Dear list,
We have been developing a python application called LSMetrics to calculate 
landscape metrics for environmental management and ecological research. All 
functions/metrics use GRASS modules in the process of calculation. More 
information here:https://github.com/LEEClab/LS_METRICS/wiki

Basically we have several python functions, each of which calculates a 
different metric. All of them are then called by a single function that can 
coordinate the calculation of several metrics for several maps in a 
row.Currently the metrics can be calculated for input maps using a grafical 
interface (we call it from the GRASS shell using "python LS_metrics_v1_0_0.py") 
or by calling python shell from the GRASS shell and then using python scripting 
to call the functions (importing functions and then calling them directly). We 
wish to transform these function into one (or more than one) grass addon.
Then I have two questions:- Do you think it would be better to build a single 
addon (e.g. called r.ls.metrics) so that each metrics is defined by a parameter 
(e.g. method = "patch_size", "fragment_size", "structural connectivity" ...), 
or rather a set of addons, each one corresponding to a single landscape metrics 
(e.g. r.ls.patch_size, r.ls.fragment_size, ...)?
- Also, I have looked on how to build the addon in GRASS help pages but I am 
not sure about some details. Can you send me some references to ease that 
process?
Thanks a lot. Below you can find more information regarding the 
metrics.BestBernardo Niebuhr
_____
Metrics calculated:Metrics related to structural connectivity:- patch size- 
fragment size (excludes corridors with a given edge depth)- structural 
connectivity- proportion of habitat (within a window around each pixel)Metrics 
related to functional connectivity- functionally connected area (considering 
the capacity of organisms to cross gaps between habitat patches)- functional 
connectivityMetrics related to habitat edges- distance from edges- 
clasisfication edge/core/matrix (considering a given edge depth)- proportion of 
edge and core (within a window around each pixel)Metrics of landscape 
diversity(we are currently using the r.diversity add on to calculate that)

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