analyzepsat: Microwave Telemtry PSAT analysis

Description Usage Arguments Details Value Author(s) See Also

Makes a dataframe for bathymetric and/or longitudinal sst correction. This format is also useful for export to Excel, ArcMap, or other software. This does not currently work with trackit but future versions will have this capability.

1	prepb(kfit, prepf, fill.sst = F, span = NULL)

`kfit`	A fitted object returned from kftrack, ukfsst, kfsst
`xtrack`	The original input dataframe to kftrack, ukfsst or kfsst
`fill.sst`	Logical. Should days with missing SST be interpolated? If TRUE, loess smoothing is applied.
`span`	span, or bandwidth, for loess smoothing if fill.sst = TRUE

LOESS smoothing is more accurate the less data is missing. Bandwidth is always an important consideration and should be reduced if there is a long time series with relatively little missing data. It is also worth noting that interpolating SST, which is most cases is considered the maximum temperature per day, will be biased towards colder regions if the fish is consistently deep over the measured time period.

A dataframe with columns for Year, Month, Day, V11, V12, V21, V22, Longitude, Latitude, Maxdepth and Max Temp

Benjamin Galuardi

prepf,make.btrack

galuardi/analyzepsat documentation built on May 17, 2019, 3:25 p.m.