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Geomad

A library for fast calculation of geomedian and median absolute deviation (MAD).

Assumptions

We assume that the data stack dimensions are ordered so that the spatial dimensions are first (y,x), followed by the spectral dimension of size p, finishing with the temporal dimension.

Algorithms reduce in the last dimension (typically, the temporal dimension).


For details of the scientific algorithms implemented, see:

  • Roberts, D., Mueller, N., & McIntyre, A. (2017). High-dimensional pixel composites from earth observation time series. IEEE Transactions on Geoscience and Remote Sensing, 55(11), 6254-6264.

  • Roberts, D., Dunn, B., & Mueller, N. (2018). Open data cube products using high-dimensional statistics of time series. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 8647-8650).

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