Satellite remote sensing analysis is extensively used for geological mapping in arid regions. However, it is not considered readily applicable to the mapping of metamorphic and igneous terrains, where lithological contacts are less predictable. In this work, ASTER (Advanced Spaceborne Thermal Emission and Refl ection Radiometer) data were used to clarify the geological framework of the Precambrian basement in the Saghro massif (eastern Anti-Atlas, Morocco). The Saghro basement is composed of low-grade metasedimentary sequences of the Saghro Group (Cryogenian), intruded by calcalkaline plutons of late Cryogenian age. These rocks are unconformably covered by volcanic to volcaniclastic series of Ediacaran age that are broadly coeval with granitoid plutons. All of these units are cut by a complex network of faults associated with hydrothermal fl uid fl ows, which developed during and shortly after the emplacement of the volcanic rocks. The geological mapping of the Precambrian units was challenging in particular for the Edicaran granitoid bodies, because they are characterized by very similar compositions and a widespread desert varnish coating. For this reason, a two-stage approach has been adopted. In the fi rst step, false color composites, band ratios, and principal components analyses on visible and near infrared (VNIR) and shortwave infrared (SWIR) bands were chosen and interpreted on the basis of the fi eld and petrographic knowledge of the lithologies in order to detect major lithological contacts and mineralized faults. In the second step, a major effort was dedicated to the detection of granitoid plutons using both thermal infrared (TIR) and VNIR/SWIR data. The ASTER TIR bands were used to evaluate Reststrahlen and Christiansen effects in the granitoid rocks spectra, whereas VNIR/SWIR false color composite and ratio images were chosen directly on the basis of the granitoid spectra (derived from both spectrophotometric analyses of samples and selected sites in the ASTER image). Finally, spectral angle mapper (SAM) and supervised maximum-likelihood classifi cations (MLL) were carried out on VNIR/ SWIR data, mainly to evaluate their potential for discriminating granitoid rocks.
No takes yet. Share an insight, caveat, or question.
Massironi et al. (2008) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: