Executive compass | March 2011
BAE Systems supports wide range of sensor models
Kurt de Venecia
SOCET GXP functionality will soon surpass SOCET SET and certain fundamental developments should be acknowledged.
SOCET GXP v3.2, just released, is highly automated to reduce manual tasks. We are addressing demands to increase productivity by building a product that is easy to use and performs rigorous processes behind the scenes to deliver highly accurate results.
A core SOCET GXP requirement that increases the capacity to generate accurate results is using data in its native format whenever possible. This extends from basic image types including TIFF, GeoTIFF, JPEG and NITF through terrain formats such as DTED, NITF and GeoTIFF to features and vectors such as shapefiles. Working with data in its native format has performance and usability advantages. For example, a TIFF image can be dragged from Windows Explorer into SOCET GXP for immediate image viewing. If metadata exists for imagery or other data types, SOCET GXP uses that information to georeference raw data to real-world ground coordinates. The georeferencing may be as simple as a text file that identifies the data’s mapping coordinate system or a tag to extend the basic form of the raw data. Image-to-ground references can be represented with a fundamental orthogonal projection to define the X and Y ground coordinates of a pixel in an image along with scale factors for image line and sample coordinates, or the four-corner locations of an image in ground space.
To move beyond simple planimetric XY models, GXP engineers work closely with organizations such as the Community Sensor Model (CSM) working group, government agencies, specific programs, system integrators, and satellite operators and vendors of airborne cameras, LIDAR systems and hyperspectral sensors. These relationships enable GXP engineers to develop and rigorously model the transformation between an image and the ground based on a projective mathematical function. The projective sensor model relates line and sample image coordinates to X, Y and Z object space coordinates (ground coordinates; latitude, longitude, height; easting, northing, height; etc.).
The projective model is important for SOCET GXP functionality, such as the easy-to-use height measurement and simple building tool, now available in SOCET GXP v3.2, to stereo mensuration and applications such as automatic terrain generation. The projective model can take many forms. In some cases the model might be generic, for example, a cubic Rational Polynomial Coefficient function (RPC), frame or generic pushbroom sensor. In other cases, rigorous sensor-specific models are developed, which typically rely on information about the sensor position, attitude and rate (exterior orientation) as well as focal length, chip size, chip orientation and lens characteristics (interior orientation).
The benefit of using SOCET GXP for geospatial analysis and image exploitation is twofold. The application reads images natively with the associated metadata and sensor model to deliver the highest degree of accuracy through automated triangulation. In addition, complex photogrammetric procedures are simplified, making the process intuitive for novice-to-expert users, with the option to perform further calculations if desired.
Figure 1. Sendai 9.0 earthquake damage of an oil refinery in Shichigahama, Japan. The red areas indicate probable oil spills that were identified using SOCET GXP v3.2 supervised classification functionality. WorldView-2 8-band imagery courtesy of DigitalGlobe.
Figure 2. This rigorous pan-sharpened image is created on-the-fly in SOCET GXP v3.2 by combining WorldView-2 panchromatic imagery at 0.6m ground sample distance (GSD) with WorldView-2 MSI imagery at 2.4m GSD. The zoomed-in view of the probable oil spill outlined in figure 2 shows rigorous projective sensor model support in the pan-sharpening process, thus allowing use of the simple height measurement tool to measure and label one of the damaged oil storage facilities.
Figure 3.
Figure 4. Figures 3 and 4 show GeoEye-1 stereo imagery collected over Port-Au-Prince, Haiti following the January 2010 earthquake. In figure 3 displaced people occupy a soccer field. The green areas in figure 4 identify potential helicopter landing zones. SOCET GXP v3.2 Automatic Terrain Generation is used to produce a digital surface model over Port-Au-Prince with 11 million points at 3-meter spacing and a nominal GSD of 0.5m. Using the surface model, SOCET GXP locates potential helicopter landing zones with a slope of less than 5 percent and an area of 60sq meters or larger. Viewing the two images side-by-side in a SOCET GXP Multiport viewing window provides both geospatial and visual intelligence. Image courtesy of GeoEye.
As new satellites and airborne sensors become available, BAE Systems continues to implement functionality for ease-of-use, and to ensure the highest degree of accuracy as a result of core development requirements imposed on the application development process. I am excited about the SOCET GXP v3.2 release that is now shipping with a breadth of new capabilities for geospatial and image analysis.
The new sensors supported in SOCET GXP v3.2 are: ALOS (PRISM, AVNIR-2 and PALSAR), COSMO-SkyMed, ASTER, KOMPSAT-2 and MSP 1.1.2. These additional sensors complement the ones already supported in the product: TerraSAR-X, EROS-B, FORMOSAT-2, Frame Advanced, SPOT, RPC, Four-Corner, Ortho, GeoEye-1, IKONOS, QuickBird, WorldView-1, WorldView-2, Radarsat-1, Radarsat-2, and MSP 1.0.3.
SOCET GXP v4.0 is planned for release in the fourth quarter of 2011 with further sensor-model support for MSP 1.x, ADS40, and the CSM interface.
Sincerely,

Kurt de Venecia
Director, product management
BAE Systems GXP














