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Sparse logistic regression and polynomial modelling for detection of artificial drainage networks

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)311-320
Number of pages10
JournalRemote Sensing Letters
Volume6
Issue number4
DOIs
Publication statusPublished - 3 Apr 2015
Publication typeA1 Journal article-refereed

Abstract

Mire ditching changes dramatically mire biodiversity. Thus, drainage network detection is an important factor when analysing the natural state of a mire. In this article, we propose a method for automated drainage network detection from raster digital terrain model created from high-resolution laser scanning data. Sparse logistic regression classifier with a large generic feature set and automated feature selection is used for classification. Broken segments are connected with polynomial modelling. The results showed that our method can accurately detect artificial drainage networks.