Endmember search and proportion estimates from airborne hyperspectral surveys. Issue 2 (17th January 2018) - Traylen, Anthony; Caccetta, Peter; Guo, Yi; Berman, Mark; Lau, Ian C
ABSTRACT: The estimation of areas of land-cover elements is required for many natural resource management programmes and is also used by the mineral and petroleum resource communities either for detection of mineral abundances or monitoring of environmental remediation and other off-site impacts. When the identification of many constituent elements is desired, remote sensors that possess many spectral bands are often deployed, providing data that can be used in a spectroscopic (or other) analysis. At the size of a (remotely sensed) ground sample (represented as an image pixel), which with current technology is typically a few metres, the sample is heterogeneous and typically composed of several biological and geological constituents. It is of interest to first identify the constituent elements and their number and, second, to estimate their relative abundance. When no suitable spectral library is available for a particular data set, an exploratory approach using a blind unmixing method may be used to detect and estimate the endmembers themselves – an exploratory approach because there is no guarantee that the spectral endmembers fitted using blind unmixing will correspond to the 'pure' materials of interest to a particular application. Further, if employing a blind unmixing technique to each image in a large multi-image survey independently, there is no guarantee that compatible sets of endmembers will be found to produce maps that are seamless across contiguous images. The aim of this article is to examine the potential for applying blind unmixing at the whole-of-survey level as a way to finding endmembers and proportion maps that are cross-swath consistent and broadscale applicable. We demonstrate that a mosaic of many radiometrically block-adjusted swaths of data from the HyMap airborne hyperspectral imager (HyVista Corporation) can be unmixed as a single image using the Iterated Constrained Endmembers blind unmixing algorithm. The major endmembers are validated against available Analytical Spectral Devices ground spectra and broadscale abundance maps of the type targeted by both vegetation and soil mapping communities are produced.