‘Mapping’ crystal orientations for ice dynamics – from macro-to micro-J O A N F I T Z PAT R I C K , PAC O VA N S I ST I N E , L A R RY W I L E N , D O N V O I GT

GEOSCIENCES AND ENVIRONMENTAL CHANGE SCIENCE CENTER

MISSION: Our world is being transformed due to climate variability, population growth, intensive land use, and the increasing demands on water, ecological, agricultural, energy, and mineral resources. To address these issues, the Geosciences and Environmental Change Science Center (GECSC) conducts research on (1) climatic, environmental, and landscape changes, (2) the geologic framework of natural resources and hazards, (3) ecological disturbance patterns resulting from natural and anthropogenic changes, and (4) the interactions among geologic, biologic, hydrologic, and human systems. This work supports policy and management decisions, the search for new sources of key materials, and the assessment of the combined environmental impacts of climate variability and human activities.

Glaciers and ice sheets hold valuable records of past climate states of the Earth.

Grain spatial data – WAIS Divide 460 m

Grain orientation data

~4 i

nche

s

~20

kilo

met

ers

Geologic Map

Geologic Map Index

COLORADO

Starting layer set:

x, y positionAreaMean Equivalent DiameterMoment AngleOrientation (Θ, Φ)

Original grain image

Simplified image

Area(cm^2)Filled_Area(cm^2)Convex_Area(cm^2)Length(cm)Breadth(cm)Equiv.Diam.(cm)Inscrib.Rad.(cm)Circum.Rad.(cm)Perimeter(cm)External_Perim.(cm)Convex_Perim.(cm)X-FeretY-FeretFormFactorRoundnessAspect_RatioSolidityConvexitySymmetryRadius_RatioElongationFractal_Dim.X-Centroid(cm)Y-Centroid(cm)Moment_AngleX-Weighted_CG(cm)Y-Weighted_CG(cm)X-Geom.Center(cm)Y-Geom.Center(cm)Nearest_Nbor_Dist.(cm)Nearest_Nbor_Dir.Nearest_Nbor_IDMin.Separation_IDAdjacent_Feature_Count

Area (px^2)

Θ (°)

Φ (°)

x-CG

y-CG

Grain spatial data

Grain orientation data

Feature_Number Area(px^2)

X-Weighted CG(px)

Y-Weighted CG(px) (origin at upper left)

reverse Y (origin at lower left) theta phi theta for ArcGIS phi for ArcGIS

1 5441 1587 280 6676 85.4714 -18.557587 85.4714 341.4424132 3595 5739 303 6653grain not analyzable3 20335 3487 385 6571 -85.819485 27.013259 85.819485 207.0132594 340318 3378 750 6206 -38.209741 60.796299 38.209741 240.7962995 23089 564 411 6545 -78.071313 -79.697021 78.071313 100.3029797 114145 4866 518 6438 -44.650841 75.403025 44.650841 255.4030258 9448 5801 392 6564grain not analyzable

10 125142 1189 601 6355 -63.628303 56.431789 63.628303 236.43178911 60480 4078 457 6499 -53.49685 58.003461 53.49685 238.00346112 60619 5647 502 6454 83.182847 87.304832 83.182847 87.30483213 56467 6728 444 6512 -90.519286 81.647107 90.519286 261.64710714 61466 1966 589 6367 86.581349 -18.84876 86.581349 341.1512415 8725 3618 450 6506 -64.099101 -68.908205 64.099101 111.09179516 72862 770 546 6410 -23.031831 11.679309 23.031831 191.67930917 69380 5864 681 6275 -53.383545 34.257237 53.383545 214.25723718 9288 3103 521 6435grain not analyzable19 39753 5408 543 6413 -74.672318 -70.194879 74.672318 109.80512120 74614 3781 598 6358 70.977656 9.268722 70.977656 9.26872221 5952 3596 559 6397 -34.510694 38.927598 34.510694 218.92759822 15702 5331 635 6321grain not analyzable23 23793 4105 607 6349 -77.832408 -39.374212 77.832408 140.62578824 5272 950 574 6382 -57.077565 -71.702549 57.077565 108.29745126 22811 6415 553 6403 -64.38011 27.630119 64.38011 207.63011927 26823 2689 593 6363 62.750145 35.344046 62.750145 35.34404629 143473 4389 619 6337 -50.027054 61.184448 50.027054 241.18444830 21161 5297 707 6249 -70.759344 -73.27168 70.759344 106.72832

Data passed to ArcGIS:

“Geo”reference image in XY pixels

0px0px

1000

0150

100px150px

Zoomed example of grain sample image

Reclassify 3 band image to Bitmap Convert Raster to line Feature Class

Add XY attributes from spreadsheet(Area)

Create polygon features using XY attributes(Area)

Use XY centroids as Theta and Phi

Desired visualizations:

WDC06A- 845 meters WDC06A – 3285 meters

Final data layers:

Original grain image

Bitmap image conversion

Area polygon feature creation

Theta and Phi point feature visualization

‘Mapping’ crystal orientations - Macro to Micro

Macro Geology Micro Ice Crystals Output Visualization