GXP Mosaic

Introduction

SOCET for ArcGIS, a SOCET SET module, adds stereo digitizing to ArcGIS; 3D information is captured directly in the ESRI^® environment. Users see their familiar ArcMap^® surroundings and Editor functions with a stereoscopic window for data collection, and SOCET SET manages image organization behind the scenes. Everything works in 3D, and photogrammetric expertise is not required. SOCET for ArcGIS works with the geodatabase, whether personal or multiuser, and handles versioning and topology. Users benefit from SOCET SET’s rigorous handling of airborne and satellite imagery – it embeds the photogrammetry into ArcMap.

Tips

Increase performance while loading graphics

Set the stereo viewport graphics mode to Limited. When set to Full, refreshing graphics will redraw every feature loaded in ArcMap, but when set to Limited it will only load features within the viewport.

Use the synchronize cursor functionality to navigate quickly to a feature in the stereo viewport from the ArcMap canvas

1. Map an accelerator key in ArcMap to the synchronize cursor function.
2. Toggle on ArcMap tools, press the accelerator key, and move to the feature of interest in the ArcMap canvas.
3. The stereo viewport will navigate to the image automatically as the cursor moves.
4. Once you have reached the area of interest, press the accelerator key again to turn off tracking and switch back to the stereo viewport to edit the feature.

Learn more about any SOCET for ArcGIS preference setting

Press the “what’s this” tool , and click on any preference.

Swansea University uses SOCET SET to track glacial activity in Norway

SOCET SET customer Swansea University, in the U.K., is studying glacier melt in Svalbard, Norway. The glaciers around Svalbard could make the largest contribution to sea-level rise of any arctic region outside of Greenland. A field study, named Sea Level Rise from ICE in Svalbard (SLICES), was conducted to gather historic topographic data sets on sea-level rise for comparison with current records of the same area. Research began in 2003. The primary goal was to measure volume changes of the benchmark Svalbard glaciers, using LIDAR and photogrammetrically derived DEMs to provide a strong baseline for continued monitoring in the area. The findings were applied to the entire archipelago with a regional mass balance model, which was used to derive 20th and 21st century contributions to global sea-level rise in Svalbard.

Ice masses around the world are changing rapidly. The Glaciology group within the School of Environment and Society at Swansea is using advanced digital terrain modeling techniques to improve the quantification and our understanding of these changes. The group has chosen SOCET SET as our key photogrammetric data capture package. – Dr. Timothy James, Scientist, Swansea University, Swansea UK

For the SLICES project, there were many large images that had been captured at 1:50,000 scale and scanned at a high resolution to maximize DEM resolution. SOCET SET’s flexibility with large images, input file formats, and ASCII files was a major advantage. SOCET SET’s Automatic Terrain Extraction (ATE) and Interactive Terrain Editing (ITE) modules offer a combination of automated and manual tools for building terrain and surface models, and work equally well with new and century-old data.

Perspective view of a glacier in Svakbard, Norway

Stereo matching on surfaces such as glaciers, with repeating patterns and a lack of texture, is notoriously difficult. Through the use of back-matching algorithms in ATE, the scientists have been able to eliminate many of the blunders that are normally associated with stereo matching on such surfaces, and thus obtain a better automated DEM with far less manual correction required.

Read the full story on the SLICES study, Imaging Notes, Spring 2007, pp. 24 – 29.

Occasionally, in extremely steep areas, or areas where fresh snow cover makes stereo matching difficult, the team implements a hybrid approach, which involves measuring DEM points or breaklines manually in ITE, then using these as seed points in ATE. If stereo matching is unreliable, it is preferable to have a hole in the data, as opposed to blunders. A TIN (Triangulated Irregular Network) DEM from ATE with back-matching yields much better results; it will identify such points as blunders and discard them.

Results from the study show that between 1961 and 2005 the average rate of melt was found to be about 0.47 meters vertically per year, with more melt occurring in recent years. Small glaciers like those in Svalbard represent only four percent of the world’s total land ice, but account for an estimated 20 to 30 percent of 20th century sea-level rise — and the melt has increased substantially since 1988. This work is extremely important for improving predictions of sea-level rise due to the density of population along the world’s coastlines.

