1. Prediction of topsoil stoniness using soil type information and airborne gamma-ray data
- Author
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Karjalainen, Ville, Tokola, Timo, and Malinen, Jukka
- Subjects
Soils -- Properties ,Gamma rays -- Properties ,Earth sciences - Abstract
The stoniness of topsoil can have a significant impact on the cost-effectiveness and quality of work in mechanized forest operations. The operations and their models should be selected on a stand-specific basis, while the physical properties of the soil, including stoniness, to achieve maximum efficiency and to minimize the damage caused by heavy forest machinery. The aim of this study was to examine whether the stoniness of the topsoil can be predicted using the gamma-ray values available from geophysical data collected at low altitude and using soil type information. Stoniness was measured at several sites with various soil types, which were then divided into stoniness index classes (SICs) for further analysis by ordinal regression analysis using gamma-ray and soil type data. The predictions associated with SIC classification were 52% accurate and 79% acceptable ([+ or -]1 class from the correct class), with kappa values of 0.55 and 0.72, respectively. The SIC prediction results were promising and showed the potential of gamma-ray and soil type data for estimating topsoil stoniness. Key words: forest trafficability, gamma-ray radiation, stoniness index, ordinal regression, kappa. La pierrosite de la couche superieure du sol peut avoir un impact important sur la rentabilite et la qualite du travail dans le cas des operations forestieres mecanisees. Les operations et leurs modeles devraient etre selectionnes en fonction des caracteristiques du peuplement tout en tenant compte des proprietes physiques du sol, y compris la pierrosite, afin d'atteindre une efficacite maximale et de minimiser les dommages causes par la machinerie forestiere de grande taille. La presente etude visait a determiner si la pierrosite de la couche superieure du sol peut etre estimee a partir des valeurs de rayons gamma provenant de donnees geophysiques recoltees a basse altitude et des renseignements sur le type de sol. La pierrosite a ete mesuree dans plusieurs stations couvrant differents types de sol qui ont ensuite ete divises en classes d'indice de pierrosite (CIP). Les donnees de rayons gamma et le type de sol ont ensuite ete integres dans une analyse de regression ordinale. Les previsions associees a la classification par CIP etaient precises a 52% et acceptables a 79% (erreur de [+ or -] 1 classe par rapport a la bonne classe), avec des valeurs kappa de respectivement 0,55 et 0,72. Ces resultats provenant de la classification par CIP sont prometteurs et mettent en evidence le potentiel des donnees de rayons gamma et du type de sol pour estimer la pierrosite de la couche superieure du sol. [Traduit par la Redaction] Mots-cles: traficabilite forestiere, rayonnement gamma, indice de pierrosite, regression ordinale, kappa., 1. Introduction The interest towards small-scale variations in soil characteristics and terrain topography has increased in recent times due to the challenges posed by varying weather conditions during rainy spring [...]
- Published
- 2022
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