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Kernel estimation as a basic tool for geomorphological data analysis

Cox, N.J.

Authors



Abstract

Kernel estimation, based on the convolution of a probability density function with a set of magnitudes or event dates, provides tuneable smooth pictures of probability density functions and event intensity functions. Such pictures are in several respects superior to those provided by histograms, box plots, cumulative distributions or raw plots. They permit examination of broad features and fine structure, are readily produced with modest computational effort and are essentially free of artefacts arising from binning. Examples are given using data on cirque lengths, limestone pavements, glacier areas and dated flood deposits. The technique deserves widespread use in geomorphology and allied sciences.

Citation

Cox, N. (2007). Kernel estimation as a basic tool for geomorphological data analysis. Earth Surface Processes and Landforms, 32(12), 1902-1912. https://doi.org/10.1002/esp.1518

Journal Article Type Article
Publication Date 2007-10
Deposit Date Feb 13, 2008
Journal Earth Surface Processes and Landforms
Print ISSN 0197-9337
Electronic ISSN 1096-9837
Publisher British Society for Geomorphology
Peer Reviewed Peer Reviewed
Volume 32
Issue 12
Pages 1902-1912
DOI https://doi.org/10.1002/esp.1518
Keywords Density estimation, Intensity estimation, Kernel estimation, Probability distributions, Time series.


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