The following function matrix.poly allows for the addition of polygons to a plot based on a matrix and defined matrix positions. I have used this function on occasion to highlight specific matrix locations (e.g. in the above figure). You can do the same by overlaying another image (left in above plot) but with this function you will have all other polygon plotting possibilities (e.g. borders etc.).
Friday, April 27, 2012
Thursday, April 19, 2012
Adding a transparent image layer to a plot
Monday, April 2, 2012
Working with Globcolour data
The Globcolour project (http://www.globcolour.info/)
provides relatively easy access to ocean color remote sensing data. Data is
provided at http://hermes.acri.fr/
and the following parameters are available:
· Chlorophyll-a (CHL1 and CHL2)
· Fully normalised water leaving radiances at 412, 443, 490,
510, 531, 550-565, 620, 665-
670, 681 and 709 nm (Lxxx)
· Coloured dissolved and detrital organic materials
absorption coefficient (CDM)
· Diffuse attenuation coefficient (Kd(490))
· Particulate back-scattering coefficient (bbp)
· Total Suspended Matter (TSM)
· Relative excess of radiance at 555 nm (EL555)
· Photosynthetic Available Radiation (PAR)
· Heated layer depth (ZHL)
· Secchi disk depth (ZSD)
· Primary production (PP)
· Aerosol optical thickness over water (T865)
· Cloud Fraction (CF)
Of particular interest to ecologists are the estimates of Chlorophyll a (chla) , which combines data from several satellites for better coverage - SeaWiFS (NASA), MODIS (NASA), MERIS (ESA). Data is available
at several temporal (daily, 8-days, and monthly averages) and spatial (4.63 km,
0.25°, and 1°) resolutions for the global domain. Several merged products are available: simple averaging (AV), weighted averaging (AVW), and Garver, Siegel, Maritorena Model (GSM) [for more information see the Product User Guide].
Due to the gappy nature of the data (e.g. due to land and clouds), many of the data products only provide values at grids where estimation was possible. For high resolution data, such as in 4.63 km resolution daily estimates, grids with values are often far fewer than the total number of ISIN grids (n=23,761,676) used by the product. This saves space in the files for download, but you may need to reconstruct the field (with NaN's included for grids without observations) for some analyses.
Due to the gappy nature of the data (e.g. due to land and clouds), many of the data products only provide values at grids where estimation was possible. For high resolution data, such as in 4.63 km resolution daily estimates, grids with values are often far fewer than the total number of ISIN grids (n=23,761,676) used by the product. This saves space in the files for download, but you may need to reconstruct the field (with NaN's included for grids without observations) for some analyses.
The following example shows how to retrieve Globcolour data
and process it using R. Global data is available, but I have provided
instructions for processing a smaller area of 4.63 km resolution chla data from
the Galapagos archipelago. One can define lat/lon limits for the desired area on the http://hermes.acri.fr/ interface. An ftp address will be sent via Email as to the location of the data when finished.
Labels:
chlorophyll,
climate science,
gappy data,
map,
map projection,
netcdf,
ocean color,
phytoplankton,
R,
remote sensing,
sparse data,
spatial
Add a frame to a map
Here is a function that adds a frame of alternating colors to a map (un-projected). One defines the extension of each bar (in degrees) and an optional width of the bars (in inches). It uses the "joinPolys" function of the package to trim the bars near the map corners where the axes meet.
the map.frame function:
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