| name | alphaearth_foundations_core |
| description | Core information for AlphaEarth Foundations Satellite Embeddings in Google Earth Engine (GEE). |
The Google Satellite Embedding dataset provides 64-dimensional geospatial
embeddings representing the semantic characteristics of Earth's surface at
10-meter resolution.
Specifications
- Dataset ID:
GOOGLE/SATELLITE_EMBEDDING/V1/ANNUAL
- Bands: 64-dimensional float embeddings, named
A00 through A63.
- Unit-Vector Guarantee: The bands are pre-normalized unit vectors (values
in range
[-1, 1]).
See the catalog page for more details:
Satellite Embedding V1 (Annual)
Quantization & De-quantization (Under the Hood)
To store global high-dimensional embeddings efficiently, the dataset is internally quantized to 8-bit signed integers.
If you are accessing raw signed 8-bit integers in the raw collection
GOOGLE/SATELLITE_EMBEDDING/V1/ANNUAL_RAW or direct from the GCS bucket
gs://alphaearth_foundations/satellite_embedding/v1/annual/, the non-linear
de-quantization mapping used to reconstruct the native float values is:
$$v_{de_quant} = \text{sign}(v_{raw}) \cdot \left(\frac{v_{raw}}{127.5}\right)^2$$
[!NOTE] If reading raw COGs from the GCS bucket, mask the reserved no-data
value -128 before applying this formula; otherwise it dequantizes to a value
outside the valid [-1, 1] range.
def de_quantize(raw_image):
raw_image = raw_image.updateMask(raw_image.neq(-128))
return raw_image.float() \
.divide(127.5) \
.pow(2) \
.multiply(raw_image.signum())
