Creating a Satellite Composite Basemap

This example utilizes DEM topography data 5 minute topography data to create a composite satellite basemap. It is similar to the Land/Sea mask example, but adds the use of a higher resolution topographic data set.

Tools Used

Gempak Programs

Data Used

Steps

  1. Create a topographic grid for desired area using GDTOPO 
      
    GDFILE   = south_america_topo5.gem
    GAREA    = -60;-105;30;-20
    GDATTIM  = 070101/0000
    TOPOFL   = dem5
    GEMPAK-GDTOPO>r


    GDTOPO PARAMETERS: 

    Grid file:       south_america_topo5.gem                                                                                                         

    Topography file: /home/gempak/GEMPAK5.10.2/gempak/tables/unidata/world_topo.5min                                                                 

    GAREA:              -60;-105;30;-20                                 
    Lower left corner:     -60.0000  -105.0000
    Upper right corner:     30.0000   -20.0000
   
    Number of X/Y grid points:   1020  1080
        Number of Grid points:      1101600

    Minimum and Maximum values -8139.00  6212.00
  2. Convert current IR satellite image to grid using IMG2GD 
      
    PROJ     =  
    GRDAREA  =  
    KXKY     =  
    GRDNAM   = irsat
    GDFILE   = south_america_irsat.gem
    GLEVEL   = 0
    GVCORD   = none
    GDATTIM  = 070525/1545
    CPYFIL   = south_america_topo5.gem
    MAXGRD   = 200
    IMGFIL   = $SAT/GOES-12/4km/IR/IR_20070525_1545
    IMGTIM   = last
    CALIMG   = no
    GEMPAK-IMG2GD>r
    satellite image date/time 070525/1545
  3. Create a composite image from grids of satellite and topography using GD2IMG
    • Use IRSAT values where brightness value is greater than 112 (eg 113 to 255, or colder than 0C). Subtract 112 from pixel values to produce values from 1 to 143 and set remaining values to 1.
    • Create a 0/1 boolean grid of land/sea.
    • Multiply the boolean 1/0 grid by 143 and add to the transformed IRSAT values as above.
    • The result is a grid of values ranging from 1 to 143 over land and 144 to 286 over the ocean.
    • Store the image as a gini image (mercator projection 870 x 1090 calculated for pixel size).
    • Use a calibration range for band 10 for colors 0 to 94 representing pixel values 0 to 286. 
          GDATTIM  = last
    GDFILE   = south_america_irsat.gem + south_america_topo5.gem
    GLEVEL   = 0
    GVCORD   = none
    GFUNC    = add(mul(bool(slt(topo%pres^070101/0000+2,0)),143),miss(sub(sgt(irsat,112),112),1)
    SCALE    = 0
    PROJ     = mer
    GRDAREA  = -60;-105;30;-20
    KXKY     = 870;1090
    CPYFIL   =  
    SATFIL   = south_america_satbase.gini
    CALINFO  = 99/10/SAT,0,94,0,286
    WMOHDR   = TICZ99/CHIZ/
    GEMPAK-GD2IMG>r
  4. Create a color lookup table representing land, ocean, and shades of IRSAT clouds for the 2 ranges of data above. The color values 0 to 94 will be divided into 2 groups of 47 with the last color entry representing missing data. Each section of 47 colors will start with the color for land or ocean and end with the maximum value of white (RGB 255,255,255). The remaining colors will be evenly ramped from the starting color to the ending color (a short program saved time for this step). You can download the color table upc_t_s.tbl generated for this composite satellite image.
  5. Add an image type entry for this band 2**(10 - 1) image for sensor 11 (Gini ID 99 above) into GEMTBL/sat/imgtyp.tbl if it does not already exist. 
       IRSAT-BASE           COMPOS        0     94     11   2**9      1 upc_t_s.tbl
  6. Display the composite image in GEMPAK programs as a satellite image and overlay data as desired. 
      
    MAP      = 1
    GAREA    = dset
    PROJ     = sat
    SATFIL   = south_america_satbase.gini
    LUTFIL   = upc_irsatbase.tbl

  7. To create a realtime product, schedule the conversion of the IR image to grid and generation of the composite image using the previously generated topography grid.