In this post, I describe the methodology that I used while performing sea floor slope variable work on phase 2 of the BOEM aliquot grid project. As was the case for ocean depth, this was a very simple process (again, with the exception of the null problem described in the last section discussing the join process). However, I am including this write up for the sake of completeness of the work I did on the project overall. Similar to the ocean depth workflow – with the differing extents between phases 1 and 2 – the source data used here was also used on the phase 1 sea floor slope work. As such, the process described here is similar to what was carried out on phase 1. A comparison of the two extents can be found at the end of this post.
PLEASE NOTE: As all data sources/end products used/generated in this workflow are deemed public, permission to document was requested and subsequently granted.
Goal, Data Input, and Deliverables
Processing Overview
Sea Floor Slope Creation
The creation of the sea floor slope raster may have been the easiest part of the whole project!
Derive Zonal Statistics
As was the case with the ocean depth data, the Zonal Statistics as Table tool was used to derive descriptive statistics for each aliquot cell. The stat values that were acquired were minimum, maximum, range, mean, standard deviation, and sum.
Sea Floor Slope Statistics To Aliquot Grid Join
The final step for the summarized sea floor slope data was to join the data to the larger aliquot grid feature class.
Since the issue first presented itself when processing the ocean depth variable – and the same ocean depth raster was used to derive this slope raster – the problem with null values upon joining the stats table to the aliquot layer existed when processing sea floor slope as well. As previously noted, I discovered that many of the aliquots along protraction seams resulted in null values when the zonal stats tool was run. This was due to a couple reasons: The first is that there is a technical limitation in the Zonal Statistics as a Table tool where, whenever the zone boundary (in this case, aliquots) is smaller than the raster cell size that it is drawing stats from, the tool will return null for the given zone. The Esri technical document on this topic can be found here. The second issue was that, for many aliquots along the EEZ (exclusive economic zone) boundary, there was simply no slope data present. This was attributed to the extents between the layers being ever so slightly different. A workaround was developed that satisfactorily resolved these issues. I will likely do a write up on that process later.
As I mentioned at the top of this post, this task was pretty straight forward. Thanks again for taking the time to read! Thanks to Joel Osuna-Williams (CGST project manager) and Frank Pendleton (BOEM GIS analyst) for having me on the project.
Comparison of extents between BOEM aliquot grid phase 1 and phase 2 work
