Table of Contents
As a start, we want to demonstrate the how to use MB-System™ to survey a data set, without any special processing. This chapter might by skipped by more experienced users, but it is a good place to start for those new to sonar data processing and MB-System™.
The standard MB-System™ distribution comes with an archive of example data sets and scripts generated using MB-System™ (MB-SystemExamples.X.Y.Z.tar.Z). When uncompressed and un-archived, the resulting directory tree will resemble the lines below.
[vschmidt@val-LDEO mbexamples]$ ls data mbbath mbgrid mbinfo mblist mbm_plot README xbt
The ~/data directory contains several sample data files used in some of the examples in this chapter an the next. The other directories contain scripts that demonstrate the use of several of the tools in MB-System™ .
For the purposes of the MB-Cookbook examples, a directory called ~/mbexamples/cookbook_examples has been created. While some of the data sets provided in the mbexamples archive will be used in these illustrations, other data sets have been chosen to augment them. These data sets have been placed in ~/mbexamples/cookcook_examples/other_data_sets.
It is common when working within a survey, to want to plot the whole thing, and then take a closer look at a few particular points of interest. "Lets look at the data around this sea mount!" "How about a plot of yesterday's data." "What about a plot of the old data, with the new data." We can do all this with mbdatalist.
While this chapter covers the processing of a single survey, Chapter 4 will explain how to organize the data from several surveys, or even several cruises, into a larger archive. Managing large data sets of this type is greatly simplified with recursive data lists created by mbdatalist.
We will first use mbdatalist to create a master file list of all the files in the survey. This list will have proper relative references, will contain the MBIO format of the files, and will have an appropriate grid weighting factor.
Weighting, referred to in the paragraph above, is the process of assigning relative weights to collocated data sets, such that only those deemed most accurate or up to date are used for subsequent processing and plotting. This feature will be demonstrated more in Chapter 4: "Processing Multibeam Data".
We will then use mbdatalist to create three ancillary files for each data file. These ancillary files will greatly speed the processing of subsequent tasks. The three files are referred to as "info", "fast bathymetry" and "fast navigation." The info (".inf" suffix") contains meta-data and statistics about its parent data file. The information it contains is, in fact, identical to that created by mbinfo as we will see later. The fast bathymetry (.fbt suffix) and fast navigation (.fnv) files contain bathymetry and navigation data, respectively, in a format that can be read and processed more quickly than the original swath file format.
We can use mbdatalist to create a geographically windowed list of the files we are interested in.
Finally, we can make some cool, quick plots.
Perhaps we need an example.
In the ~/mbexamples/cookbook_examples/other_data_sets/ew0204survey/ directory you will find a collection of data files recorded with the Atlas Hydrosweep DS2 sonar aboard the R/V Ewing. These files will be used for the following examples.
First we need an initial list of the data files. This list needs to be in the directory that contains the data files themselves. This is done easily enough with the following:
cd ew0203survey/ ls -1 | grep mb183$ > tmplist
Sometimes the data files are in a write protected archive, that prevents you from just making your own local data list. What do you do then? Generate the file list with the following: find <pathtoarchivedir> -type f | grep mb183$ > tmplist. This will create a file list with relative path names to the data files, which will be carried through the subsequent steps below. Clever eh?
Now that we have a list of the files in our data directory, we can use mbdatalist to create a properly formatted data list for our subsequent MB-System™ processing.
mbdatalist -F-1 -I tmplist > datalist-1
Let us take a moment to peek inside and see what mbdatalist has done for us.
00020504090010.mb183 183 1.000000 00020504091010.mb183 183 1.000000 00020504092010.mb183 183 1.000000 00020504093010.mb183 183 1.000000 00020504094010.mb183 183 1.000000 00020504095010.mb183 183 1.000000 00020504100010.mb183 183 1.000000 ...
Here we see, for each file, the file name, the format, and a default grid weight of 1. Perfect!
With our new data list in hand, we can go ahead and create the ancillary data files. Using mbdatalist again:
mbdatalist -F-1 -I other_data_sets/ew0204survey/filelist.124 -N
The data directory now looks like this:
00020504090010.mb183 00020504090010.mb183.fbt 00020504090010.mb183.fnv 00020504090010.mb183.inf 00020504091010.mb183 00020504091010.mb183.fbt 00020504091010.mb183.fnv 00020504091010.mb183.inf 00020504092010.mb183 00020504092010.mb183.fbt 00020504092010.mb183.fnv 00020504092010.mb183.inf ...
Now that we have the ancillary files created (particularly the statistics file which is used by mbdatalist for geographic windowing) we can create a new file list geographically windowed around a particular area. In this instance, I know from my exemplary notes during the cruise, that a small survey was taken of an area bounded by the following coordinates: (W/E/S/N) 170.133/170.35/42.2/42.4. The following line creates a list of data files within the geographic bounds of interest, with all the proper details required by other MB-System™ tools.
mbdatalist -F-1 -I datalist-1 -R170.133/170.35/42.2/42.4 \ > survey-datalist
The resulting survey-datalist looks something like this:
00020504100010.mb183 183 1.000000 00020504101010.mb183 183 1.000000 00020504102010.mb183 183 1.000000 00020504103010.mb183 183 1.000000 00020504104010.mb183 183 1.000000 00020504105010.mb183 183 1.000000 ....
As you can see, each data file is listed appropriately, each format type (183) is specified, and the default weighting factor of 1 is included as well.
Now lets make some plots.