A4 Article in conference proceedings
Arctic soil hydraulic conductivity and soil type recognition based on aerial gamma-ray spectroscopy and topographical data

List of Authors: Jonne Pohjankukka, Paavo Nevalainen, Tapio Pahikkala, Pekka Hänninen, Eija Hyvönen, Raimo Sutinen, Jukka Heikkonen
Publication year: 2014
Book title *: 22nd International conference on pattern recognition
ISBN: 978-1-4799-5208-3


A central characteristic of soil in the arctic is its load bearing capacity since that property influences forest harvester mobility, flooding dynamics and infrastructure potential. The hydraulic conductivity has the greatest dynamical influence to bearing capacity and hence is essential to measure or estimate. In addition, the arctic soil type information is needed in many

cases, e.g. in roads and railways building planning. In this paper we propose a method for hydraulic conductivity estimation via linear regression on aerial gamma-ray spectroscopy and

publicly available topographical data with derived elevation based features. The same data is also utilized for the arctic soil type recognition; both logistics regression and nearest neighbor

classification results are reported. The classification results for logistic regression resulted in 44.5 % prediction performance and 50.5 % for 8-nearest neighbor classifier respectively. Linear

regression results for estimating the hydraulic conductivity of the soil resulted in C-index value of 0.63. The hydraulic conductivity and soil type estimation results are promising and the proposed

topographic elevation features are apparently new for remote sensing community and should also have a wider general interest.

Last updated on 2019-29-01 at 12:07