Abstract

Currently R is the most popular software for data analyses among biologists. Here, we present bwimage, a package designed to describe patterns from black and white images. The package can be used for a wide range of applications. We implemented functions previously described in the literature to calculate parameters designed originally, but not exclusively, for vegetation structures. Additionally, we propose a new parameter: the aggregation index. We demonstrate applications for field work, providing examples that range from calculation of canopy openness, description of patterns in vertical vegetation structure, to patterns in bird nest structure. We provide advice and illustrated examples of how to produce high quality images for analyses.

Highlights

  • 23 Jul 2019 report report reportAfter Dr Francesco Chianucci comments, we have released a new version (1.2) of the bwimage package published in CRAN where: i) two new functions (stretch and compress functions) were introduced to provide an additional tool to distort images

  • The facility to obtain high quality digital images creates the opportunity to measure natural variables using image analyses

  • If the user is not acquainted with scale and threshold processing and/or images were captured under different light conditions, we recommend the scale and application of threshold algorithms in a native image editor software, such as GIMP6, and subsequent usage of the resulting images with the bwimage package

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Summary

23 Jul 2019 report report report

After Dr Francesco Chianucci comments, we have released a new version (1.2) of the bwimage package published in CRAN where: i) two new functions (stretch and compress functions) were introduced to provide an additional tool to distort images. These functions are applications of algorithms for mapping images from circle to square, and vice versa, adapted from Lambers (2016 J of Computer Graphics Techniques); and ii) included the possibility of users processing single channel images. Any further responses from the reviewers can be found at the end of the article

Introduction
Methods
Conclusions
R Core Team
14. Deeming DC

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