metadata
license: cc-by-4.0
language:
- en
tags:
- climate
pretty_name: BioMassters
size_categories:
- 100K<n<1M
BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series https://nascetti-a.github.io/BioMasster/
The objective of this repository is to provide a deep learning ready dataset to predict yearly Above Ground Biomass (AGB) for Finnish forests using multi-temporal satellite imagery from the European Space Agency and European Commission's joint Sentinel-1 and Sentinel-2 satellite missions, designed to collect a rich array of Earth observation data
Reference data:
- Reference AGB measurements were collected using LiDAR (Light Detection and Ranging) calibrated with in-situ measurements.
- Total 13000 patches, each patch covering 2,560 by 2,560 meter area.
Feature data:
- Sentinel-1 SAR and Sentinel-2 MSI data
- 12 months of data (1 image per month)
- Total 310,000 patches
Data Specifications:
Data Size:
dataset | # files | size
--------------------------------------
train_features | 189078 | 215.9GB
test_features | 63348 | 73.0GB
train_agbm | 8689 | 2.1GB