---
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:
 <img src="https:"https://huggingface.co/datasets/nascetti-a/BioMassters/blob/main/Data_specifications.png">

### Data Size:

```
  dataset         | # files  | size
  --------------------------------------
  train_features  |  189078  | 215.9GB
  test_features   |   63348  |  73.0GB
  train_agbm      |    8689  |   2.1GB
```
### Contact Information: