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ee.FeatureCollection.randomPoints
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AI-generated Key Takeaways
ee.FeatureCollection.randomPoints generates points that are uniformly random within a given geometry.
The distribution of the generated points depends on the dimension of the input geometry.
The function takes arguments for the region, number of points, seed for randomness, and maximum error.
The function returns a FeatureCollection of the generated points.
Examples are provided for generating random points using both JavaScript and Python.
Generates points that are uniformly random in the given geometry. If the geometry is two-dimensional (polygon or multi-polygon) then the returned points are uniformly distributed on the given region of the sphere. If the geometry is one-dimensional (linestrings), the returned points are interpolated uniformly along the geometry's edges. If the geometry has dimension zero (points), the returned points are sampled uniformly from the input points. If a multi-geometry of mixed dimension is given, points are sampled from the component geometries with the highest dimension.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-02-20 UTC."],[],["The `ee.FeatureCollection.randomPoints` function generates a specified number of random points within a given geometry. The points are uniformly distributed within the geometry's area if it's two-dimensional, along its edges if one-dimensional, or sampled from the input points if zero-dimensional. For mixed-dimension multi-geometries, points are drawn from the highest-dimension components. The user defines the `region`, the number of `points`, a random `seed`, and an optional `maxError`.\n"]]