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entropy

Normalized Shannon diversity index


Description

A normalized Shannon vertical complexity index. The Shannon diversity index is a measure for quantifying diversity and is based on the number and frequency of species present. This index, developed by Shannon and Weaver for use in information theory, was successfully transferred to the description of species diversity in biological systems (Shannon 1948). Here it is applied to quantify the diversity and the evenness of an elevational distribution of las points. It makes bins between 0 and the maximum elevation. If there are negative values the function returns NA.

Usage

entropy(z, by = 1, zmax = NULL)

Arguments

z

vector of positive z coordinates

by

numeric. The thickness of the layers used (height bin)

zmax

numeric. Used to turn the function entropy to the function VCI.

Value

A number between 0 and 1

References

Pretzsch, H. (2008). Description and Analysis of Stand Structures. Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-540-88307-4 (pages 279-280) Shannon, Claude E. (1948), "A mathematical theory of communication," Bell System Tech. Journal 27, 379-423, 623-656.

See Also

Examples

z <- runif(10000, 0, 10)

# expected to be close to 1. The highest diversity is given for a uniform distribution
entropy(z, by = 1)

 z <- runif(10000, 9, 10)

# Must be 0. The lowest diversity is given for a unique possibility
entropy(z, by = 1)

z <- abs(rnorm(10000, 10, 1))

# expected to be between 0 and 1.
entropy(z, by = 1)

lidR

Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

v3.1.2
GPL-3
Authors
Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented wing2015() for segment_snags()), Bourdon Jean-François [ctb] (Contributed to Roussel2020() for track_sensor()), Gatziolis Demetrios [ctb] (Implemented Gatziolis2019() for track_sensor())
Initial release
2021-03-11

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