Over the last decade, the unprecedented population growth rates throughout much of the world and the subsequent need for information to support and manage that growth has put more pressure than ever before on geographical information system (GIS) and production mapping professionals. Businesses and planners need more up-to-date information than ever before, so much so that photogrammetry production “factories” can work 24/7 and still find it a challenge to keep up with the increasing volume of work.

The GIS professionals who typically rely on these data “factories” for assistance with data layer creation now find themselves standing in line. For busy GIS and mapping professionals, the solution to transforming imagery into reliable geospatial content more efficiently but without compromising accuracy lies in a process-driven workflow. This article discusses the process-driven workflow concept and the tools available to implement it effectively.

The Key to Increased Productivity

Subpixel positioning capabilities enable more accurate measurement of features.
Transforming imagery into usable data typically requires several processing steps. These steps are referred to as a workflow. It should be noted that following every step in this workflow is not necessarily required. Some scenarios might require certain steps but not others. However, typical scenarios will require every step in the workflow.

The first step in the process-driven workflow is to create a new project. This involves defining project properties such as the type of imagery that will be processed and the coordinate system used. This step also involves adding all of the raw data that will be processed to the project. When a project is created, the workflow begins.

A sensor model describes the properties and characteristics associated with the camera or sensor used to capture an image. Internal sensor model information describes the internal geometry, including focal length and lens distortion for aerial photographs. External sensor model information describes the position and orientation of each image as it existed when the imagery was collected. Without this information, value-added data layers such as oriented images, 3D feature datasets, Digital Terrain Models (DTMs), and orthorectified images cannot be derived from imagery.

Ground Control Points (GCPs) are used to establish a geometric relationship among the images in a project, the sensor model, and the ground so accurate data can be collected from the imagery. The GCP has three coordinates: x, y, and z, which are measured across multiple images. GCPs can be collected from existing vector files, orthorectified images, DTMs, and maps.

A tie point is a point with unknown ground coordinates but is visually recognizable in the overlap area between images. Tie points are used to position multiple images correctly, relative to one another. Automatic tie point collection uses digital image matching techniques to automatically identify and measure tie points across multiple images.

Block adjustment, which can include aerial triangulation, is essential to determining the information required to create orthophotos, DTMs, digital stereo models (oriented images), and 3D features. A block adjustment can obtain internal and external sensor model information, 3D coordinates of tie points, and additional parameters that characterize the sensor model. Most importantly, the results of a block adjustment can provide detailed statistical reports on the accuracy of data.

DTMs form the basis of many GIS applications and are vital for creating orthorectified images. To automatically generate a 3D terrain representation of the Earth and its associated geography, digital image matching techniques are used to automatically identify and measure the image positions of ground points appearing within the overlapping areas of two adjacent images. With this information, the accurate sensor model information from block adjustment is used to transform the image positions of the ground points into 3D coordinate information. After the automated DTM extraction process is completed, a series of evenly distributed, 3D mass points is located within the area and can be used to create a Triangular Irregular Network (TIN) or a raster DEM.

In photogrammetry solutions, contour maps, point clouds, and imagery can all be used to edit Digital Terrain Models (DTMs).
Terrain datasets automatically derived from imagery must be reviewed prior to their use in orthorectification, 3D visualization, and spatial analysis. Using stereo imagery as a reference backdrop, a terrain dataset is superimposed on top of the imagery and can be viewed in 3D stereo. Using a series of terrain editing tools, the terrain dataset can be modified as needed to represent the surface of the Earth.

Orthorectification is the process of removing geometric errors inherent within photography and imagery. Orthorectified images serve as the image backdrops for displaying and editing GIS vector layers. Using sensor model information generated by block adjustment and a DTM, errors associated with sensor orientation, topographic relief displacement, earth curvature, and other sources can be removed. Measurements and geographic information collected from an orthorectified image represent the corresponding measurements as if they were taken on the Earth’s surface. The process of color-balancing, orthorectification, and mosaicking can be combined into one step, rather than three independent steps.

