Application of probability theory to integrated geological mapping from remotely sensed data of the Precambrian Shield (Manitoba, Canada)

dc.contributor.authorRao, Govindaraju Suresh Kumaren_US
dc.date.accessioned2012-06-01T19:03:41Z
dc.date.available2012-06-01T19:03:41Z
dc.date.issued1995en_US
dc.degree.disciplineGeological Sciencesen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractInvestigation of earth resource potential requires the integration of various information obtained from different survey techniques. Such information is commonly represented as two-dimensional digital map layers. The ability to selectively combine, by spatial data integration processes, diverse data types, is increasingly becoming a mainstay of geological exploration programs. Such automated mapping of a terrain usually requires some previous knowledge of the terrain. This knowledge is used to constrain the mapping algorithm or to formulate a set of rules that govern the integration process. However, in cases where a completely unknown terrain is being investigated, the lack of prior knowledge can be a serious obstacle. The present research addresses the fundamental problem of integrating remotely sensed satellite and geophysical data, in the absence of an initial data base. Three types of integration techniques, based on probability theory, are presented: algebraic probability, spatial index, and Bayesian probability. The target proposition is the mapping of the boundary zone between the Proterozoic Churchill Province and Archean Superior Province. In an hitherto unmapped study area, the algebraic probability method demonstrates the assignment of probabilities to input data sets, based on the target proposition and visual interpretation. The input data are integrated by an algebraic additive process. The probability assignment and the algebraic additive process are validated by application to another area of known geology. Once validated, the results of the algebraic probability method are treated as an a priori indicator for the next two methods. The spatial index method is developed to quantify the spatial correlation in the input data sets with the a priori information. This correlation is then converted into a probability measure, and the integration process is carried out... The results show that the probability method is a useful technique for data integration. Based on the results of this study, a revised geological map was compiled, which shows that the NE trend of the Churchill-Superior boundary zone changes to an approximate N-S trend in the southern part of the study area, where Paleozoic rocks mask the Precambrian Shield. The results also show that the boundary zone as located by the present analysis, is about 11 km east of the the currently estimated eastern edge of the boundary zone as defined by surface geology. One possible explanation of this discrepancy is to invoke a shallow SE dip for the boundar zone, as opposed to the NW dip advocated by most workers. Independent investigations using latest seismic reflection data also support a SE dip for the Thompson Belt.en_US
dc.format.extentxviii, 212 [i.e. 213] leaves :en_US
dc.identifierocm00132167en_US
dc.identifier.urihttp://hdl.handle.net/1993/7358
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.titleApplication of probability theory to integrated geological mapping from remotely sensed data of the Precambrian Shield (Manitoba, Canada)en_US
dc.typedoctoral thesisen_US
local.subject.manitobayesen_US
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