I am trying to virtually put a blanket over a DEM so to say, in more technical terms, a convex hull over 3d point data. To get some insight in what I'm doing exactly, I will first explain my entire plan so it becomes clear what the purpose of the convex hull is.
I am trying to detect sand bars close to the shore of the Netherlands. I have point measurements of the depth and may plan is as follows: first I remove the slope of the coast, secondly I invert the DEM and lastly I use ArcGIS' hydrology toolset to find the spots in the landscape where water will accumulate, these areas are my sand bars.
Here is a sample of my point data. It's transects from a part from the coast. And here is what I would like to to visually:
The order of the three images is arbitrary. I realised after making this image, it's also possible to first remove the angle and than invert it.
My question right now is that in order to remove the slope, my plan is to create a convex hull over the DEM, which would look like putting a blanket over the 3d landscape (enclosed on the bottom, but this is not relevant for me). After this I will subtract the point measurements form this straight slope, resulting in a flat landscape with indentations in it. Does anybody know of a python, arcgis or qgis library or tool that could do this? I have been looking at ArcGIs' minimum bounding geometry, but this only works for 2d data. R's Convhulln might work, but there might work, but I'd rather find something in Python.