“alternative” data structures. information spaces / spatialization
TRANSCRIPT
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“Alternative” Data Structures
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Information Spaces / Spatialization
www.smartmoney.com
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Information Spaces / Spatialization
Chen et al. 1998
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Information Spaces / Spatialization
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Information Spaces / Spatialization
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Alternative Data Structures(especially w/ increased processing speeds, storage)
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Thiessen (Voronoi) Polygonsand Delaunay Triangles
they divide the space between the points as ‘evenly’ as possible
– market area delimitation, rain gauge area assignment, VIPs
DTs are as near equiangular as possible, thus minimizes distances for interpolation
elevation, slope and aspect of triangle calculated from heights of its three corners
A
Thiessen neighbors of point A share a common boundary. Delauney triangles are formed by
joining points to its Thiessen neighbors.
A
Thiessen Polygons
Delaunay Triangles
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• partition areas based on “influence” of sample points (Thiessen polys)• all sample points connected w/ 2 nearest neighbors to form triangles
• connect centroids of Thiessen polygons
market area delimitation, rain gauge area assignment, trusted elevation benchmarks or VIPs, etc.
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Sampled locations and values Thiessen polygons
Daniel P. Ames, Dept. of Geosciences (Geology), Idaho State University
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Visualization of Theissen Concept
Arthur J Lembo, Jr., Bowne
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Inverse Distance Weighting
Arthur J Lembo, Jr., Bowne
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Kriging
Arthur J Lembo, Jr., Bowne
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Perspective Plot from TIN
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TIN (Triangulated Irregular Network)
avoids redundancy of raster while still producing a continuous surface
more efficient than raster for some terrain analysis– slope and aspect (faces of triangles)– contouring
Measurements are irregularly spaced with more sampling in areas of greater complexity– requires fewer points or grid cells
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Contours from TIN(triangles can be many and extremely small with a
good sampling of points)
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• Computers love rasters• A cell on 1 map is at same position on all others
• Easy query, neighborhood ops., etc.
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Storage/Scan Orders
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Compression:Run Length Encoding
based on spatial autocorrelation– nearby things tend to be
more similar than distant things
data entered as pairs– run length & value
40 items instead of 704 a 6 b 4 a 6 b 4 a 1 c 4 b 3 a 2 c 5 b 3 a 4 c 3 b 2 a 5 c 3 b 8 c 2 b 8 c 2 b
a a a a b b b b b b
a a a a b b b b b b
a a a a c b b b b b
a a a c c c c b b b
a a c c c c c b b b
c c c c c c c c b b
c c c c c c c c b b
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• way of encoding irregularity of vector in raster form
• step beyond run-length-encoding compression• compress in row AND column directions
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Raster to Quadtree
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Divide into sub-quadrantsfocusing on irregularity
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Quadtrees of Chloropleth Raster Map
NW NE SW SE
NW NE
SW SE
Marc van Kreveld, U. of Utrecht
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Multiple resolution storage
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Adaptive MWVD solution Rene Reitsma, OSU CoB
Vector solution: infinite precision, difficult computing. Raster solution: limited precision, easy computing.
– Resolution increases allow higher precision.– Boundary-only, quadtree resolution increases.
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Gateway to the Literature“information spaces”
Reitsma, R. and Trubin, S., Information space partitioning Information space partitioning using adaptive Voronoi diagrams, using adaptive Voronoi diagrams, Information Information VisualizationVisualization, http://www.palgrave-journals.com/ivs/, 2006., http://www.palgrave-journals.com/ivs/, 2006.
Dodge, M., and R. Kitchin, Code and the transduction of Dodge, M., and R. Kitchin, Code and the transduction of space, space, Annals AAGAnnals AAG, , 9595 (1), 162-180, 2005. (1), 162-180, 2005.
Fabrikant, S.I., and B.P. Buttenfield, Formalizing semantic Fabrikant, S.I., and B.P. Buttenfield, Formalizing semantic spaces for information access, spaces for information access, Annals AAGAnnals AAG, , 9191 (2), 263- (2), 263-280, 2001.280, 2001.
