Mineral sandsApplied Earth Science provides an opportunity for geoscientists working in the minerals industry to share their knowledge. In particular, the journal is publishing special issues devoted to the different aspects of modern applied exploration and mining geology. This journal has previously published special issues devoted to the technical characterisation of iron ore deposits (Appl. Earth Sci. 119 (1) (3) 2010), nickel sulphide deposits (Appl. Earth Sci. 120 (4) 2011) and sandstone hosted uranium mineralisation (Appl. Earth Sci. 121 (2) 2012) and mineral resource estimation for a range of commodities (Appl. Earth Sci. 123 (2) 2014).This latest special issue is devoted to mineral sands deposits and the extraction of valuable heavy minerals (mainly ilmenite, rutile, leucoxene and zircon). The mineral sand deposits fall into three main deposit styles, palaeo-marine placers, aeolian (dunal) sands and alluvial deposits. Analogues from present day geomorphological processes are used to understand the processes and depositional environments for the concentration of heavy minerals and deposit formation. The main challenges for the exploration and mining of the mineral sands are that:. Mineral sands deposits comprise non-consolidated to semi-consolidated sands hosting valuable heavy minerals that are unevenly distributed in a matrix of mainly gangue quartz. The heavy minerals have high average densities (of over 4.0 g cm −3 ) and are significantly heavier than the sand matrix (density 2.6 g cm −3 ). The large difference in the mineral densities can result in segregation of the heavy minerals during drilling and sample collection causing a biased composition of the recovered samples. . The presence of hard pan lenses, concretions and clay beds, hosted within non-consolidated sediments, which can hamper the application of dredging technologies for mining the mineral sands deposits. . The product costs depend on the mineralogy of the heavy fraction and so the mineral composition of the heavy fraction needs to be accurately estimated into the Ore Reserve model.