GEOG 480
Exploring Imagery and Elevation Data in GIS Applications

Elevation Data Collection


The geometric conditions of a pair of overlapping photographs, coupled with the evolution of stereo vision in most creatures that inhabit our planet made photogrammetry the most important method for topographic mapping for over a century. For decades, topographic maps have been irreplaceable planning and design tools for the military, for civil engineers, for scientists, and even for the adventuring public. The depiction and interpretation of terrain data from a 2-dimensional paper product required special skills and considerable practice. While this type of depiction was incredibly useful and enabled many great accomplishments, advances in computer graphics, animation, and 3D rendering in the past few decades are quickly turning the 2D topographic map into a quaint historical relic.

Historically, elevation data was almost always collected as a "bare-earth" model, eliminating above ground features such as buildings, vegetation, and bridges. Today, because many applications make use of the above-ground features, digital surface models which include these features are often specified as additional deliverables.

Stereo aerial photography or satellite imagery is still a very important source of elevation data. Human beings drawing cartographically-pleasing contours by hand is rare in today's mapping industry, but it is still common to manually extract elevation points (mass points) and breaklines along key features of the natural and man-made landscape. Automated image correlation techniques are also useful, although there is almost always a need for manual editing and correction if a clean bare ground surface is desired. Autocorrelation is a fast and effective way of producing digital surface models, particularly for the generation of "true orthophotos." which were discussed in Lesson 3.

Active remote sensing technologies, particularly lidar and IFSAR, are quickly gaining acceptance as the most accurate and/or cost-effective ways to collect high-resolution elevation data over large areas. An in-depth discussion of either of these technologies (including sensor design and operation, project planning, data processing, and product generation) is beyond the scope of this course. However, the textbook readings do describe these technologies at an overview level. Most of the information in this lesson, which deals with the elevation data products, rather than the method of acquisition, is applicable regardless of the sensor used for acquisition.

Seamless coverage of the United States with current digital orthophotography has been achieved, and is kept current, by a combination of government and commercial activities. In previous lessons, we discussed federal programs, such as USGS and USDA, and commercial endeavors such as the Microsoft/Bing Global Ortho Project. The USGS has developed and maintained seamless elevation data coverage of the United States through the National Elevation Database, but much of the source information for the NED is very old and of relatively low accuracy and resolution. There is significant interest in upgrading the nationwide elevation coverage with high-resolution, high-accuracy data, but it would require commitment of hundreds of millions of dollars for data acquisition and processing. One of the best cost-benefit arguments for seamless elevation data appears to be in support of FEMAs floodplain mapping program, but the pool of potential users of this data is much larger. Execution of a national elevation mapping program will require a significant number of interagency partnerships and cooperative cost-sharing agreements.

The viability of various remote sensing technologies for creation of a seamless national elevation database was the subject of a National Academies of Science report published in 2007. The study was done for FEMA, and the committee was made up of experts in mapping as well as engineering applications. This report, Elevation Data for Floodplain Mapping, can be downloaded for free and provides an in-depth comparison of photogrammetry, lidar, and IFSAR that should more than satisfy the student who would like to read beyond the scope of the assigned reading in this course.