Prono et al. (2026) FOREST-GC: A conFOrmable Rendering Engine for Synthetic Tree Generation and Counting

Identification

• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Luciano Prono, Najmeddine Dhieb, Philippe Bich, Chiara Boretti, Fabio Pareschi, Marco Brini, Hakim Ghazzai, Riccardo Rovatti, Gianluca Setti
• DOI: 10.1109/jstars.2026.3671468

Research Groups

This paper introduces FOREST-GC, a conformal rendering engine developed for the generation of synthetic tree models and their subsequent automated counting.

Objective

• To develop and present FOREST-GC, a novel conformal rendering engine for the purpose of generating synthetic tree models and enabling their automated counting.

Study Configuration

• Spatial Scale:
• Temporal Scale:

Methodology and Data

• Models used: FOREST-GC (a conformal rendering engine)
• Data sources:

Main Results

Contributions

• Introduction of FOREST-GC, a new conformal rendering engine specifically designed for synthetic tree generation.
• Provision of a tool that facilitates the automated counting of generated synthetic trees.

Funding

Citation

@article{Prono2026FORESTGC,
  author = {Prono, Luciano and Dhieb, Najmeddine and Bich, Philippe and Boretti, Chiara and Pareschi, Fabio and Brini, Marco and Ghazzai, Hakim and Rovatti, Riccardo and Setti, Gianluca},
  title = {FOREST-GC: A conFOrmable Rendering Engine for Synthetic Tree Generation and Counting},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year = {2026},
  doi = {10.1109/jstars.2026.3671468},
  url = {https://doi.org/10.1109/jstars.2026.3671468}
}