alberto Molina-Valero 5****o 472
Molina-Valero j****o@u****s 141
Adela Martínez-Calvo 7****o 21
anikaseppelt a****t@i****m 17
olivroy 5****y 1
Dirk Eddelbuettel e****d@d****g 1

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Total issues: 10
Total pull requests: 9
Average time to close issues: 3 months
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Average comments per issue: 4.5
Average comments per pull request: 0.33
Merged pull request: 7
Bot issues: 0
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Past year issues: 0
Past year pull requests: 1
Past year average time to close issues: N/A
Past year average time to close pull requests: less than a minute
Past year issue authors: 0
Past year pull request authors: 1
Past year average comments per issue: 0
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Past year merged pull request: 1
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Package metadata

cran.r-project.org: FORTLS

Automatic Processing of Terrestrial-Based Technologies Point Cloud Data for Forestry Purposes

  • Homepage: https://molina-valero.github.io/FORTLS/
  • Documentation: http://cran.r-project.org/web/packages/FORTLS/FORTLS.pdf
  • Licenses: GPL-3
  • Latest release: 1.5.0 (published about 1 month ago)
  • Last Synced: 2025-04-26T14:02:21.118Z (2 days ago)
  • Versions: 12
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 411 Last month
  • Rankings:
    • Forks count: 11.273%
    • Stargazers count: 15.6%
    • Average: 24.119%
    • Downloads: 28.47%
    • Dependent packages count: 29.797%
    • Dependent repos count: 35.455%
  • Maintainers (1)

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • Distance * imports
  • Rcpp >= 1.0.5 imports
  • dbscan * imports
  • ggvoronoi * imports
  • htmlwidgets * imports
  • lidR * imports
  • plotly * imports
  • progress * imports
  • raster * imports
  • scales * imports
  • sp * imports
  • tidyr * imports
  • vroom * imports
  • testthat * suggests

Score: 10.990836648925526