mask = batch["mask"]
# train a model, or make predictions using a pre-trained model

```
Many applications involve intelligently composing datasets based on geospatial metadata like this. For example, users may want to:

Combine datasets for multiple image sources and treat them as equivalent (e.g., Landsat 7 and 8)
Combine datasets for disparate geospatial locations (e.g., Chesapeake NY and PA)

These combinations require that all queries are present in at least one dataset, and can be created using a UnionDataset. Similarly, users may want to:

Combine image and target labels and sample from both simultaneously (e.g., Landsat and CDL)
Combine datasets for multiple image sources for multimodal learning or data fusion (e.g., Landsat and Sentinel)
