alexa CMEIAS Quadrat Maker: A Digital Software Tool to Optimize Grid Dimensions and Produce Quadrat Images for Landscape Ecology Spatial Analysis
ISSN: 2157-7625

Journal of Ecosystem & Ecography
Open Access

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Research Article

CMEIAS Quadrat Maker: A Digital Software Tool to Optimize Grid Dimensions and Produce Quadrat Images for Landscape Ecology Spatial Analysis

Frank B. Dazzo* and Colin Gross

Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, USA

*Corresponding Author:
Frank B Dazzo
Department of Microbiology and Molecular Genetics
Michigan State University, East Lansing
Michigan 48824 USA
Tel: 517-884-5394
E-mail: [email protected]

Received date: July 15, 2013; Accepted date: September 10, 2013; Published date: September 12, 2013

Citation: Dazzo FB, Gross C (2013) CMEIAS Quadrat Maker: A Digital Software Tool to Optimize Grid Dimensions and Produce Quadrat Images for Landscape Ecology Spatial Analysis. J Ecosys Ecograph 3:136. doi:10.4172/2157-7625.1000136

Copyright: © 2013 Dazzo FB, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and and source are credited.

Abstract

This paper describes CMEIAS Quadrat Maker, a new digital computing tool designed to alleviate the nontrivial
problem of optimizing the grid-lattice dimensions and automating the production of size-optimized quadrat
images for plot-based spatial pattern analysis in landscape ecology. The program is written for 32-bit and 64-bit
Window’s operating systems and handles both 8-bit grayscale and 24-bit color input images. Following a brief user
interaction, the software application transforms a copy of the input landscape image into an annotated, color index
image with optimized grid overlay and column-row labeling of individual quadrats, cuts a copy of the landscape
image into quadrats defined by the optimized grid raster, and then saves each individual quadrat image with a
file name indicating its unique location within the landscape domain, now ready for stack building and automated
image analysis. Version 1.0 of this computing technology is implemented into a software package containing the
executable file, user manual and tutorial images that will be freely available at https://cme.msu.edu/cmeias/. This
new computing technology will facilitate quadrat-based analyses of how spatial patterns vary with the scale at which
they are measured, and will also strengthen microscopy-based approaches for understanding the spatial ecology of
microbial biofilm communities.

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