Skupin, A., On Geometry and Transformation in Map-Like Skupin, A., On Geometry and Transformation in Map-Like Information Visualization. In: Börner, K., Chen, C (Eds.) Information Visualization. In: Börner, K., Chen, C (Eds.) Visual Interfaces to Digital LibrariesVisual Interfaces to Digital Libraries. Lectures in Computer . Lectures in Computer Science 2539. Springer Verlag, Berlin. 161-170, 2002Science 2539. Springer Verlag, Berlin. 161-170, 2002.
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Gateway to the Literature“natural spaces”
Chen, J., C. Li, Z. Li, and C. Gold, A Voronoi-based 9-intersection model for spatial relations, Int. J. Geog. Inf. Sci., 15 (3), 201-220, 2001. - voronoi_ijgis.pdf
Chen, J., C. Qiao, and R. Zhao, A Voronoi interior adjacency-based approach for generating a contour tree, Comp. Geosci, 30, 355-367, 2004.– voronoi_contour_tree.pdf
Gold, C.M., and A.R. Condal, A spatial data structure integrating GIS and simulation in a marine environment, Mar. Geod., 18 (3), 213-228, 1995.
Mostafavi, M.A., C. Gold, and M. Dakowicz, Delete and insert operations in Voronoi/Delauney methods and applications, Comp. Geosci, 29, 523-530, 2003. - voronoi_2003.pdf
Zhang, H., and C. Thurber, Adaptive mesh seismic tomography based on tetrahedral and Voronoi diagrams: Application to Parkfield, California, J. Geophys. Res., 110 (B04303), doi:10.1029/2004JB003186, 2005. - seismic_mesh.pdf
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Dynamic Segmentationmultiple attributes to a single arc...
attribute to a portion of an arc...
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DynSeg: Measures & “Events”
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DynSeg: Point Events
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DynSeg: Single Arc, Multiple Attributes
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Heceta Bank, Oregon
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Heceta Bank Fisheries InvestigationsM.S. Theses: Nasby, 2000; Whitmire, 2003
At what scales are there quantifiable relationships between groundfish populations and seafloor morphology/texture?
What are the factors that control these relationships?
What changes may have occurred in the fish populations after a decade?
What are the characteristics and extent of natural refugia?
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EM 300 Multibeam Bathymetry
Depth Range:– 60-1000 m
Gridded to 5 and 10 m
Nasby, 2000; Whitmire, 2003
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Dives
28 ROV dives 5 submersible dives 6 historical stations
Nasby, 2000; Whitmire, 2003
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Heceta Bank Fish Habitats
Seabed Classification– Mud– Sand– Pebble– Cobble– Boulder– Flat Rock– Rock Ridge
Nasby, 2000; Whitmire, 2003
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M = Mud S = Sand P = Pebble C = Cobble B= Boulder F = Flat Rock R = Rock Ridge
12671269
1268
ID TO HABITAT TRANSECT DELTA88#1 104.85 RR 1267A 102 146.79 CC 1267A 103 251.64 RR 1267A 104 293.58 BR 1267A 105 356.49 BB 1267A 106 377.46 BB 1267A 107 419.4 CR 1267A 108 440.37 BB 1267A 109 482.31 RR 1267A 1010 482.31 SC 1267A 10
Mud
Sand
Pebble
Cobble
Boulder
Flat rock
Rock ridge
Nasby, 2000
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Bottom Type
Whitmire, 2003
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Species TypeDensity of Dover Sole
Nasby, 2000
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Other Fish Species
Greenstripe rockfish
Sablefish
Yellowtail rockfish
Shortspine thornyhead
Rex Sole
Lingcod
Pygmy rockfish
Nasby, 2000
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3 3
2
0
0.5
1
1.5
2
2.5
3
Rock Ridge Pebble/Cobble/Boulder
Mud
Rock ridge:yellowtail rockfish and juvenile rockfish
Pebble/cobble/boulder:sharpchin rockfish, rosethorn rockfish, greenstripe rockfish and pygmy rockfish
Mud:Dover sole, rex sole, sablefish and shortspine thornyhead
Habitat Characterization
Summary
Nasby, 2000
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Segue to Terrain Analysis
Whitmire, 2003
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Thesis Downloads
Nicole Nasby, 2000dusk.geo.orst.edu/djl/theses/nasby_lucas.html
(also published in 2002 issue of Fisheries Bulletin)
Curt Whitmire, 2003dusk.geo.orst.edu/djl/theses/whitmire_abs.html