Update README.md

README.md

@@ -24,9 +24,18 @@ All of the scripts were developed using python 2.7.11 in a windows 10 enviroment
 
 
 #### Workflow
-All of the continious side scan sonar recordings were processed using [PyHum](https://github.com/dbuscombe-usgs/PyHum).  In the interest of space, I have not included any of the binary side scan sonar files, intermediate PyHum files, or georeferenced point clouds.  If any of those files are of interest, please contact me and I will provided them outside of this repository.  However, I have included some auxillary scripts if you need the scripts to resample the point clouds to a reqular grid and convert them to raster format in '/scripts/extra_scripts/'.  Note, you will need install [pyresample 1.1.4](http://pyresample.readthedocs.io/en/latest/). The latest version (1.1.6) at the time of writing this readme does not play nicely with scipy.  Hence, the previous version.
+All of the continious side scan sonar recordings were processed using [PyHum](https://github.com/dbuscombe-usgs/PyHum).  In the interest of space, I have not included any of the binary side scan sonar files, intermediate PyHum files, or georeferenced point clouds.  If any of those files are of interest, please contact me and I will provided them outside of this repository.  However, I have included some auxillary scripts if you need the scripts to resample the point clouds to a reqular grid and convert them to raster format in `/scripts/extra_scripts/`.  Note, you will need install [pyresample 1.1.4](http://pyresample.readthedocs.io/en/latest/) (i.e. `pip install pyresample==1.1.4`). The latest version (1.1.6) at the time of writing this readme does not play nicely with scipy.  Hence, the previous version.
 
-Begining with the side scan sonar echogram rasters in '/ss_rasters/`, you will first need to calculate GLCM texture features using `/scripts/GLCM_calc.py`.  This script will produce georeferenced GLCM texture features in the directory `/output/glcm_rasters/`.  Before any zonal statistics are calculated the GLCM texture features need to be resampled to a 3-meter resolution.  There are many ways to do this, but I reccomend using the command line utlilty [gdalwarp](http://www.gdal.org/gdalwarp.html).
+Begining with the side scan sonar echogram rasters in `/ss_rasters/`, you will first need to calculate GLCM texture features using `/scripts/GLCM_calc.py`.  This script will produce georeferenced GLCM texture features in the directory `/output/glcm_rasters/`.  Before any zonal statistics are calculated the GLCM texture features need to be resampled to a 3-meter resolution.  There are many ways to do this, but I reccomend using the command line utlilty [gdalwarp](http://www.gdal.org/gdalwarp.html). 
 
 ```
-gdalwarp -tr 3 3 -srcnodata -99 -dstnodata -99 -r average c:/workspace/ss_texture_analysis/output/glcm_rasters/R01346_R01347_3
+gdalwarp -tr 3 3 -srcnodata -99 -dstnodata -99 -r average c:/workspace/ss_texture_analysis/output/glcm_rasters/R01346_R01347_entropy.tif c:/workspace/ss_texture_analysis/output/glcm_rasters/R01346_R01347_entropy_resampled.tif
+```
+
+To simplify this procedure, I have created a bash script located at `ss_texture_analsis/scripts/resample_glcm.sh`. From a shell type,
+
+```bash
+bash c:/workspace/ss_texture_analysis/scripts/resample_glcm.sh
+```
+
+Next you will have to use the shapefiles provided in