In the example above,
the center of the image contains the seam between two 1:24,000 quad maps.
The actual edge of each quad image is to the left and right of the seam.
Therefore, you will still see some sort of neatline, but you will not
see the boundary of the images. An exception is if the two quads do not
match because of differences in color between them or differences in geo-referencing
accuracy. But the idea is that steps are taken to reduce the amount of
differences between quads and make them appear as seamless as possible.
The SJRWMD covers
240 USGS 1:24,000 quads. Since we wanted some overlap with the other
Water Management Districts, we are also including at least 100 more quads.
That means we had at least 340 quads to process. In addition, there are
several 1:100,000 and 1:250,000 quads that we also needed to process.
This methodology can be applied to any one of these map series. For simplicity,
this methodology only referes to the 1:24,000 quads.
Projecting the Quads
The SJRWMD uses
the UTM Zone 17 NAD 83 (HPGN) projection and coordinate system. The
target projection for the quads was NAD83 without the 90 adjustment. The
adjustment accounts for about 40 cm of difference, which is much less
than the spatial accuracy of the quad maps.
ARC/INFO vs. Imagine
The District has
ARC/INFO and ERDAS Imagine, which are both capable of changing
raster data projections using resampling techniques. We have found ERDAS to
be at least 100 to 150 times faster at projecting raster data. For example,
a 1:24,000 quad may take 5 hours to project in ARC/INFO GRID, but
only 2 minutes in ERDAS Imagine.
The problem with
ERDAS is that we have not been successfull at automating ERDAS using
its EML language. We attempted to automate our Districtwide conversion
from State Plane East NAD 27 to UTM NAD 83-90 using EML and it simply
did not work right. Tech support from ERDAS tried to help us out,
but they finally said "Use the C-Toolkit." We don't have the
resources to write custom C code, so that wasn't an option. Manually using
ERDAS through the Graphical User Interface was easy, but it was laborious
and people become prone to mistakes after doing 10 quads in a row. Even
though the project is fast, you still have to import the TIFF file,
set-up the projection parameters, do the project, then convert the file
back to a LAN or TIFF file.
ARC/INFO is highly
automatable through AML. Even though the processing time is orders of
magnitude slower, we decided to use GRID and let it run in the background
accross multiple CPUs. We developed two AMLs to automate the projection
process. The first AML, loop.aml, was a
very simple AML that converted the TIFF images to GRID format
and projected each file.
quads were projected over 1 month's time. This was done utilizing a dual
processor SPARC Ultra powered Enterprise 3000 server and a SPARC
Ultra 1 Model 170. The process was interrupted several times by un-related
network configuration changes. However, we were able to run the processes
for days on end which helped speed the processing. The key was to keep
the computers busy and be patient. Disk space was not an issue, because
we had a 14 GB partition available on the server and a 3 GB partition
available on the workstation.
Removing the Map Collar
An AML named
scan24_proc1.aml was created for
removing the map collar. The AML used the SJRWMD 1:24,000 quad
index coverage to reselect polygons to clip the GRID format DRG.
The basic methodology
is as follows:
Creating a Seamless DRG Layer
- Using cursors,
get the 4-digit WMD quad number from the index24 coverage. (the USGS quads
use a LAT/LONG and alpha-numeric numbering scheme).
- Reselect the quad
polygon from the index24 coverage (based on NAD27 tiles!)
- Clip the DRG with
- Rename the quad
to the WMD standard
A separate AML named
scan24_proc2.aml was developed for
creating the images that became part of the seamless DRG layer.
The basic methodology
is as follows:
Create the Image Catalog
- With a simple
looping AML, put all of the clipped DRGs that will be needed into a
- NOTE: I
had problems putting more than 150 GRID format DRGs in one
directory. I never resolved what the problem was. GRIDs were randomly
becoming corrupted when I copied more into the directory. Therefore,
I had to do this whole process in batches.
- Get the coordinates
for the quad box and add a 100-meter buffer
- Use the coordinates
with the generate command to generate a polygon coverage
- Calculate which
quads will be needed
- Merge all available
surrounding quads (up to 8 plus the quad itself) /* and re-clip the
grid using the generated polygon coverage
- Convert the DRG
from GRID to TIFF image
The image catalog
allows you to seamlessly browse the 1:24,000 DRGs without having to know
which quad to load into ArcView or Arcplot.
Following are the
two ARC/INFO commands necessary to implement the catalog.
- ADDIMAGE drg_list
In ArcView, image
catalogs are selected by adding an image theme type and you must go into
the INFO directory where the catalog is stored in order to see the
In ArcPlot, image
catalogs are treated like a single image on the command line, e.g. IMAGE drg24
The result is a set
of DRG images that are squared off using the surrounding DRGs. The
net effect, when used in conjunction with an image catalog, is the appearance
of a seamless DRG layer in the GIS.
On-screen, the 1:24,000
DRGs look best at a scale less than 1:24,000. This is because the screen
is not as high resolution as the printed map is. The features on the map
therefore do not have enough pixels on the screen to properly represent
themselves. The 1:100,000 and 1:250,000 maps are similar in this respect.
The TIFF image
format using packbits compression is the same format that the USGS uses
for the DRGs. The amount of compression varies by quad, depending on the
variation in color on the quad. To give you an idea of disk space requirements,
275 quads in compressed TIFF format is taking up 2200 MB of space.
File sizes range from around 3 MB to 23 MB. The average appears to
be around 8 MB.
The process outlined
above is time consuming, but the computer does most of the work and the
results are well worth it. The DRGs now serve a major role as a complete
base map for use within the SJRWMD's GIS.