General-to-part type triangular network multi-threading parallel generation method for massive terrain big data cloud

Abstract

The invention discloses a general-to-part type triangular network multi-threading parallel generation method for massive terrain big data cloud. The method comprises the following steps: proposing self-adaptive grid space division to realize the balance scale grid distribution of the massive cloud data; building a center spacing sequencing rules of point data spaces in the grid to reasonably arrange the sequence of participating structure TIN of center points in the grid; preferentially performing the locating and inserting method and the topological insertion algorithm of the traditional TIN according to the general-to-part mode to model data point among the grids, in order to avoid the dividing and rule modeling based grid combing process which is complex and low in efficiency; building a topological closure detecting mechanism of the grid; starting independent and parallel multi-threading to model the rest modeling points according to the traditional topological insertion algorithm for each space grid at the proper time, so as to realize the triangular network modeling work of the whole space under the parallel, efficient and general-to-part mode. With the adoption of the method, the space modeling supporting capacity for the massive cloud big data is obviously improved.

Description

technical field [0001] The invention relates to the technical field of engineering simulation, in particular to a multi-threaded parallel generation method of total-fraction triangulation for point clouds of massive topographical big data. Background technique [0002] The academically recognized mainstream methods of Delaunay triangulation modeling include point-by-point insertion method, growth method and divide-and-conquer-synthesis method. The divide-and-conquer-synthesis method is based on the former two methods, and the most mature and general triangulation modeling method among the two basic methods is the point-by-point insertion method, but this method is only suitable for small-scale point data modeling. [0003] There are many Chinese and foreign professional literatures introducing the technology of interpolation to construct triangulation. Among them, "Research on the method of fast construction of triangulation digital terrain model" (2001.12, Pu Hao, China Rai...

AI Technical Summary

Problems solved by technology

[0004] The biggest problem of the triangulation modeling algorithm is the time complexity of the calculation, because the formation of each triangulation involves all the points to be processed, and it is difficult to so

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