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Chapter 1
Remote sensing in the optical and microwave regions

Remotely sensed image data is widely used in a range of oceanographic, terrestrial, and atmospheric applications, such as land cover mapping, environmental modelling and monitoring, and the updating of geographical databases. Hence, the quantised pixel values making up an image may be converted to physical values of radiance and related to some property of the surface being sensed. An example of this approach is the calibration of thermal infrared imagery to produce maps of temperature fields, such as sea surface temperature. In other applications, thematic information is required. A thematic map is one that displays the spatial variation of a specified phenomenon, such as land surface elevation, soil type, geology, or vegetation. It is this second approach that is considered in this book. The term ‘pattern recognition’ is used to describe the procedures involved in relating vectors of measurements that are spatially referenced to individual pixel locations to the types or categories into which the phenomenon of interest is subdivided. If, for example, the phenomenon of interest is agricultural crops, then the categories are the individual crop types. Each crop type is represented in the thematic image by a numerical label. Vectors of measurements that are spatially referenced to individual pixel locations include image pixel values plus derived values such as texture, coherence, or context, as well as other geographical data that can be related to the pixel location, such as terrain elevation and slope, geology and soil type.

Digital thematic maps can be represented in two ways, using either the raster or the vector models. The vector model uses the classical cartographic representation of map objects in terms of points, lines and areas. Using this model, a continuously varying spatial attribute, such as terrain elevation, is represented by contour lines and spot heights, whilst an attribute such as soil type or underlying geology is represented in terms of boundary lines that enclose areas that are homogenous with respect to the property of interest and at the chosen scale of observation. The raster model represents spatial attributes in terms of their values over a contiguous set of small individual (and usually square) areas. Thus, variations in land surface elevation over a region of interest are represented by numerical

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