تقرير
Open-Canopy: A Country-Scale Benchmark for Canopy Height Estimation at Very High Resolution
| العنوان: | Open-Canopy: A Country-Scale Benchmark for Canopy Height Estimation at Very High Resolution |
|---|---|
| المؤلفون: | Fogel, Fajwel, Perron, Yohann, Besic, Nikola, Saint-André, Laurent, Pellissier-Tanon, Agnès, Schwartz, Martin, Boudras, Thomas, Fayad, Ibrahim, d'Aspremont, Alexandre, Landrieu, Loic, Ciais, Philippe |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing |
| الوصف: | Estimating canopy height and canopy height change at meter resolution from satellite imagery has numerous applications, such as monitoring forest health, logging activities, wood resources, and carbon stocks. However, many existing forest datasets are based on commercial or closed data sources, restricting the reproducibility and evaluation of new approaches. To address this gap, we introduce Open-Canopy, the first open-access and country-scale benchmark for very high resolution (1.5 m) canopy height estimation. Covering more than 87,000 km$^2$ across France, Open-Canopy combines SPOT satellite imagery with high resolution aerial LiDAR data. We also propose Open-Canopy-$\Delta$, the first benchmark for canopy height change detection between two images taken at different years, a particularly challenging task even for recent models. To establish a robust foundation for these benchmarks, we evaluate a comprehensive list of state-of-the-art computer vision models for canopy height estimation. The dataset and associated codes can be accessed at https://github.com/fajwel/Open-Canopy. Comment: 22 pages, 8 figures, Submitted to NeurIPS 2024 Datasets and Benchmarks Track |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.09392 |
| رقم الأكسشن: | edsarx.2407.09392 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |