Sparse logistic regression and polynomial modelling for detection of artificial drainage networks
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||10|
|Journal||Remote Sensing Letters|
|Publication status||Published - 3 Apr 2015|
|Publication type||A1 Journal article-refereed|
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.