UnMixMamba splits four crops out of coarse MODIS pixels, lifting barley recall to 0.55 in Alberta at roughly a thousand times the compute
A MODIS pixel often covers one or more Prairie fields, so the coarse signal is a mixture of crop types and direct coarse-to-fine classifiers struggle. UnMixMamba uses the abundance field from unmixing as a shared intermediate, so reconstruction, classification and sparse refinement all read the same fractions, while a learnable per-crop variant bank absorbs intra-class spectral spread. On 183 spatially blocked Alberta 2015 test patches it reaches OA 0.8397, mIoU 0.6640, AA 0.7837 and Kappa 0.7715, ahead of ST-DRes and other baselines, with the best barley recall in the comparison at 0.5496; the task is closed-set four-crop mapping inside a known agricultural mask.