boaR-package: The Belkin-O'Reilly front detection algorithm.

In galuardi/boaR: BOA front detection

Description

Belkin-O'Reilly routine for detecting fronts from sea surface temperature and chlorophyll (and probably other) satellite imagery.

Details

Package:	boaR
Type:	Package
Version:	1.0
Date:	2012-01-02
License:	GPL (>= 2)
LazyLoad:	yes

This package works on satellite imagery imported into R. This package contains three functions which iteratively perfom median filtering and front detection. This is a port from IDL code which operated on flat binary files directly. It is easiest (in my opinion) to import satellite data into R as a netcdf file using the raster package.

Author(s)

Benjamin Galuardi

[e-mail]

References

Belkin, I. M. & O'Reilly, J. E. An algorithm for oceanic front detection in chlorophyll and SST satellite imagery. Journal of Marine Systems, 2009, 78, 319 - 326

Examples

library(boaR)

# some good color ramps for gradient mapping
chlgradcol =   colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan","#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"), interpolate = 'spline', bias = 2.0)
sstgradcol =   colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan","#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000"), interpolate = 'spline')

# load some satelite data originally downloaded here (as a netcdf file):  http://coastwatch.pfeg.noaa.gov/erddap/griddap/index.html
data(satdata)

# Blended SST image
x11()
tfront = boa(sst$lon, sst$lat, sst$DATA, direction = T)
par(mfrow=c(1,2))
plot(tfront[[1]])
title('Direction')
plot(tfront[[2]], col = sstgradcol(100))
title('Gradient Magnitude')

# SeaWifs chlorophyll image
x11()

cfront = boa(swchl$swlon, swchl$swlat, log(swchl$chl), direction = T)  # be sure to take the log of the chl 
par(mfrow=c(1,2))
plot(cfront[[1]])
title('Direction')
plot(cfront[[2]], col = chlgradcol(100))
title('Gradient Magnitude (Ratio)')

galuardi/boaR documentation built on May 16, 2019, 5:37 p.m.