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Spatial Indexing of Large Volume Bathymetric Data. by Bradford G. Nickerson University of New Brunswick Faculty of Computer Science Fredericton, New Brunswick Canada joint work with Feng Gao. Bathymetric Data Observation. Simrad ME70 transducer array. Frequency range: 70 to 120 kHz

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spatial indexing of large volume bathymetric data

Spatial Indexing of Large Volume Bathymetric Data

by

Bradford G. Nickerson

University of New Brunswick

Faculty of Computer Science

Fredericton, New Brunswick

Canada

joint work with Feng Gao

bathymetric data observation
Bathymetric Data Observation

Simrad ME70 transducer array

Frequency range: 70 to 120 kHz

800 Tx + 800 Rx channels

summary
Summary
  • R-tree average 4.6 times less time to search R-tree indices (compared to Morton code)
  • Space requirement about 1.8% of original data size
  • Range deletion average 17 times faster compared to original R-tree deletion
  • RDBMS (INGRES) took an average of 1,535 times more CPU time for search, 4.5 times more space
slide10

Curse of Dimensionality

  • k-d tree range search time O(n1-1/d+F), where F is the number of points in range [Lee and Wong, 1977]

For uniform, random points in [0,1]d, query square W with side length ,  = d-th root of E(F)/n.

e.g. E(F)/n=0.001,

for d=2, =0.0011/2=0.03;

for d=20, =0.0011/20=0.79