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ALP 2307: REMOTE SENSING 2 - NOTES CHAPTER 5 - INFORMATION EXTRACTION 5.1 Supervised and Unsupervised Classification 5.2 Fuzzy Classification 5.3 Image Transformation 5.4 Principal Component Analysis Remote Sensing-Digital Image Processing Information Extraction 5.1 Image classification-Supervised IMAGE CLASSIFICATION - SUPERVISED 1. Introduction Classification is the technique by which real world objects/land covers are identified within remotely sensed imagery. Consider a multispectral image with m bands. In the case of a simplest pixel, its characteristics are expressed in the form of a vector where the vector elements represent the spectral properties of that pixel, which can be captured in these m bands. The number of classes can be determined a priori or using certain indices. The classes represented by this pixel may be water bodies, woodlands, grassland, agriculture, urban or other land cover types. Classification identifies the land cover represented by each pixel based on its spectral reflectance value (or digital number). The process also involves labeling each class entities using numerical value which can be done using a classification rule or a decision rule. In this context, the process of clustering involves an exploratory procedure wherein the aim is to estimate the number of distinct land cover classes present in an area and also to allocate pixels to these aforementioned classes. Image classification can be of many types. The two major classificatio ...
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