Method for fitting regular grid by discrete point grading and weighting

The invention discloses a method for quickly constructing a regular grid DEM (Digital Elevation Model) for ultra-large discrete point cloud data by adopting a hierarchical weighted fitting strategy. First of all, pyramid grading strategies are employed, the target regular grid is refined from one grid to an nth level according to 3*3 refining parameters; and the discrete point cloud is placed in the grid step by step in a weighted average mode until the nth level is reached, the result of the level serves as the initial value of the next level, and all the points are placed in the grid in a weighted average mode again to form a new grid until the interval of the grid is equal to the expected interval. The method is simple in operation, free of extra memory consumption and very high in execution efficiency, point cloud data operation is streaming operation, topological information of point clouds does not need to be considered, point number limitation does not exist, and the method is particularly suitable for regular gridding of mass point clouds.