| Title | Elevation modelling from satellite visible and infrared (VIR) data |
| Download | Downloads (Preprint) |
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| Licence | Please note the adoption of the Open Government Licence - Canada
supersedes any previous licences. |
| Author | Toutin, Th |
| Source | International Journal of Remote Sensing 22, 6, 2001 p. 1097-1225, https://doi.org/10.1080/01431160117862 |
| Image |  |
| Year | 2001 |
| Alt Series | Earth Sciences Sector, Contribution Series 20042969 |
| Publisher | Informa UK Limited |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | remote sensing; satellite imagery |
| Illustrations | tables |
| Released | 2010 11 25 |
| Abstract | Since the early emergence of Earth observation satellites, researchers have investigated different methods of extracting three-dimensional information using satellite data. Apart from a few early
stereo-images by hand-held photographs acquired during the Gemini and Apollo missions, the first experiments to extract three-dimensional data using stereo viewing from space began with the Earth Terrain Camera flown onboard SkyLab in 1973/74. Since
this time, various analogue or digital sensors in the visible spectrum have flown to provide researchers and geoscientists with spatial data to extract and interpret three-dimensional information of the Earth's surface. Although clinometry techniques
can be applied with the optical sensor images, stereo-viewing of images was and still is the most common method used by the mapping, photogrammetry and remote sensing communities for elevation modelling. The paper will review clinometry and
stereoscopy and their applicability to the different satellite sensors (space photographs and scanners). Their performances to extract absolute or relative elevation from various research and commercial organizations are addressed. The respective
advantages, difficulties and constraints of the sensors are discussed, as well as the methods and the technologies used for extracting elevation data in an operational context. |
| GEOSCAN ID | 219771 |
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