: It natively executes both supervised (user-guided training) and unsupervised (automated clustering) classification techniques. This allows users to conduct complex Land Use and Land Cover (LULC) studies to map out physical features across various timelines.
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The software provides a robust environment for land cover classification, allowing users to transform raw imagery into actionable information. It supports both and unsupervised classification , which are critical for identifying terrestrial features, vegetation types, and land-use changes based on spectral signatures. 3. LiDAR Tools erdas imagine software
Understanding ERDAS IMAGINE: The Industry Standard for Geospatial Data Authoring erdas imagine software