This function is a wrapper function for all of the metrics. It calculates each metric for an input lakeMorphoClass. This returns a list of all metrics
calcLakeMetrics(
inLakeMorpho,
bearing,
pointDens,
slope_quant = 0.5,
correctFactor = 1,
zmax = NULL
)
Returns a list with all lake metrics calculated for a given input lakemorpho object
an object of lakeMorphoClass
. Output of the
lakeSurroundTopo
function would be appropriate as input
Numeric that indicates the bearing of the desired fetch.
Number of points to place equidistant along shoreline for
lakeMaxLength
or density of lines to test for
lakeMaxWidth
and lakeFetch
.
The slope quantile to use to estimate maximum depth. Defaults to the median as described in (Hollister et. al, 2011).
Value used to correct the predicted maximum lake depth. Defaults to 1. Corrections are simply accomplished by multiplying estimated max depth by correction factor. Correction factors can be determined empirically by regressing the predicted depth against a known maximum depth while forcing the intercept through zero. The slope of the line would then be used as the correction factor(Hollister et. al, 2011).
Maximum depth of the lake. If none entered and elevation dataset
is inlcuded in inLakeMorpho, lakeMaxDepth
is used
to estimate a maximum depth.
Florida LAKEWATCH (2001). A Beginner's guide to water management - Lake Morphometry (2nd ed.). Gainesville: Florida LAKEWATCH, Department of Fisheries and Aquatic Sciences. Link
Hollister, J. W., W.B. Milstead (2010). Using GIS to Estimate Lake Volume from Limited Data. Lake and Reservoir Management. 26(3)194-199. tools:::Rd_expr_doi("10.1080/07438141.2010.504321")
Hollister, J. W., W.B. Milstead, M.A. Urrutia (2011). Predicting Maximum Lake Depth from Surrounding Topography. PLoS ONE 6(9). tools:::Rd_expr_doi("10.1371/journal.pone.0025764")
# \donttest{
data(lakes)
calcLakeMetrics(inputLM, bearing = 45, pointDens = 25)
# }
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