I am attempting to interpolate sediments across an area with data from 3 sources using ArcGIS 10.3.
All three sources divide sediments into percentages of mud, sand or gravel.
Two sources come from actual sediment cores where grain size was analyzed in the lab.
The third comes from annotated photographs where a person estimates the % cover of each sediment type while viewing a photo of the seafloor. The annotated photographs are understandably much less precise than the grain size analysis.
I have more data points from the annotated photos than the grain size analysis.
All percentages were converted into decimals before using geostatistical analyst to interpolate using ordinary kriging.
I will be repeating these steps for each sediment type (mud, sand, gravel).
Is it more appropriate to combine all data points into one data set and krig together, or is it better to use co-kriging and add each data-set as a separate layer/variable?
It seems like a gray area since the data are all either percent mud, sand or gravel but since some are collected with different methods, I could see using them as different variables.