We group grids together by creating 'samples' at larger scales by way of

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We group grids together by creating 'samples' at larger scales by way of

Grouping grids across scales uses a pyramid structure. An image or data pyramid represents the same grid at multiple resolutions, creating samples at larger scales by downsampling (often with smoothing) to form coarser versions. This lets you capture broad patterns with fewer data points while still having finer levels for detail when needed. The pyramid approach is built precisely to produce these successive, larger-scale samples from the original grid, enabling efficient analysis, storage, and processing. The other options describe shapes or boundaries rather than a method for multi-scale sampling, so they don’t fit this purpose.

Grouping grids across scales uses a pyramid structure. An image or data pyramid represents the same grid at multiple resolutions, creating samples at larger scales by downsampling (often with smoothing) to form coarser versions. This lets you capture broad patterns with fewer data points while still having finer levels for detail when needed. The pyramid approach is built precisely to produce these successive, larger-scale samples from the original grid, enabling efficient analysis, storage, and processing. The other options describe shapes or boundaries rather than a method for multi-scale sampling, so they don’t fit this purpose.

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