🌲 AGBD: A Global-scale Biomass Dataset 🌳

Authors: Ghjulia Sialelli ([email protected]), Torben Peters, Jan Wegner, Konrad Schindler

🚀 Usage

To get started with this dataset, use the following code snippet:

# Install the datasets library if you haven't already
!pip install datasets

# Import necessary modules
from datasets import load_dataset

# Load the dataset
dataset = load_dataset('prs-eth/AGBD', trust_remote_code=True, streaming=True)["train"]  # Options: "train", "val", "test"

This code will load the dataset as an IterableDataset. You can find more information on how to work with IterableDataset objects in the Hugging Face documentation.

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📊 Dataset Overview

Each sample in the dataset contains a pair of pre-cropped, pre-normalized images along with their corresponding biomass labels. For additional resources, including links to the preprocessed uncropped data, please visit the project page on GitHub.

⚙️ Load Dataset Options

The load_dataset function provides the following configuration options:

• normalize_data: {True, False}
  Whether to return normalized (0-1) data or raw values.

• additional_features: []
  A list of additional features the dataset should include. Refer to the documentation below for more details.

• patch_size: 25
  The size of the returned patch (in pixels). The maximum value is 25 pixels, which corresponds to 250 meters.

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🖼️ Image Details

Each image consists of 24 channels, organized into the following categories:

• Spectral Bands:
  B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12

• Geographical Coordinates:
  lat_cos, lat_sin, lon_cos, lon_sin

• ALOS PALSAR Bands:
  alos_hh, alos_hv

• Canopy Heights:
  ch, ch_std

• Land Cover Information:
  lc_cos, lc_sin, lc_prob

• Digital Elevation Model (DEM):
  dem

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📐 Channel Structure

The channels are structured as follows:

(Spectral Bands) | (Geographical Coordinates) | (ALOS PALSAR Bands) | (Canopy Heights) | (Land Cover Information) | DEM

(B01 B02 B03 B04 B05 B06 B07 B08 B8A B09 B11 B12) | (lat_cos, lat_sin, lon_cos, lon_sin) | (alos_hh, alos_hv) | (ch, ch_std) | (lc_cos, lc_sin, lc_prob) | dem

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➕ Additional Features

You can include a list of additional features from the options below in your dataset configuration:

• "agbd_se" - AGBD Standard Error: The uncertainty estimate associated with the aboveground biomass density prediction for each GEDI footprint.
• "elev_lowes" - Elevation: The height above sea level at the location of the GEDI footprint.
• "leaf_off_f" - Leaf-Off Flag: Indicates whether the measurement was taken during the leaf-off season, which can impact canopy structure data.
• "pft_class" - Plant Functional Type (PFT) Class: Categorization of the vegetation type (e.g., deciduous broadleaf, evergreen needleleaf).
• "region_cla" - Region Class: The geographical area where the footprint is located (e.g., North America, South Asia).
• "rh98" - RH98 (Relative Height at 98%): The height at which 98% of the returned laser energy is reflected, a key measure of canopy height.
• "sensitivity" - Sensitivity: The proportion of laser pulse energy reflected back to the sensor, providing insight into vegetation density and structure.
• "solar_elev" - Solar Elevation: The angle of the sun above the horizon at the time of measurement, which can affect data quality.
• "urban_prop" - Urban Proportion: The percentage of the footprint area that is urbanized, helping to filter or adjust biomass estimates in mixed landscapes.
• "gedi_num_days" - Date of GEDI Footprints: The specific date on which each GEDI footprint was captured, adding temporal context to the measurements.
• "s2_num_days" - Date of Sentinel-2 Image: The specific date on which each Sentinel-2 image was captured, ensuring temporal alignment with GEDI data.
• "lat" - Latitude: Latitude of the central pixel.
• "lon" - Longitude: Longitude of the central pixel.