NDLI: Recipes for Spatial Statistics with Global Datasets: A Martian Case Study

Content Provider	Springer Nature Link
Author	Karunatillake, Suniti Squyres, Steven W. Gasnault, Olivier Keller, John M. Janes, Daniel M. Boynton, William V. Finch, Michael J.
Copyright Year	2010
Abstract	The Mars Odyssey Gamma Ray Spectrometer has yielded planetary data of global extent. Such remote-sensing missions usually assign the value of a continuous-valued geospatial attribute to a uniform latitude-longitude grid of bins. Typical attributes include elemental-mass fraction, areal fraction of a mineral type, areal fraction of rocks, thermal inertia, etc. The fineness of the grid is chosen according to the spatial resolution of the orbiter and concomitant data processing. We describe methods to maximize the information extracted from both bin and regional data. Rigorous use of statistical parameters and related methods for inter- and intra- regional comparisons are also discussed. While we discuss results from the Mars Odyssey mission, the techniques we describe are applicable whenever continuous-valued attributes of a planet’s surface are characterized with bins and regions. Our goal is to distill the simplest statistical methods for regional comparisons that would be intuitively accessible to planetary scientists.
Starting Page	439
Ending Page	451
Page Count	13
File Format	PDF
ISSN	08857474
Journal	Journal of Scientific Computing
Volume Number	46
Issue Number	3
e-ISSN	15737691
Language	English
Publisher	Springer US
Publisher Date	2010-08-21
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mars odyssey ESDA Spatial autocorrelation K-S Kolmogorov-Smirnov Planetary exploration GIS Planetary data Mars science laboratory MESSENGER Chandrayaan Theoretical, Mathematical and Computational Physics ApplicationMathematics/Computational Methods of Engineering Computational Mathematics and Numerical Analysis Algorithms
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Theoretical Computer Science Engineering Computational Theory and Mathematics Computational Mathematics Numerical Analysis Software

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