This course offered by PCI Geomatics, using Geomatica Desktop Image Processing Software and the Historical Airphoto Processing (HAP) Module
Overview Does your organization have hundreds, thousands, or even more old, historical air photos sitting on the shelf, not being used? This course will provide you with an operational workflow to take your scanned air photos into modern day tools, allowing you to create great looking ortho mosaics and elevation models.
Who is the intended audience?
you are interested in rescuing old air photos that could be used for planning, change detection and a myriad of other applications, this course is perfect for you! Within a short amount of time you will be able to produce ortho mosaics. We provide you with everything you need - sample imagery (courtesy of the City of Saint John, New Brunswick in Canada), trial software (Geomatica includes a HAP trial license) and all of the reference information you need.
What Materials will be used? Students will be able to work with a licensed version of Geomatica as well as sample data sets to follow along with the instructor. Students are expected to install Geomatica on their computer and work with a copy of the data which is provided.
How long will it take me to complete the course? The course materials (videos) run for just over 1 hour. You will likely play the videos several times and review certain steps. The expected time to complete the course is 4-6 hours.
This lecture will introduce you to the course, and you will have access to free imagery provided by the City of Saint John as well as access to a trial version of Geomatica. Using the free images (18 scanned historical images and a subset reference image), you will be able to generate Digital Surface Models, as well as a color balanced ortho mosaic.
Ingesting the imagery is the first step in your project. We will use the HAP module within Geomatica to create the necessary information for processing, including exterior orientation, flight line information, and a basic ortho engine project we can use to collect fiducial marks off the scanned airphotos.
In order to position the images, we need to build a camera model for each image. By providing the HAP system with the corner fiducial locations (through the collection of a template), the HAP system can assemble a project and begin the alignment process.
This quality assurance step will roughly position the images to within a few hundred meters of their actual location, depending on the accuracy of the air photo scene center positions provided. Loading the results of the nominal georeferencing allows us to inpect the images and identify any rotation issues, scale issues, or to identify anything that is abnormal.
Having completed the inspection of the images through the nominal georeferencing step, we proceed to the coarse image alignment. We will make use of the reference image to collect ground control points automatically. Automatic tie points will also be collected which we can inspect in the next section.
The coarse alignment inspection includes ensuring there are no images without GCPs (islands). We can use the tools in OrthoEngine to identify problem areas (sorting by # of GCPs per image) and address issues as needed. The inspection step's goal is to reduce the overall GCP RMS to less than 20 image pixels, and to prepare it for fine alignment. You should also ensure a good distribution of GCPs across images and in different types of terrain.
In this step, the coarse alignment is improved upon, and the overall project exterior orientation is edited automatically and improved as well - for example using the block adjusted points, flying height is fixed to ensure the model is as accurate as possible. Similar editing steps are repeated in OrthoEngine to bring the pixel error below 10, or even better (below 6 pixels). Instead of deleting too many points, we choose to pass through the data one more time using another fine alignment process in the next module.
The last fine alignment pass is applied for this dataset, and a final grooming of GCPs and TPs is performed. This ensures optimal results and that the quality of the final model is high enough to attain good quality ortho image production. A good model can also be used to produce elevation models - we choose in this course to leave the pixel error at less than 3 pixels and generate the elevation data. For better models, it is suggested to bring the accuracy down closer to 1 pixel.
Givent that the accuracy of the model was good, we chose to generate elevation data. We created epipolar pairs, then extracted elevation data automatically. The result is a Digital Surface model from 1967, which contains valuable information on the height of forest stands, and structures for example. A demonstration is provided on the use of the Digital Elevation Model (DEM) Editing tool to fix the elevation and also to interactively create a Digital Terrain Model (DTM) which can then be used for the ortho production step is provided.
Having completed all prior steps, we arrive at the final and most important process, to create ortho images, and mosaic them into a single seamless image. We provide you with Python scripts that will allow you to interactively create the mosaic preview, where you can make interactive edits using the Mosaic Tool. Small adjustments are made to the mosaic, such as balancing the images and making easy, interactive edits to cutlines and dodging points. Once the preview looks as good as possible, we export the final product to a new mosaic file. The final step is an inspection of the quality of the corrections, by comparing the historical image with the road center line (provided in the data pack) and also the reference image.
Kevin R. Jones has worked in the field of Geomatics since 1996, and currently holds the position of Director, Marketing and Communications at PCI Geomatics. Mr. Jones has been involved in the acquisition, processing, and dissemination of information products derived from Earth Observation imagery throughout his career. Mr. Jones previously held the position of Project Manager for several large international development and commercial projects (ranging from $50,000 to
$5,000,000), and has worked with subcontractors, government partners, and local project partners to deliver innovative and practical solutions that leverage the use of geospatial imagery and technology. Mr. Jones also has extensive experience in bringing technology to market including product design, development, testing, evaluation, and commercialization.
In 2009 joined PCI Geomatics to lead the Marketing and Communications team. Mr. Jones has successfully rebranded PCI as the provider of scalable, high speed image processing solutions, and played a key role in developing and supporting business partner relations with Esri, Blackbridge, MDA, RapidEye, and over 30 of PCI's International resellers. Mr. Jones implemented the use of social media and the created PCI TV, which has helped to reinforce PCI Geomatics as a leading supplier of software solutions to the global market. In addition, he has lead web seminar production and delivery, international tradeshow strategy/presence, organized and hosted domestic events, and worked with top level executive staff within the company to implement numerous internal and external programs.
Specialties: Earth Observation, Remote Sensing, Image Processing, Project Management, Marketing, Product Development/Management, Social Media, Video Production, Corporate Communications, Photography