Some basics of the science of Remote Sensing / Image Analysis:<br /><br />The identification of objects and determination of their significance involves: <br /><br /><b>Identification</b> - recognizing features on the image.<br /><br /><b>Measurement</b> - once features have been identified, can make measurements (i.e., the distance between objects, the number of features per unit area). <br /><br /><b>Interpretation</b> - normally based on a systematic examination of the primitive elements of the photograph, in conjunction with a wide range of ancillary data. <br /><br />Primitive elements include tone, color, size, shape, texture, pattern, shadow, site, association automated image analysis typically relies on only the first few primitive elements (tone, color, size) ancillary data are often very diverse, may include maps, vegetation phenologies, and many kinds of information about human activities in the general area human experts bring all these elements, plus their acquired skills and knowledge of related disciplines <font color="yellow">the best photointerpreters have expertise in such related disciplines as physical geography, geology and plant <br />biology and ecology.</font><br /> <br />Human interpretation also includes a significant perceptual or subjective component.<br /><br /><b>Classification</b><br /><br />The information obtained from a remote sensing instrument consists of reflectance measurements, often in several different bands or parts of the electromagnetic spectrum. Measurements are in discrete units with fixed range, e.g. 0-255.<br /><br />The process of classification, an important part of image interpretation, attempts to assign each pixel to one of a number of classes based on its reflectance in one or more bands e.g. vegetation types or land use classes ("urban", "pasture", "cropland", "water", "forested"). <br /><br />Many techniques exist for classification:<br /> <br />Supervised classification develops the rules for assigning reflectance measu <div class="Discussion_UserSignature"> <p><em>Differential Diagnosis: </em>"<strong><em>I am both amused and annoyed that you think I should be less stubborn than you are</em></strong>."<br /> </p> </div>