Tools for analyzing aerial point clouds of forest data.
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Updated
Dec 28, 2019 - Python
Tools for analyzing aerial point clouds of forest data.
Implementation of Grondin et al. 2022 "Tree Detection and Diameter Estimation Based on Deep Learning". Also includes datasets and some of the pretrained models.
A library of tree segmentation and detection algorithms.
Tools to calculate growth statistics for individual urban trees such as for estimating carbon storage.
Automatic dendrometry in terrestrial point clouds
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.
The Simple Biomass Comparison Model
ws3: Wood Supply Simulation System
Python-based implementation of the EWMACD/EDYN vegetation change detection algorithm.
Ignition pattern simulator for prescribed fire
`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
Codes and data for a published work "Improve the deep learning models in forestry based on explanations and expertise" (https://doi.org/10.3389/fpls.2022.902105)
Fine-tune and evaluate deep learning models built with PyTorch for semantic segmentation of trees from satellite imagery of forestry areas.
QGIS plugin FIM - Forest Inventory and Monitoring
A multi-objective approach to optimizing forwarder routing in cut-to-length forest harvesting operations. Distributed under the terms of the GNU Lesser General Public License version 3.0 or any later version.
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