Statistics – Computation
Scientific paper
Dec 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001agufm.p42a0567a&link_type=abstract
American Geophysical Union, Fall Meeting 2001, abstract #P42A-0567
Statistics
Computation
5464 Remote Sensing, 5494 Instruments And Techniques, 6225 Mars
Scientific paper
The Mars Orbiter Laser Altimeter (MOLA) instrument on the Mars Global Surveyor (MGS) spacecraft has returned a large amount of data on the topography of Mars. It is possible to generate high-resolution Digital Elevation Models (DEMs) from this data by employing data interpolation techniques. Four interpolation algorithms were selected to be tested on MOLA data: Delaunay-based Linear Interpolation, Splining, Nearest Neighbor (or Inverse Distance Weighting), and Natural Neighbor. These methods were applied to the MOLA data of Korolev crater (a large crater in the north polar region of Mars) for qualitative analysis. In addition, a known DEM of a part of Iceland was used for both qualitative and quantitative testing. The quantitative testing was conducted by simulating MOLA data acquisition, interpolating that data, and then calculating the mean absolute error (MAE) between the interpolated DEM to the original DEM. Also, execution speeds were measured for the four algorithms. The Natural Neighbor method appears to be superior both quantitatively and qualitatively to other methods tested, but is relatively slow computationally. The Natural Neighbor algorithm was also applied to the MOLA data of potential Mars Exploration Rovers (MERs) landing sites. >http://pirl.lpl.arizona.edu/~abramovo/MOLA_interpolation/ interpolation.html
Abramov Oleg
McEwen Alfred S.
No associations
LandOfFree
An Evaluation of Interpolation Methods for MOLA Data does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with An Evaluation of Interpolation Methods for MOLA Data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and An Evaluation of Interpolation Methods for MOLA Data will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1239543