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.

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

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

Automatic dendrometry in terrestrial point clouds

A library of tree segmentation and detection algorithms.

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

ws3: Wood Supply Simulation System

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.

`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

Automated tree detection in the urban environment with deep learning

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

Forestry Functions in Python

QGIS plugin FIM - Forest Inventory and Monitoring