Hi
I'm working on a GIS project to figure out if rarity of lichens species is connected with environmental conditions and to find the areas in which rare lichen species could live using parameters such as: average annual temperature (°C), rain (mm/y), insolation, TWI (Topographic wetness index), slope and exposition.
To find the rarity I used an index called TLR (Total Lichen Rarity).This index is a calculate as:
LR=(x1*x2 ..*.xn)*m
where x=numer of individuals of a rare species
m=number of total species per sampled point.
There are 3 to 6 samples per location with a different score of LR each.
The sum of the total LR score per location equal the TLR.
I thought to 2 options:
1. Using the map algebra. Extrapolate the raster values in the points where I have the TLR and use these values to find the not sampled areas in which there are the same or higher scores.
2. Using random tree forest algorithm.However I don't know if this could be a proper solution.
Could you suggest or recommend me one of these methods or a new approach?
Thank
Manuel Tiburtini
Below the map of the TLR scores and the temperature. Higher is the TLR index, more red will be the point.
That what you ask, is a good idea, but I think that you have to do it, with native trees.
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