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

作者：Liimatainen Kaisa^*; Heikkila Raimo; Yli Harja Olli; Huttunen Heikki; Ruusuvuori Pekka

来源：Remote Sensing Letters, 2015, 6(4): 311-320.

DOI：10.1080/2150704X.2015.1031919

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.

• 出版日期2015-4-3