This article expands on "Analyzing risk index using habitat connectivity" from [@geohabnet] to demonstrate one example on how parameters can be customized to calculate centrality and it's implication in the results.
Package installation -
if (!require("geohabnet")) { utils::install.packages("geohabnet") } library(geohabnet)
Getting the host density
avocado_mon <- geohabnet::cropharvest_rast("potato", "monfreda")
Running Sensitivity Analysis
avocado_result <- geohabnet::msean(avocado_mon, global = TRUE, link_threshold = 0.000001, inv_pl = list(beta = c(0.5), metrics = c("betweeness"), weights = c(100), cutoff = -1), res = 24, neg_exp = list(gamma = c(0.1), metrics = c("betweeness"), weights = c(100), cutoff = -1))
It is important to note that Betweenness centrality is a time intensive operation. Geohabnet uses a wrapper around igraph::betweenness()
. Refer to [@igraph] for more details and further reading. The cutoff
parameter can be used set the threshold which will include the link weights based on this threshold. Setting this parameter will also be reflected in closeness.
The configuration based run for the above will be as follows -
get_parameters() -> modify values in parameters.yaml -> set_parameters() -> run sensitivity_analysis()
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