I have some plots of land spread across the landscape. Sometimes a parcel is subdivided in different sectors. For each parcel (and, in case of subdivision, for each sub-section) the quality of agricultural yield is known - binary coded as good or bad.
With the ultimate goal to assess what topographic/environmental IV (say, slope, elevation, distance from water reservoirs, etc) may have influenced the binary DV (by using Logistic Regression), I am wondering what could be a sound sampling strategy.
The starting point would be to draw a number of points within the parcels, then for each of them record the value of the DV (whether the quality is optimal or not) and the values of the IVs.
- I am unsure which is (more) correct: (a) to draw equally-spaced points or (b) to draw random distributed points?
- In either approach, since the total area of good quality land is not equal to the total area of bad land, should the number of (random?) points be equal across the two qualities, or proportional to the size of each area?