Supraglacial dust (cryoconite) is an important but poorly understood component of the glacial system. There is a lack of primary data on cryoconite form, extent and dynamics. Here we present a suite of rapid, low-cost methodologies for quantification of granule geometry and supraglacial cryoconite coverage using image data captured by commercially available digital cameras. We develop robust, transferable protocols for analysis of (1) cryoconite granule geometry (major axis, Feret diameter, circularity); (2) centimetre-metre scale supraglacial extent (m2cryoconite m−2surface); and (3) temporal change in supraglacial extent at hourly intervals over several days. Image-processing methodologies were developed using the public domain software ImageJ. Manual (supervised) controls were used to estimate sources of error, and measurements then automated using simple scripting tools (macros). Fully automated processing successfully identified ∼90% of a sample of isolated granules ranging between 2.5 and 39.2 mm, with uncertainties of <20%. Particle sphericity (inferred from circularity) decreased as particle size increased. Supraglacial cryoconite extent was obtained with a mean uncertainty of 37% and 22% for data from field sites in Greenland and Svalbard, respectively. These methods will facilitate acquisition and analysis of datasets for cryoconite across a range of spatial scales, supporting research into cryoconite impacts on supraglacial hydrological connections, nutrient and carbon cycling, and initiation of primary succession in deglaciating environments.