As a remote sensing satellite follows its orbital path over the spinning globe, each scan row begins at a position slightly west of the row that preceded it. If you were to plot on a cylindrical projection the flight path that a polar orbiting satellite traces over a 24-hour period, you would see a series of S-shaped waves. At the same time, remote sensing satellites like IKONOS, Landsat, and the NOAA satellites that carry the AVHRR sensor, orbit the Earth from pole to pole. The Earth rotates on its axis from west to east. Another source of geometric distortions is the Earth itself, whose curvature and eastward spinning motion are more evident from space than at lower altitudes. Relief displacement is one source of geometric distortion in digital image data, although it is less of a factor in satellite remote sensing than it is in aerial imaging, because satellites fly at much higher altitudes than airplanes. Most prefer preprocessed data from which these flaws have been removed. Understandably, most users of remotely sensed image data are not satisfied with the raw data transmitted from satellites to ground stations. Raw remotely sensed image data are full of geometric and radiometric flaws caused by the curved shape of the Earth, the imperfectly transparent atmosphere, daily and seasonal variations in the amount of solar radiation received at the surface, and imperfections in scanning instruments, among other things. 7.4.1 Image CorrectionĪs suggested earlier, scanning the Earth's surface from space is like scanning a paper document with a desktop scanner, only a lot more complicated. Over the next few pages, we focus on digital image processing techniques used to correct, enhance, and classify digital, remotely sensed image data. One of the main advantages of digital data is that they can be readily processed using digital computers.
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