Products

Crop Biomass

note

As of December 1, 2024, BIOMASS-PROXY_V3.0_10 has been officially deprecated. We encourage all users to migrate to the latest version (BIOMASS-PROXY_V4.0_10) to benefit from enhanced features, updates, and continued support (FAQ). For assistance with the transition, please contact your Customer Success Manager.

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Product Specifications

Data Resource	Crop Biomass
Unit	None (Typical Range 0 to 1)
Pixel Size	0.000089° (±10x10 m) - EPSG:4326
Temporal Resolution	daily (365 observations per year)
Satellites Used	Sentinel-1, Sentinel-2, Planetscope
NRT Latency	Daily at 6am local time
Archive Latency	Less than 4 hours after creating a subscription

Crop Biomass is a global product, but its geographic availability is limited in some areas between December 2021 and January 2025 due to the failure and subsequent end of mission of Sentinel 1-B.

Metadata

The daily GeoTIFF files include metadata that provides transparency regarding how the product is constructed.

Metadata	Description
DATE_LAST_OPTICAL_IMAGE_USED	The date of the most recent optical image used in the product. This can support the understanding and interpretation of the signal, as it is an indication of the relative contribution of the optical data.
DATE_LAST_S1_IMAGE_USED	The date of the most recent Sentinel-1 SAR image used in the product. This can support the understanding and interpretation of the signal, as it is an indication of the relative contribution of the radar data.
LAST_OPTICAL_IMAGE_SOURCE	The source of the most recent optical image used, either "PS" (PlanetScope) or "S2" (Sentinel-2).
PERCENTAGE_PIXELS_MASKED	The percentage of pixels in the dataset that were masked due to issues such as cloud cover, water, snow, roads, or buildings. A value of "0.0" indicates that no pixels were masked, meaning the data is complete and unaltered.
PRODUCT_VERSION	The version of the product, "v4", indicates the current version of the Crop Biomass product, reflecting the most recent updates and improvements in the methodology and data processing.

Below is a Python code snippet on how to extract the metadata from the .tif file of interest.

from osgeo import gdal

def get_metadata_from_raster(file_path: str) -> dict:
    dataset = gdal.Open(file_path)
    metadata = dataset.GetMetadata()
    return metadata