Trellis drainage recognition method

Abstract

The invention discloses a trellis drainage recognition method. The method comprises the steps that (1) line layer data of to-be-recognized drainage in an shp format is acquired and read into a datasetL={l|i=0,1,2,...,m}; (2) total length RL of the to-be-recognized drainage and drainage straight feature factors SL are obtained through calculation according to the dataset L; (3) river accumulated length in each azimuth interval is obtained through statistical analysis according to the dataset L, and statistical results are stored in a list DL; (4) drainage main trend ratio factors Rratio anddrainage main trend included-angle factors Rangle are obtained through calculation according to the list DL and the drainage total length RL; (5) trellis drainage type recognition is performed basedon SL, Rratio and Rangle; and (6) a trend rose diagram is drawn for the recognized trellis drainage. Through the method, the trellis drainage is recognized based on vector data, algorithm complexity is low, and recognition accuracy is high.

Description

technical field [0001] The invention relates to the application field of geographic information technology, in particular to a method for identifying a grid-like water system based on vector data. Background technique [0002] In 1957, Leopold and Wolman first systematically proposed to use the plane shape of the river to distinguish the water system (see Leopold L, Wolman M G. River channel patterns: braided, meandering, and straight [R], U.S. Geol. Surv.: 282- B.1957.), since then, scholars at home and abroad have discussed and expanded this classification method, and summarized many types of water systems such as dendritic water systems, lattice water systems, radial water systems, ring water systems, parallel water systems, and feather water systems. type of water system. [0003] In nature, the areas where the same type of water system often have similar geological structures and natural environments. By analyzing the arrangement and plane shape of the water system, t...

AI Technical Summary

Problems solved by technology

However, the automatic identification methods for water system types are relatively limited, and the main ones retrieved are: Wang Yichuan used binarized water system images and based on the optimal statistical image classifier, formed a water system classification method based on water system texture units (see Wang Yichuan .Research on automatic classification of water systems [D]. Southwest Jiaotong University, 2006.); Che Guoquan used syntax pattern recognition technology to automatically identify images of braided water systems (see Che Guoquan. Automatic recognition of braided water systems [D ]. Southwest Jiaotong University, 2007.)

Although the relevant water system type identification method can identify the water system type to a certain extent, because it uses binary water system images instead of directly using water system vector data, the complexity of the algorithm is high and the recognition effect is poor

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