3D data can be collected from oriented images. Using sensor model information, two overlapping oriented images are automatically aligned, leveled, and scaled to produce a 3D stereo effect. The resulting digital stereo model allows for interpretation, collection, and visualization of 3D geographic information from imagery, and is used as the primary data source for collecting 3D engineering and GIS data layers.

To update a GIS or an engineering data layer, existing feature datasets often are superimposed on the DTM, edited, and reshaped to their real-world positions. Two-dimensional vector layers can be transformed into 3D geographic information. During data collection, the spatial and non-spatial attribute information associated with a vector layer can be edited and the attribute tables can be displayed with the DTM. Automated attribution techniques simultaneously populate a GIS during the collection of 3D data. Additional qualitative and quantitative attribution information associated with a feature can be input during the collection process.

Determining the Right Tools

Geospatial professionals — from GIS to production mapping — need to produce more information in less time while maintaining accuracy and managing costs. For example, GIS professionals who use ESRI’s ArcGIS want solutions that closely integrate with ESRI data formats and software, as well as an all-in-one solution for digital mapping. Engineering professionals who use a specific CAD or modeling program want solutions that closely integrate with their system for large-scale engineering mapping applications.

Production mapping professionals already have sophisticated tools, but these tools tend to be inefficient and difficult to use. These professionals want a highly accurate, end-to-end production mapping system that is functionally complete. They want a high level of automation, including the ability to batch and streamline processes, but they also want access to functional details and the ability to customize the technology to their needs. Both GIS and production mapping professionals require seamless data transfer without the risk of lost quality.

The ideal solution should be a process- and workflow-driven system consisting of a suite of photogrammetric production tools that processes geospatial images from end to end quickly and accurately. It should be seamlessly integrated to increase the throughput of creating and updating geospatial content.

It is important to have a seamlessly integrated collection of software tools allowing transformation of raw imagery into reliable data layers required for all digital mapping, GIS analysis, and 3D visualization. You also need to be able to streamline projects into one fast, manageable workflow without compromising detail and accuracy. Software such as the Leica Photogrammetry suite can help provide that solution.

This type of software lets GIS and mapping professionals focus on using their expertise to fine-tune the data by taking on many of the repetitive tasks commonly associated with data production. Automated processes such as interior orientation, tie point generation, terrain extraction, and simultaneous color balancing/orthorectification/mosaicking help to increase production throughput.

Large-Volume Orthorectification

Photogrammetry production “factories” supply accurate GIS datasets to organizations that create and update maps. Most of these factories specialize in large capacity photogrammetric and satellite projects, so they appreciate the importance of handling geospatial projects efficiently and economically.

Using photogrammetry software, production shops can orthorectify images that represent thousands of square kilometers of aerial photography in a fraction of the time it previously took. The software allows fast and accurate rectification of aerial photographs by block triangulation.

Aerial triangulation lets you rectify large volumes of aerial photography efficiently and accurately. It establishes a relationship among the images contained in a project, the camera at the time of data acquisition, and the ground. The preparatory stages in a block triangulation include selecting the relevant camera model and defining appropriate block properties, such as datum and projection.

Production companies can establish workflows to rapidly process large volumes of photography using photogrammetry tools. Data initially is divided into manageable blocks — typically 50 to 200 frames — and pyramid layers are calculated to enhance data display. Each block is then triangulated using tie points that were automatically derived and ground controls, which can be obtained from a variety of sources.

The results of the triangulation are checked visually by viewing the resulting stereo imagery or by calibrating the imagery and overlaying the control information. Any errors can thus be detected before re-sampling is performed. The orthorectified data can now be mosaicked. The final stage of the program is to visually check each tile and remove cut line and scanning artifacts. A comprehensive photogrammetry system allows you to create production-grade geospatial content within a single software package.

This article was written by Ryan Strynatka, Product Manager - Driven Workflow, at Leica Geosystems GIS & Mapping in Atlanta, GA. For more information, Click Here 

Imaging Technology Magazine

This article first appeared in the June, 2007 issue of Imaging Technology Magazine.

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