This chapter explains the rationale for considering shallowly buried (0 to >5 m depth) water ice in the mid-latitudes of Mars as a resource to support future human missions, and describes a NASA-funded effort to map that ice with existing orbital remote-sensing data. In recent decades, numerous studies have used various datasets to investigate the presence and stability of water ice in the Martian shallow subsurface, with the aim of understanding the planet’s recent climate history. As part of a renewed effort to prepare for human Mars missions, NASA has undertaken a more resource-focused approach. Here we describe the Mars Subsurface Water Ice Mapping (SWIM) team’s efforts to characterize the distribution of buried water-ice resources across all longitudes from 60°S to 60°N latitude through the integration of multiple datasets. Deriving composite measures for the presence of accessible ice from a diverse range of remote sensing techniques with unique resolutions and caveats is a challenging problem. To enable data synthesis, the team developed a methodology that assigns values of ice consistency for mapped detections of hydrogen from a neutron spectrometer, thermal behavior from various thermal spectrometers, multiscale geomorphology from imagery and elevation data, and surface and subsurface echoes from a radar sounder. Faced with diverse sensing depths and footprints for these datasets, the team has been pursuing an optimal approach to best represent multi-dataset ice consistency. The current formulation includes the use of weighting factors tuned to depth zones of interest for resource extraction. In the absence of dedicated ground-truth data, the validity of the team’s efforts is assessed by comparing the maps to the locations of fresh, ice-exposing impacts. The highest ice-consistency values occur within discrete zones poleward of ~40° latitude, where ice is relatively shallow, but positive values extend well into the ~20°–30° latitude zone, which is preferable for landing sites due to engineering considerations.