In this comprehensive tutorial, you'll explore the process of unsupervised classification for remote sensing imagery, starting from image import and creating a composite. Learn how to perform extraction by masking, apply Principal Component Analysis (PCA) for dimensionality reduction, and classify land cover using unsupervised techniques.
The video also covers how to identify land cover classes, layout your map with essential marginal information such as scale, legend, and title.
Finally, you will learn how to analyze and compare land cover changes over time using Excel for a deeper insight into environmental transformations.
Негізгі бет Unsupervised Classification in ArcMap: Image Import, Masking, PCA, and Land Cover Change Analysis
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