Implementation of Grondin et al. 2022 "Tree Detection and Diameter Estimation Based on Deep Learning". Also includes datasets and some of the pretrained models.

Tools for analyzing aerial point clouds of forest data.

Plugin generates heights raster maps from LiDAR classified point clouds (las and laz formats)

[WACV 2025] TimberVision dataset and framework for tree-trunk detection and tracking

A library of tree segmentation and detection algorithms.

Automatic dendrometry in terrestrial point clouds

Tools to calculate growth statistics for individual urban trees such as for estimating carbon storage.

Object-Oriented distance-independent Individual Tree Simulator (TreeSim)

A collection of modules to programmatically search for/download imagery from live cam feeds across the state of California.

Ignition pattern simulator for prescribed fire

The Simple Biomass Comparison Model

Python-based implementation of the EWMACD/EDYN vegetation change detection algorithm.

Fine-tune and evaluate deep learning models built with PyTorch for semantic segmentation of trees from satellite imagery of forestry areas.

QGIS processing chain that converts forest DSM images to tree crown polygons

ws3: Wood Supply Simulation System

`libcbm_runner` is a python package for automating simulations of forest growth and harvesting involving the European economy, carbon budgets and their interactions.

A Discord bot for practicing tree identification

Code for "Deep Learning for Detecting Trees in the Urban Environment from Lidar"

Forestry Functions in Python

QGIS plugin FIM - Forest Inventory and Monitoring