To compensate for the different amounts of illumination of scenes captured at different times of day, or at different latitudes or seasons, image analysts may divide values measured in one band by values in another band, or they may apply mathematical functions that normalize reflectance values.
To cope with such problems, analysts have developed numerous radiometric correction techniques, including Earth-sun distance corrections, sun elevation corrections, and corrections for atmospheric haze. Such differences can be advantageous at times, but they can also pose problems for image analysts who want to create a mosaic, by adjoining neighboring images together, or to detect meaningful changes in land use and land cover over time. With these factors in mind, it should not be surprising that an object scanned at different times of the day or year will exhibit different radiometric characteristics. Furthermore, the response of a given sensor may degrade over time. The reflectance at a given wavelength of an object measured by a remote sensing instrument varies in response to several factors, including the illumination of the object, its reflectivity, and the transmissivity of the atmosphere. This is why processed scenes are shaped like skewed parallelograms when plotted in geographic or plane projections. To properly georeference the pixels in a remotely sensed image, pixels must be shifted slightly to the west in each successive row. In the raw scanned data, however, the first pixel in each row appears to be aligned with the other initial pixels. 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.
MULTISPEC BASECOAT SERIES
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.
MULTISPEC BASECOAT FULL
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.
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