Towards Global Mapping of the Earth’s Land Surface Composition

New “geoscience-tuned” remote sensing technologies are now available (e.g. satellite-borne multi-spectral ASTER and airborne HyMap imaging systems) or soon to be available (e.g. satellite hyperspectral Hyper-J and EnMap systems) for the resources (energy, minerals and soils) community. These imaging sensors have the potential to provide global information at high spatial resolution for baseline mapping and monitoring of land surface composition, including the abundance and physicochemistry of minerals. These mineral information products complement other types of public geoscience information currently available through government geosurveys, such as geology and soil maps, geophysics and geochemistry. However, the opportunity to capture the full potential of these mineral maps for public use by the global resources communities has not been realised, even though some of these remote sensing systems have been operating for over 10 years. The failure to act upon this opportunity is for a variety of reasons, including: o Need for robust instrument correction, radiative transfer and cross-calibration corrections for generating seamless multiscene imagery; o Non-trivial processing of the “reflectance” data into valuable information products (requires image processing experts); o Lack of geoscience products standards, including traceable validation and error assessment; o Lack of easy standard information access (web delivery with associated interoperability and metadata structure); and o Technology transfer (what do these maps mean for the resources sector?). Many of these issues result from the current reliance on the private sector to deliver these geoscience information products to the resources community in a commercially competitive environment. This paper provides examples from Australia of how government geoscience and research agencies are working together to develop publicly available, web-accessible geoscience mineral mapping products from ASTER and hyperspectral imaging data of value to the resources, soils and agricultural communities.