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As a result, it became imperative to generalize the Feature Classes so that they can be used in a Feature Service as well as being taken offline.\nUsing configuration settings, the user may choose between using a Smoothing algorithm or Simplification algorithm to perform generalization. \nDocumentation on the Smoothing algorithm can be found here: https://pro.arcgis.com/en/pro-app/latest/tool-reference/cartography/smooth-polygon.htm\nDocumentation on the Simplification algorithm can be found here: https://pro.arcgis.com/en/pro-app/latest/tool-reference/cartography/simplify-polygon.htm\nNote: At the time of this writing, only polygon smoothing/simplification is tested. However, Linear datasets are also supported (FEATURE_TYPE)\n*Each of the features were generalized except for the labels (anno) and the point feature class in the admu blm webpub dataset. To keep the naming convention the same, we added the _gen after each feature class so this service and the data layers won\u2019t get confused with the other admu services. This service and the underlying data will be kept \u201cin-sync\u201d with national replication. \n\nThis feature class is the State Office level data from the feature level Dataset for the BLM Administrative Unit Boundaries Data Standard. The feature dataset includes both BLM administrative land areas and office locations. Land areas are depicted with polygons for the smallest administrative unit (field offices). Larger administrative units, such as district offices, and administrative states may be derived from these polygons. Office locations at each level are depicted with points.\n\nThis dataset is a subset of the official national dataset, containing features and attributes intended for public release and has been optimized for online map service performance. 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