The Bayesian classifier function in the dissertation results - Part 2: getting the Souness catalogue into shapefile form

In order to focus on the areas of the Souness et al. 2012 glacier-like forms, I first needed to get the actual areas of interest as shapefiles.

I wrote some really not very good Python code to get the information from the Souness catalogue (a .csv exported from a spreadsheet which is available as a supplement from the paper itself) and then convert the coordinates of the GLF head, centre, terminus and left/right mid-channel from lat/long to an equicylindrical coordinate system with a standard parallel of 40°.

The Nilosyrtis Mensae area is fairly densely populated with Souness GLFs.

I have uploaded the code itself to my Bitbucket repository: bitbucket.org/davidtreth/marsglaciers

A flowchart from my dissertation showing the usage of shapefiles of the Souness objects to create zonal statistics.

Later on in the process, these are intersected with the segmented DEM to find out zonal statistics on the subset of DEM segments that intersect with the Souness GLFs.

While digging around in the scripts I found that I in fact lost the script that actually did the zonal statistics for each DTM tile. I will have to rewrite it from a related one in the backups.

I used one script to loop through each of the HRSC fields and do zonal statistics with the GLF shapefiles. This produced a .csv file in the directory of each tile, and I used a further script to gather them all together into a single .csv file using the manually specified HRSC tile for each field.


Meanwhile, I recently adapted the script that made the Souness regions of interest, to make a series of intermediate areas along the midpoint of the glacier. :

A series of GLFs along the northern wall of Greg crater, with intermediate points along them, that could be useful for making approximate profiles, provided I can manage the rather opaque Python code involved in making the zonal statistics.