Looking ahead, the Swansea Glaciology Group is turning its attention to Greenland, an area that has been identified as crucial for predicting future sea-level rise. For details on these and other projects underway within the Swansea Glaciology Group, please visit: http://geography.swan.ac.uk/glaciology/.

Coordinate Measurement window

SOCET SET image coordinates are expressed as an ordered pair of double precision, floating point numbers which identify a row (line) and column (sample) location within the matrix of pixels. The SOCET SET image coordinate values can be seen on the Coordinate Measurement window, or within measurement files from triangulation (*.ipf) and interior orientation (*.iop).

The origin, position (0,0), to which the line and sample values are referenced is defined as half of the total number of lines and half of the total number of samples measured from the center of the upper left pixel. This means that the origin of the image coordinate system may fall inside a pixel or on the boundary between pixels depending on whether the number of lines and samples is even or odd, respectively. Also it should be noted that the origin will be near the center of the image, not exactly at the center. The origin will be one half pixel down and to the right of the actual image center.

Figure 1. Even number of lines and samples, origin inside a pixel.

Figure 2. Odd number of lines and samples, origin at pixel boundary.

Positive line coordinates are measured downward from the origin and positive sample coordinates are to the right of the origin. Lines above the origin are negative as are samples to the left of the origin. The figure below shows some example image locations and their line and sample values in the SOCET SET image coordinate system. See Sensor Model section of the SOCET SET programmer’s reference for more detail.

Figure 3. Point, line and sample results

Point, line, and sample results

Note to Developers: When integrating SOCET SET with other applications where image coordinates are being passed back and forth, it is the calling application’s responsibility to convert the image coordinates to/from SOCET SET coordinates, origin as described above, and the coordinate system used by the other application — most likely origin at the upper left hand corner.

BAE Systems is pleased to announce the release of SOCET SET v5.3. This new release provides additional sensor models and new features based on automatic tie-point measurement for multi-sensor triangulation. Productivity improvements have been made throughout the SOCET SET workflow, including enhancements to SOCET for ArcGIS, Sketch, Feature Extraction, Mosaic and more. Automatic Terrain Extraction (ATE) has been improved with enhancements for bare-earth and reflected surface processing using back-matching and multi-pair matching.

If your production workflow includes significant mosaic operations, be sure to check out SOCET SET v5.3. Parallel processing improvements in this area are showing large gains in productivity running on a dual processor machine. Outlined below is a list of improvements and new features included in SOCET SET v5.3.

• Improvements to Terrain Extraction for increased productivity, accuracy and blunder elimination. The data structure for both TIN and Grid terrain is now capable of handling billions of points, including LIDAR point clouds. The Automatic Terrain Extraction improvements reduce manual editing for all terrain types. These improvements allow for increased productivity with workflows requiring terrain. In addition, the ATE improvements are relevant to both terrain surface models as well as reflected surface models.
• Based on customer feedback, enhancements were added to the SOCET for ArcGIS product, which was introduced in the SOCET SET v5.2 release. Improvements include compatibility of grouped layers in the ArcMap® table of contents with SOCET SET display and collection; new snapping agent integrated with ArcMap; the addition of accelerator key mapping for commonly used SOCET for ArcGIS commands; rotation and zoom to extent of ArcMap display to match the SOCET SET Viewport and support and population of subtype attributes from ArcGIS.
• Orthomosaic enhancements provide a new pixel void fill that prevents non-image data (usually black pixels) from being included in an orthomosaic. Multiple input images allow the process to sort through overlapping pixels to determine image vs. non-image pixels.
• Product improvements for ClearFlite include the ICAO PANS-OPS surface for compliance with international standards for mapping airport obstructions.
• OrbView-3 BASIC Imagery with ephemeris can now be imported and triangulated in SOCET SET with the advanced sensor models. Rigorous modeling is used throughout the workflow for accurate mensuration and product generation using OrbView-3 imagery.

For more information on SOCET SET v5.3: http://www.baesystems.com/gxp.