PRELIMINARY MATERIALS INVESTIGATIONS TO SUPPORT SEARCH AND RECOVERY USING HYPERSPECTRAL REMOTE SENSING: INITIAL GEOMATERIALS AND CLOTHING RESULTS

The use of hyperspectral remote sensing techniques (HRST) to locate missing or lost persons in the context of traditional search and rescue (SAR) and law enforcement will be an emerging area of interest. HRST approaches currently are limited by the spatial resolution of sensors and the robustness of spectral libraries. HRST has the advantage of imaging large areas over a short period of time and collecting repeated images of the same scene for detailed comparison. Furthermore HRST can be used in situations where infrared cameras may not have high contrast, such as deserts or where diagnostic features of objects are in the NIR/SWIR. There is also the additional advantage that some HRST-SAR methods would not be time or environmentally dependent such as flares, radios and signal fires. Initial results are presented evaluating the use of natural mineral samples and granular synthetic oxide materials that have potential to be used as optically distinct “taggants”. These taggants can be dispersed in numerous geoenvironmental conditions. Used clothing items were investigated to determine their optical signatures, as well as common and representative geomaterial substrates from a proposed test site in eastern Kentucky. These taggants, clothing samples and geomaterial substrates were combined in an effort to distinguish unique optical signatures. Generally Al-rich taggant materials are not optically distinct in the wavelengths investigated (200 or 350 – 1050 nm). Selected metal oxides are very distinctive. Topology of spectra of glasses compared to oxides are broadly similar for one metal group, however oxides tend to be more spectrally rich. The preliminary results of this investigation suggest a HRST-SAR system may be developed with extensive laboratory work that includes intense materials characterization and software tool development. Such a geotechnology may be beneficial especially in lost hiker scenarios, disaster scenarios and stranded person scenarios.