The application of GIS to unravel patterns of deformation in high grade terrains: a case study of indentor tectonics from west Greenland

Abstract

Abstract The ability to compare, integrate and knit together multidisciplinary datasets in terms of subject, space and scale is critical to the recognition of geological patterns. In this contribution, we show that the use of Geographic Information Systems (GIS) is extremely valuable in detecting patterns associated with broad zones of deformation in high grade terrains. The GIS methodology facilitates the geological interpretation and development of models as it permits an easy and quick investigation of several geoscientific datasets by subject, space and scale. The GIS-based integration of structural, metamorphic, fabric type and aeromagnetic datasets collected in west Greenland shows that patterns seen within one dataset coincide with patterns observed in other datasets. Consequently, two major domains are recognized that are separated by a broad boundary zone. The southern block is characterized by a distinct, irregular magnetic signal coupled with granulite facies metamorphism and dominant S-type fabrics. The map scale geometry of this block controls the patterns observed within the amphibolite facies domain further north. Foliation and lineation patterns form an arcuate swing in strike about the southern block. Fabric types vary both around the strike swing and across strike. An indentor model that incorporates a rigid, cooled granulite block in the south bounded to the north by a rheologically weaker amphibolite facies domain can explain these patterns. The preserved metamorphic grade governs the rheology of the different, but essentially authochthonous blocks with the amphibolite facies domain being plastered and ‘moulded around’ the rigid granulite indentor. As patterns of remote geophysical and geological data closely correspond with one another, greater confidence may be placed in the application of remote geophysics in areas which lack abundant ground-based data.