ANALYSIS OF PLUTONIC TEXTURE BY GIS ANALYSIS OF THIN SECTIONS

It is difficult to quantify the textural properties of rocks beyond simple modal analysis using standard thin-section examination. In order to better quantify plutonic textures we made a GIS-based geologic map of a thin section of equigranular Half Dome Granodiorite from Yosemite National Park, California. The resulting geodatabase can be queried for many textural properties.

Grain boundaries were digitized by hand using both polarized and unpolarized scans checked against microscopic examination of the original thin section. The resulting map gives a much clearer picture of textural relations than the microscopic view because extraneous information (e.g., twinning and variations in brightness) is suppressed. The attribute table contains many textural measures, including mineral proportions and the area and perimeter of each grain. Plagioclase (40% by area) and quartz (25%) compose the majority of the slide and occur in large, sinuous clusters of 20 or more grains. All other minerals occur as discrete crystals with little or no clustering. Grain-boundary sinuosity was calculated as grain perimeter divided by the perimeter of a circle of equivalent area; quartz (14.4) and plagioclase (16.2) are the most sinuous. Random clustering should occur for abundant minerals such as plagioclase and quartz, but the linear grain clusters evident in the map are clearly not randomly distributed. K-feldspar is nearly as abundant as quartz but is unclustered, occurring as relatively large, isolated grains. Rogers and Bogy (Science, 1958) found similar results from a variety of granites and speculated that K-feldspar crystals suppress nucleation of other K-feldspar crystals nearby. The solitary nature of K-feldspar may also result from its idiomorphic tendency (in contrast to quartz). During crystal aging, small K-feldspar crystals dissolved and were accreted onto larger ones, producing K-feldspar megacrysts in the porphyritic Half Dome and Cathedral Peak Granodiorites (Johnson et al., Eos, 2006). Such processes can be quantified using GIS mapping of thin sections.