Automatic identification method of geographical data change type

Abstract

The invention relates to a method of automatically recognizing types of changes in geographic national condition data, comprising the steps of acquiring data to be processed, recognizing data type ofthe data, and acquiring the data meeting a target data type; preprocessing data in a data processor; performing quality check on the preprocessed data according to change detection requirements; for the data passed the quality check, setting areal feature tolerance and linear feature tolerance of automatic recognition for change information of geographic national condition data; recognizing arealfeatures, linear features and point features of two geographic national condition feature datasets; subjecting the areal features, linear features and point features of the two geographic national condition feature datasets to identity superposition, and automatically recognizing change information of geographic national condition data; outputting the geographic national condition data having thechange information automatically recognized. By implementing the method of automatically recognizing types of changes in geographic national condition data, filling of change information can be accurately carried out to efficiently acquire geographic national condition data.

Description

technical field [0001] The invention belongs to the technical field of geographic national condition monitoring, and in particular relates to an automatic identification method for geographic national condition data change types. Background technique [0002] Vector data change detection is an important content of spatial data change detection. It is an applied technology based on computer image processing system to identify and analyze target changes in different periods. The existing vector data change detection technology is facing many difficult problems and difficulties, and domestic and foreign researchers have also done a lot of research on this. Tang Luliang, Yang Bisheng, etc. proposed a spatial data change detection algorithm based on the similarity of linear features by studying the relationship between spatial data changes and similarity, and realized the discovery and extraction of road data changes based on the similarity of linear figures. . Wan Yuan, Li Lin...

AI Technical Summary

Problems solved by technology

The research of the above-mentioned scholars still needs to be improved in terms of the efficiency and accuracy of actual production recognition, and the type of spatial data processed is relatively single, and there is almost no research involving full-coverage spatial data.

Images