Cropland mask dataset for the Canadian Prairies derived from Google Satellite Embedding imagery

# Canadian Prairies Cropland Masks — 10 m (GeoTIFF)

# Overview
This repository/package accompanies a spatially explicit raster dataset of cropland mask for the Canadian Prairies (Alberta (AB), Saskatchewan (SK), and Manitoba (MB))

# Methods Summary (How the dataset was created)
1. Predictor generation: Multi-source predictors were derived from AlphaEarth embeddings.
2. Reference sampling: Stratified-random sample points were distributed across the Prairies to represent cropland and non-cropland conditions.
3. Model training: A Random Forest classifier was trained to separate cropland from non-cropland using AAFC crop mask as labels.
4. Wall-to-wall inference: The trained models were applied to generate annual binary cropland masks for 2017–2024 at 10 m.
5. Aggregation: Annual masks were summed to generate a cropland frequency layer.
6. Stable cropland definition: Pixels classified as cropland in more than two years were labeled as persistent cropland to produce a stable mask.

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## Spatial and Technical Specifications
- Geographic extent: Canadian Prairies — Alberta, Saskatchewan, Manitoba
- Spatial resolution: 10 m
- Raster format: GeoTIFF
- Coordinate reference system (CRS): EPSG:4326)
- NoData value: 0
- Pixel encoding: - Annual mask: 0 = non-cropland, 1 = cropland

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Caution / best practices:
- Annual masks represent modeled predictions and may contain errors near edges of fields, heterogeneous land cover, or mixed pixels.
- If comparing with other products, ensure consistent CRS, resolution, and resampling methods.