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Processing of digital terrain models for improving the reliability of the analysis of water basin morphometry
Abstract.The object of the study are open digital terrain models located on the Internet. The subject of the study is the procedure for eliminating the errors of digital terrain models aimed at increasing the reliability of calculations of the morphometric characteristics of basins of water bodies. This article is devoted to the improvement of methods for processing and modifying geoinformation features by processing digital high-altitude relief models. The approaches outlined in this paper are aimed at increasing the reliability of calculating the main morphometric characteristics of the relief by eliminating errors in the original data. Usually for morphometric analysis, cartographic works are used, according to which the defined relief forms contain subjective errors. The values of these errors can then affect the results of the analysis, since the quantitative characteristics depend on where and how the boundary of the form passes. Given the presence in the initial open data of a number of high-altitude distortions that indicate their inapplicability to use for qualitative morphometric analysis at the level of private watersheds, the paper considers ways to adjust their geometric characteristics by eliminating the influence of tree vegetation and preserving the relief's relief using the Lagrange coefficients. A comparison of the results of a particular morphometric analysis obtained using corrected relief models with results obtained from other data is given. To increase the reliability and automate the processing of the digital model of the river basin relief, which is a regular network, it is necessary to carry out analysis in private watersheds with an area from 0.6 to 0.8% of the total area of the basin.
Keywords: geoinformation system, normalized difference vegetation index, forest vegetation, digital elevation model, Lagrange interpolation polynomial, normal Gaussian distribution, geometric modeling, remote sensing data, morphometric analysis, open source
Article was received:30-05-2018
This article written in Russian. You can find full text of article in Russian here .