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TitleRemote predictive mapping of bedrock geology using image classification of Landsat and spot data, western Minto Inlier, Victoria Ssland, NWT
AuthorBehnia, P; Harris, J R; Rainbird, R H
SourceGeological Association of Canada-Mineralogical Association of Canada, Joint Annual Meeting, Abstracts Volume vol. 34, 2011 p. 15,
Alt SeriesEarth Sciences Sector, Contribution Series 20110064
MeetingGAC/AGC - MAC/AMC - SEG - SGA, Ottawa 2011; Ottawa; CA; May 25-27, 2011
Mediapaper; CD-ROM; digital
File formatpdf
ProvinceNorthwest Territories
AreaVictoria Island; Minto Inlier
Subjectsgeophysics; stratigraphy; remote sensing; satellite imagery; computer mapping; mapping techniques; bedrock geology
LinksOnline - En ligne
AbstractImage classification of Landsat-7 and SPOT-5 data was used to analyze and map the bedrock geology of a part of western Minto Inlier on Victoria Island. The image data set consisted of two SPOT scenes and the corresponding area on the Landsat data. Based on the existing geology map, the main lithological units exposed in the study area include the Minto Inlet, Wynniatt, Kilian, and Kuujjua Formations of the Shaler Supergroup which are unconformably overlain by the Cambro-Ordovician succession. The Franklin magmatic event is represented by Natkusiak Formation basalts and the related gabbro-diorite sills and dykes intruded into the sedimentary strata. Digital image processing techniques were used to mask out the water, ice, and the main part of the vegetation to enhance the images and obtain a better discrimination between various lithological units. Six bedrock classes including diabase, basalt, carbonates of Wynniatt Fm, Kuujjua sandstone, evaporates of Minto and Kilain Formations, and Cambro-Ordovician carbonates together with six surficial classes including the vegetation, were defined mainly based on the spectral diversity observable in the Landsat image as well as expert knowledge. The separability of training areas was measured using both the Jeffries-Matusita and Transformed Divergence statistic and the maximum likelihood algorithm was used for classification. The resulting classified images for both Landsat and SPOT data were very similar in terms of the regional distribution of lithological classes, as reflected by fairly high classification accuracies for both imageries. Diabase and basalts, despite having a similar mineralogical composition are spectrally distinct throughout most of the study area especially on Landsat image. The Carbonates of Cambro-Ordovician succession were also successfully separated from carbonates of the Wynniatt Fm where the later was unconformably overlain by the former. Complicating spectral signatures of overlying glacial sediments and/or other overburden materials and spectral similarities between some of the lithologies caused poor classification in some areas. Generally the Landsat imagery provided better spectral separability between most of the lithological units than the SPOT imagery
because of its higher spectral resolution. However, in certain areas where the spectral separation between different lithologies is not dependant on the SWIR channels, the SPOT imagery provided a better classification because of higher spatial resolution.