Landsat-TM-Based Discrimination of Lithological Units Associated with the Purtuniq Ophiolite, Quebec, Canada

Abstract

Abstract:In order to better constrain the utility of multispectral datasets in the characterization of surface materials, Landsat Thematic Mapper (TM) data were evaluated in the discrimination of geological classes in the Cape Smith Belt of Quebec, a greenstone belt that hosts Early Proterozoic units including those of the Purtuniq ophiolite. Ground-based measurements collected for the study area highlight the importance of chemical alteration in controlling the reflectance properties of key geological classes. The spatial distribution of exposed lithologies in the study area was determined through (1) image classification using a feedforward backpropagation neural network classifier; and (2) generation of fraction images for spectral end members using a linear unmixing algorithm and ground reflectance data. Despite some shortcomings, the database of surface cover generated by the neural network classifier is a useful representation of the spatial distribution of exposed geological materials in the study area, with an overall agreement with ground truth of 87.7%. In contrast, the fraction images generated through unmixing are poor representations of ground truth for several key lithological classes. These results underscore both the considerable utility and marked limitations of Landsat TM data in the mapping of igneous and metamorphic lithologies.

Detection and Mapping of Black Rock Coatings Using Hyperion Images: Sudbury, Ontario, Canada

“…The feedforward backpropagation neural network algorithm relates image values to surface classes on the basis of the magnitudes of weights associated with the links and nodes of a network [81,[83][84][85][86]. In this study, a standard network geometry was defined with nine nodes in the input layer of the network (with each node associated with one of the nine spectral ranges defined above), nine nodes in each of two intermediate layers, and either six or seven nodes in the output layer (each corresponding to a particular surface class).…”

Targeting Mineral Resources with Remote Sensing and Field Data in the Xiemisitai Area, West Junggar, Xinjiang, China

“…Remote sensing has been extensively used for lithological mapping and mineral exploration [6][7][8][9][10][11][12][13][14][15][16][17][18]. The multispectral data of the Landsat Thematic Mapper (TM) and the Enhanced Thematic Mapper (ETM+) have been the most commonly used data sources for geologic applications in the past three decades with promising results [7,[16][17][18][19][20][21][22].…”

Application of remotely sensed data in detecting zinc-lead bearing mineralized zones in Westkunlun Huoshaoyun area

“…The sandstone-to-mudstone, which is rich of mica and clay minerals, is mapped by the ratios (6/5 of OLI) and (5/3 of ASTER), since its spectra show high reflectance in band 6 of OLI and band 5 of ASTER, against an absorption at 860 nm (band 5 of OLI) and 800 nm (band 3 of ASTER), corresponding to the near infrared region. This type of absorption is also due to the presence of iron oxides [22][23][24]. In comparison with other spectra, conglomerate shows a high reflectance in band 4 of OLI and band 3 of ASTER, and intense absorption of Al-OH type at 2200 nm (band 7 of OLI and band 6 of ASTER) due to mica or clay minerals [9,23,25], hence the ratios of (4/7 of OLI) and (3/6 of ASTER) are used to map this rock unit.…”