Using Citizen Science Data as Pre-Training for Semantic Segmentation of High-Resolution UAV Images for Natural Forests Post-Disturbance Assessment
Kamyar Nasiri, William Guimont-Martin, Damien LaRocque, Gabriel Jeanson, Hugo Bellemare-Vallières, Vincent Grondin, Philippe Bournival, Julie Lessard, Guillaume Drolet, Jean-Daniel Sylvain and Philippe Giguère
Paper: https://www.mdpi.com/1999-4907/16/4/616

This repo contains the source code and the datasets used in our paper Using Citizen Science Data as Pre-Training for Semantic Segmentation of High-Resolution UAV Images for Natural Forests Post-Disturbance Assessment, published in the Classification of Forest Tree Species Using Remote Sensing Technologies: Latest Advances and Improvements special issue of the Forests MDPI journal.

The repository is composed of two main directories:

• lowAltitude_classification contains the code for the image classifier $C_{\text{DINOv2}}$
• lowAltitude_segmentation contains the code for the segmentation model $S_{\text{M2F}}$

To ease the installation of the dependencies and the training of the models, we provide two Dockerfiles, DockerfileClassif and DockerfileSeg, respectively, for the image classifier and the segmentation model. We provide make commands to build the containers.

With docker:

make cls-build # Image classifier
make seg-build # Segmentation model

With podman:

make cls-podbuild # Image classifier
make seg-podbuild # Segmentation model

This project is maintained with pre-commit. To setup pre-commit, follow these commands.

pip install pre-commit
pre-commit install

If you use the code or data in an academic context, please cite the following work:

@article{Nasiri2025,
  title     = {{Using Citizen Science Data as Pre-Training for Semantic Segmentation of High-Resolution UAV Images for Natural Forests Post-Disturbance Assessment}},
  volume    = {16},
  issn      = {1999-4907},
  url       = {http://dx.doi.org/10.3390/f16040616},
  doi       = {10.3390/f16040616},
  number    = {4},
  journal   = {Forests},
  publisher = {MDPI AG},
  author    = {Nasiri,  Kamyar and Guimont-Martin,  William and LaRocque,  Damien and Jeanson,  Gabriel and Bellemare-Vallières,  Hugo and Grondin,  Vincent and Bournival,  Philippe and Lessard,  Julie and Drolet,  Guillaume and Sylvain,  Jean-Daniel and Giguère,  Philippe},
  year      = {2025},
  month     = mar,
  pages     = {616}
}