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With an ever-increasing availability of aerial and satellite Earth observation data, image analysis has become an essential part of remote sensing. Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL combines theory, algorithms, and computer codes and conveys required proficiency in vector algebra and basic statistics. It covers such topics as basic Fourier transforms, wavelets, principle components, minimum noise fraction transformation, and othorectification. The text also discusses panchromatic sharpening, explores multivariate change detection, examines supervised and unsupervised land cover classification and hyperspectral analysis. With programming examples in IDL and applications that support ENVI, it offers many extensions, such as for data fusion, statistical change detection, clustering and supervised classification with neural networks, all available as downloadable source code.<br /><br />Focusing on pixel-oriented analysis of