Westerschelde monitoring stations

## ============================================================================
## NIOZ westerschelde monitoring stations in google maps
## data are in OceanView, called niozWS
## implemented by Karline Soetaert
## ============================================================================
 library(OceanView)
 library(RgoogleMaps)
 library(png)

# get googlemaps and plot it; create room for color key (mar)
 destfile <- "WS.png"
 MetaInfo <- GetMap(center = c(51.35, 3.97), zoom = 10, 
             maptype = "satellite", destfile = destfile)
 par (mar = c(4, 4, 4, 6))
 scatter2D(c(MetaInfo$BBOX$ll[2], MetaInfo$BBOX$ur[2]),
     c(MetaInfo$BBOX$ll[1], MetaInfo$BBOX$ur[1]), type = "n",
       xlab = expression(""^o~E), ylab = expression(""^o~N), 
       main = "Westerschelde monitoring stations",
       xaxs = "i", yaxs = "i")
 img <- as.raster(readPNG(destfile))
 rasterImage(img, xleft = MetaInfo$BBOX$ll[2], ybottom = MetaInfo$BBOX$ll[1], 
            xright = MetaInfo$BBOX$ur[2], ytop = MetaInfo$BBOX$ur[1])

# station position, and mean salinity
 stpos <- unique(data.frame(WSnioz$Station, WSnioz$Latitude, WSnioz$Longitude))
 sal <- sapply(stpos[,1], FUN = function(x) mean(WSnioz$DataValue[WSnioz$Station == x  
    & as.character(WSnioz$VariableName) == "WCSALIN" ], na.rm = TRUE))

# plot it
 scatter2D(stpos[,3], stpos[,2], colvar = sal, pch = 18, cex = 3, 
   col = jet2.col(100), add = TRUE, NAcol = "transparent", 
   clab = "psu", colkey = list(width =0.5, length = 0.5, dist = 0.1))
 text2D(stpos[,3], stpos[,2], lab = stpos[,1], add = TRUE, cex = 0.75, 
   font = 2)

scatter2D(stpos[,3], stpos[,2], colvar = sal, pch = 18, cex = 3, 
   col = jet2.col(100), add = TRUE, NAcol = "transparent", 
   clab = "psu", colkey = list(width =0.5, length = 0.5, dist = 0.1))
text2D(stpos[,3], stpos[,2], lab = stpos[,1], add = TRUE, cex = 0.75, 
   font = 2)