I am examining rodent captures on six permanent rodent trapping grids measuring 150 x 150 meters and consisting of 121 trap stations evenly spaced 15 meters apart. There are six such trapping grids on the study site that is < 1000 hectares in size. I would like to interpolate the capture data to create a Kriged surface of rodent activity. An assumption of interpolation is that the data are stationary.
stationarity is required for making inferences from a model that characterizes the process of the spatial structure of data at locations that are not sampled.
From what I understand, a process can be described as stationary when its statistical properties (mean and variance) do not vary across space.
But isn't variation across space why we conduct spatial analysis in the first place?
Stationarity is very often introduced in the spatial/geostatistical analysis literature but, I have yet to find solid direction and information about
- what scale, or for which types of studies, it is reasonable to assume your data are stationary,
- how to examine and verify data are stationary, and lastly,
- once quantified in some way just how much difference from one area to the next area qualifies your data as non-stationary?
Thus far after reviewing the literature the concept and the examination of stationarity seems highly subjective, arbitrary and/or obfuscated.
If anyone can provide some practical advice with this problem I'd greatly appreciate it!