Volume 10, Issue 2 , September 2018, , Pages 75-94
Abstract
Repairing incorrect polygons for use in GIS software is semi-automated and time-consuming.Automatic polygon repair, interpretation of obscure polygons, and elimination of all existing bugsbased on definitions and global standards that have many uses in software related to GIS. Due to thecomplexity of ...
Read More
Repairing incorrect polygons for use in GIS software is semi-automated and time-consuming.Automatic polygon repair, interpretation of obscure polygons, and elimination of all existing bugsbased on definitions and global standards that have many uses in software related to GIS. Due to thecomplexity of the computation and data volumes in working with big data, there is always acompetition between the speed and the amount of memory used. In this paper, while introducing thestandard of the characteristics of simple complications in polygons, using Delaunay Triangulation andGTS functions in Java and with the help of the H2 database, a method is presented that receivespolygons in the form of a file in the CSV format and applies several effective algorithms toautomatically repair them. The polygons in the spatial data set are automated at optimal time and withminimal memory consumption and are repaired if necessary. The results show that this method,compared with the previous ones, our method leads to relative improvement in execution speed andprovides more than 50 percent saving (in average) in the main memory while working with big data.
