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