The imagery was collected using ADS40, ADS40-SH51, and ADS40-SH52 digital sensors.
Collection was performed using a combination of twin-engine aircraft flying
at an average flying height of 21000 ft above mean terrain with 25% sidelap,
giving the collected data nominal ground sampling distance of 0.7 meters.
Based-upon the CCD Array configuration present in the ADS40 digital sensor,
imagery for each flight line is 12,000-pixels in width. Red, Green, Blue,
Near-Infrared and Panchromatic image bands were collected.
Collected data was downloaded to portable hard drives and shipped to the processing
facility daily. Raw flight data was extracted from external data drives using GPro
software. Airborne GPS / IMU data was post-processed using IPAS, PosPac and/or TerraPos
software and reviewed to ensure sufficient accuracy for project requirements.
Using Pictovera software, planar rectified images were generated from the collected data
for use in image quality review. The planar rectified images were generated at five meter
resolution using a two standard deviation histogram stretch. Factors considered during
this review included but were not limited to the presence of smoke and/or cloud cover,
contrails, light conditions, sun glint and any sensor or hardware-related issues that
potentially could result in faulty data. When necessary, image strips identified as not
meeting image quality specifications were re-flown to obtain suitable imagery.
Aerotriangulation blocks were defined primarily by order of acquisition and consisted of
four to seventeen strips. Image tie points providing the observations for the least
squares bundle adjustment were selected from the images using an autocorrelation algorithm.
Photogrammetric control points consisted of photo identifiable control points, collected
using GPS field survey techniques. The control points were loaded in to a softcopy workstation
and measured in the acquired image strips. A least squares bundle adjustment of image pass
points, control points and the ABGPS was performed to develop an aerotriangulation solution
for each block using Pictovera software. Upon final bundle adjustment, the triangulated strips
were ortho-rectified to the USGS NED DEM for the project area. A combination of 10-Meter
and 30-Meter NED data purchased from USGS in 2005 was used for rectification. The images
were re-sampled from the raw resolution of 0.7 meters to the required resolution of 1.0 meters.
Positional accuracy was reviewed in the rectified imagery by visually verifying the horizontal
positioning of the known photo-identifiable survey locations using ArcGIS software.
The red, green, and blue bands were combined to generate a final ortho-rectified image strip.
The ADS40 sensor collects twelve bit image data which requires radiometric adjustment for output
in standard eight bit image channels. The ortho-rectified image strips were produced with the
full 12 bit data range, allowing radiometric adjustment to 8 bit range to be performed on a strip
by strip basis during the final mosaicking steps.
The imagery was mosaicked using manual seamline generation in Orthovista Seam Editor (OVSE).
The 12 bit data range was adjusted for display in standard eight bit image channels by defining
a piecewise histogram stretch using OrthoVista software. A constant stretch was defined for
each image collection period, and then strip by strip adjustments were made as needed to account
for changes in sun angle and azimuth during the collection period. Strip adjustments were also
made to match the strips histograms as closely as possible to APFO specified histogram metrics and
color balance requirements. Automated balancing algorithms were applied to account for bi-directional
reflectance as a final step before the conversion to 8 bit data range.
APFO specified DOQQs were extracted from the final mosaic in GeoTIFF format. 3-Band DOQQs were
produced and 3-Band RGB CCMs were created. DOQQs corresponding to an individual CCM were
reviewed for overall color balance within the CCM. Local corrections were made where necessary
to ensure uniformity within the CCM. In the case of DOQQs occurring in more than one CCM,
a separate version of the image was generated and balanced for each CCM it occurred in.
The color balanced DOQQs were then compressed to MrSID Generation 3 format at 15:1 compression ratio
to create a composite CCM.