Code and Data: Power laws and critical fragmentation in global forests

Source code for image processing and statistical analysis, and the patch size data files for the manuscript:<b><br></b><b>Power laws and critical fragmentation in global forests</b>. (2016) Saravia L.A. Doyle S.R. Bond-Lamberty B. bioRxiv 091751; doi: http://dx.doi.org/10.1101/091751<br>Zip Files:<br>Patch Sizes distribution by region, year and threshold from 2000 to 2015: these are binary files consisting on a vector of doubles, the R command used to read it is readBin(connection_file, "double", n = 10^8)<br><b>Africa_PatchSizes.zip</b><b>Northamerica_PatchSizes.zip</b><b>Southamerica_PatchSizes.zip</b><b>Eurasia_PatchSizes.zip</b><b>Oceania_PatchSizes.zip</b><b>Southasia_PatchSizes.zip</b><br><br><b>LargestPatchAnimations.zip</b> Animations of the two largest patches for all the regions defined in the paper. <br><b>PercolationAnimations.zip </b> Animation demonstrating percolation in a forest/non-forest model<br>R markdown files:<br><br><b>Threshold_sensitivity.Rmd</b> # Fitting heavy tails to modis VCF, Smax &amp; RSmax patch analysis. <br><b>Download_modis.Rmd</b> # Download modis files MOD44B version 051<b><br></b><b>Map_study_areas.Rmd</b> # Generate maps of study areas <b><br></b><b>Map_Max_patches.Rmd</b> # Generate GIF animations of maximum patch dynamics <br>R Files<b><br></b><b>map_fun.r </b># Map raster functions<b>power_fun.r </b># Function to fit continuos heavy tail distributions<br>MATLAB Files<br>Extract patch sizes from bin, and other analysis not used in the paper<br><b>data_input_script.m</b><b>GCF_spatial_analyses.m</b><b><br></b>PYTHON Files<br><strong>powlawfit.py :</strong> Call the Python powerlawpackage from command line <br><br><br> DATA Tables: csv and tab separated text files with model fits for the patch size distribution models.<br><strong>Fitted_Patch_models.csv</strong><strong><strong>Fitted_Patch_models.txt</strong></strong><strong><strong><br></strong></strong><strong><strong><br></strong></strong><br>