Remote Sensing - a tool for environmental observation

Figure 514 shows the principle for a two dimensional

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abstract coordinate system. Figure 5.14 shows the principle for a two-dimensional situation i.e. 2 spectral bands. For a Landsat TM image 6 spectral bands are used and hence, a transformation is computed in a 6 dimensional space.
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77 Tasselled Cap Transformation The Tasselled Cap transformation was originally developed as a linear transformation of Landsat multi-spectral scanner (MSS) data that projects soil and vegetation information into a single plane in the multi-spectral data space (Kauth and Thomas, 1976). The name Tasselled Cap originates from the ‘triangular, cap shaped region with a tassel’ in the visible and near infrared space (figure 5.15). The Tasselled Cap MSS-application was extended by Crist et al. (1986), Crist and Kauth (1986) and Crist and Cicone (1984b) to the six optical TM bands for the United States. Standard Tasselled Cap transformation coefficients for the USA are presented in table 5.2. Basically three new dimensions are considered: brightness, greenness and wetness. Brightness is a measure of overall reflectance, i.e. differentiating light soils from dark soils. Greenness displays the contrast between the sum of the near-infrared reflectance and the sum of the visible reflectance and is thought to be a measure of the presence and density of green vegetation. Wetness is most sensitive to changes of soil moisture content and plant moisture. Figure 5.14 Rotated coordinate system used in a principal component transformation (Lillesand & Kiefer, 1994). ────────────────────────────────────── TM1 TM2 TM3 TM4 TM5 TM7 ────────────────────────────────────── TC1: Brightness .3037 .2793 .4743 .5585 .5082 .1863 TC2: Greenness -.2848 -.2435 -.5436 .7243 .0840 -.1800 TC3: Wetness .1509 .1973 .3279 .3406 -.7112 -.4572 ────────────────────────────────────── Table 5.2 Thematic Mapper Tasselled Cap Transformation Coefficients proposed by Crist and Cicone (1984a).
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78 Figure 5.15 Graphical representation of the Tasselled Cap Transformation (Schowengerdt, 1997). 5.9 Image classification Digital image classification refers to the process of assigning pixels to classes. Usually each pixel is treated as an individual unit composed of values in several spectral bands. Classification of each pixel is based on the match of the spectral signature of that pixel with a set of reference spectral signatures. The term ‘classifier’ refers loosely to a computer program that implements a specific procedure for image classification. The classes form regions on a map or an image, so that after classification the digital image is presented as a GIS-layer or a mosaic of uniform parcels each identified by a colour or symbol. Most classifiers are spectral classifiers or point classifiers because they consider each pixel as a point observation. Other methods of image clas- sification are based on textural information of the image, they use information from
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  • Winter '12
  • JOHN
  • Remote Sensing, Electromagnetic spectrum, µm, Infrared

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