Skip to content
GitLab
    • Explore Projects Groups Topics Snippets
Projects Groups Topics Snippets
  • /
  • Help
    • Help
    • Support
    • Community forum
    • Submit feedback
    • Contribute to GitLab
  • Register
  • Sign in
  • L lidaRtRee_tutorials
  • Project information
    • Project information
    • Activity
    • Labels
    • Members
  • Repository
    • Repository
    • Files
    • Commits
    • Branches
    • Tags
    • Contributor statistics
    • Graph
    • Compare revisions
  • Issues 0
    • Issues 0
    • List
    • Boards
    • Service Desk
    • Milestones
  • Deployments
    • Deployments
    • Releases
  • Packages and registries
    • Packages and registries
    • Package Registry
    • Terraform modules
  • Monitor
    • Monitor
    • Incidents
  • Analytics
    • Analytics
    • Value stream
    • Repository
  • Wiki
    • Wiki
  • Activity
  • Graph
  • Create a new issue
  • Commits
  • Issue Boards
Collapse sidebar

En prévision de l'arrivée de la forge institutionnelle INRAE, nous vous invitons à créer vos nouveaux projets sur la forge MIA.

  • Monnet Jean-Matthieu
  • lidaRtRee_tutorials
  • Wiki
  • Forest structure metrics mapping
"js/git@gitlab-ssh.irstea.fr:reversaal/OhmPi.git" did not exist on "76e3092e36bb5fc9532bc6eab7bd5498c1fcdcd6"
Last edited by Monnet Jean-Matthieu 1 year ago
Page history

Forest structure metrics mapping

This workflow is now on https://lidar.pages.mia.inra.fr/lidaRtRee/articles/forest.structure.metrics.html

This R tutorial presents a workflow to compute both object-oriented and pixel-based metrics to describe the forest structure from Airborne Laser Scanning (lidar remote sensing) data. Extraction of different types of metrics is exemplified and code for parallelized processing of several ALS data files is provided.

Change log

  • Dec 21, 2023: moved to https://forgemia.inra.fr/lidar/lidaRtRee
  • April 6, 2023: checked with new version of lidaRtRee
  • July 19, 2022: checked with new version of lidaRtRee
  • May 24, 2022: switch to terra and sf to comply with new version of lidR and lidaRtRee
  • Dec. 27, 2021: future.apply package used for parallelization
  • Aug 3, 2021: updated to comply with lidaRtRee 3.1.0
  • Jan 2021: updated to comply with lidR 3.1.0 and lidaRtRee 3.0.0
  • Oct, 2020: checked compatibility with lidR 3.0.3
  • May, 2020: added edge metrics, gaps computed using option gapReconstruct=TRUE, output resolution changed to 10 m for better consistency of tree metrics
  • July, 2019: use of doFuture package instead of doParallel for parallelization; tested with lidR 2.1.0
  • Feb, 2019: updated for compatibility with package lidR 2.0.0 and lidaRtRee 2.0.0
  • July, 2018: initial version
Clone repository
  • ABA data preparation
  • ABA mapping and inference
  • ABA model calibration
  • ALS data preprocessing
  • Area based approach
  • Field plot coregistration with ALS data
  • Forest gaps and edges detection
  • Forest structure metrics mapping
  • Tree segmentation
  • Home

Menu

Explore Projects Groups Topics Snippets