CHAPTER 4 – Data Models

Publisher Summary This chapter discusses common data models, providing the link among the physical remote sensing models, the sensor models, and image processing algorithms with examples. The connection among radiation, sensor models, and data models are also discussed and explored by simulation. The chapter concludes the following points: (1) the spectral statistics of remote-sensing image data are influenced by the topography in the scene and the topographic effect tends to correlate the data among spectral bands along a straight line through the origin of the reflectance scattergram; (2) the spectral statistics of remote-sensing image data are also influenced by the sensor's spectral passband locations and widths and noise characteristics; and random, spatially uncorrelated sensor noise increases the within-class variance of all surface materials equally; (3) the spatial and spectral statistics of remote-sensing image data are influenced by the sensor's spatial response function, which increases the spatial correlation length, reduces within-class variance, and creates mixed spectral vectors.