A benchmark dataset for deep learning-based tree detection: VHRTrees

Diffusion-based Tree Skeletonization

WebGL point cloud viewer for large datasets

Individual-tree attribute scaling from airborne laser scanning point clouds

R Package for calculating individual Tree Competition

PyCrown - Fast raster-based individual tree segmentation for LiDAR data

Code repository for the paper Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks

Interactive Shiny Dashboard for monitoring multi-year Land Use / Land Cover (LULC) changes in Istanbul using spatial and statistical visualizations.

AI-Enhanced Toolset for 3D Tree Processing: A CloudCompare Plugin

A CloudCompare Python plugin for a suite of LiDAR processing modules targeting forest and tree analysis.

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

SfQSM is a three-dimensional tree modeling method based on skeleton graph optimization and fractal self-similarity.

A SAM-based model for instance segmentation of images of grains

rTLS: Tools to Process Point Clouds Derived from Terrestrial Laser Scanning

Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.

R code for compiling output tables from the Alberta Provincial Growth and Yield Initative database for use in growth and yield models

official source code for paper entitled "Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning"

R package for analysis and manipulation of tree structure models

!!! MY FORK !!! --- R functions for processing individual tree TLS point clouds from @tiagodc

Utilities to support landscape-, forest-, and tree-related data collection, manipulation, analysis, modelling, and visualization.

Label airborne LiDAR point clouds with TLS data to create benchmark in complex forest contexts

An R package for NASA’s GEDI Level 4A data download, processing and visualization.

R package for evaluating individual tree crown predictions against a diverse benchmark dataset

LIDAR and RGB Deep Learning Model for Individual Tree Segmentation

Utilities to support landscape-, forest-, and tree-related data collection, manipulation, analysis, modelling, and visualization.

R package aRchi. Tree architecture from terrestrial laser scanning (TLS) data