Started with SXP files that were the output from A 234 kHz Interferometric Submetix Swath Bathy Sonar System. Based on the Julian date at original data collection, individually imported each raw backscatter file into "SEA Swath Processor Real-Time Software System". Configured the way the data was processed in "SEA Swath Processor" by inputting adjustment and offset information, such as ship's motion, tides, velocity of sound, and relative sensor positions.
Used the "SonarWiz.MAP Sonar File Manager" tool: check and correct the navigation data. Manually "bottom-tracked" each line. Applied signal processing functions by setting the Automatic Gain Control (AGC), Beam Angle Correction (BAC), project sonar data using sensor headings. Individually exported the line as a GeoTif file.
Looped through the directory of GeoTif files and
convert GeoTif to ArcGIS raster format.
Removed "NoData" raster cells
using the ArcGIS Con statement; and
projected the data to WGS 1984 UTM Zone 11.
**** Ascii to ArcRaster & Project Pyramids (Python Script)****
# ---------------------------------------------------------------------------
# ascii_to_arcraster_project_pyramids_stand_alone.py
# Created on: Tuesday Oct 04 2006
# Nadine Golden
# ---------------------------------------------------------------------------
# Import system modules
import glob, sys, string, os, win32com.client
# Create the Geoprocessor object
gp = win32com.client.Dispatch("esriGeoprocessing.GpDispatch.1")
# Load required toolboxes...
gp.AddToolbox("E:/ArcGIS/ArcToolbox/Toolboxes/Data Management Tools.tbx")
gp.AddToolbox("E:/ArcGIS/ArcToolbox/Toolboxes/Conversion Tools.tbx")
files = glob.glob("F:/test/grids/*asc")
for file in files:
(basename, ext) = os.path.splitext(file)
ingrid = file
outgrid = basename + "tmp"
os.system("scii_to_arcraster_project_pyramids_stand_alone.py %s %s" % (ingrid, outgrid))
# Process: ASCII to Raster...
gp.ASCIIToRaster_conversion(ingrid, outgrid, "INTEGER")
## # Process: Define Projection...
## gp.DefineProjection_management(outgrid, "PROJCS['NAD_1983_UTM_Zone_11N',GEOGCS['GCS_North_American_1983',DATUM['D_North_American_1983',
SPHEROID['GRS_1980',6378137.0,298.257222101]],
PRIMEM['Greenwich',0.0],
UNIT['Degree',0.0174532925199433]],
PROJECTION['Transverse_Mercator'],
PARAMETER['False_Easting',500000.0],
PARAMETER['False_Northing',0.0],
PARAMETER['Central_Meridian',-117.0],
PARAMETER['Scale_Factor',0.9996],
PARAMETER['Latitude_Of_Origin',0.0],
UNIT['Meter',1.0]]")
# Process: Project Raster...
finalgrid = basename
gp.ProjectRaster_management(outgrid, finalgrid, "PROJCS['WGS_1984_UTM_Zone_11N',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',
SPHEROID['WGS_1984',6378137.0,298.257223563]],
PRIMEM['Greenwich',0.0],
UNIT['Degree',0.0174532925199433]],
PROJECTION['Transverse_Mercator'],
PARAMETER['False_Easting',500000.0],
PARAMETER['False_Northing',0.0],
PARAMETER['Central_Meridian',-117.0],
PARAMETER['Scale_Factor',0.9996],
PARAMETER['Latitude_Of_Origin',0.0],
UNIT['Meter',1.0]];
-10000 -10000 100000;0 100000;0 100000", "NEAREST", "1")
# Process: Build Pyramids...
gp.BuildPyramids_management(finalgrid)
# Clean up the mess
gp.Delete(outgrid)
Looped through the directory arcgrids and
normalized the backscatter values
using the Python script "RasterStats.py".
**** Rasters Statistics for Normalizing Data (Python Script)****
# ---------------------------------------------------------------------------
# RasterStats.py
# To Calculate the mean value of a raster
# Created on: Thursday Oct 20, 2006
# Nadine Golden
# ---------------------------------------------------------------------------
# Import system modules
import sys, string, os, win32com.client
# Create the Geoprocessor object
gp = win32com.client.Dispatch("esriGeoprocessing.GpDispatch.1")
# Check out any necessary licenses
gp.CheckOutExtension("spatial")
# Load required toolboxes...
gp.AddToolbox("E:/ArcGIS/ArcToolbox/Toolboxes/Spatial Analyst Tools.tbx")
gp.AddToolbox("E:/ArcGIS/RasterStatsTool/RasterStatistics.tbx")
#Directory of grids
gp.Workspace = "F:\\test"
rasterlist = gp.ListRasters()
name = rasterlist.Next()
while name:
print name
# Process: RasterBand Statistics...
mean = gp.RasterBandStatistics(name, "MEAN")
print mean
# Process: Minus...
(indir,basename) = os.path.split(name)
outgrid = os.path.join("F:\\test\\Normalized", basename)
gp.Minus_sa(name, mean, outgrid)
print outgrid
name = rasterlist.Next()
In ArcGIS, imported lines according to track line number and mosaiced adjacent backscatter lines. Mosaicing was done by manually drawing a mask around the best possible data for each line and it's overlapping lines. Best possible data was determined subjectively and included the least no data values as possible in the overlapping areas.