Prediction of soil depth using environmental variables in an anthropogenic landscape, a case study in the Western Ghats of Kerala, India

Auteur(s) et Affiliation(s)

KURIAKOSE, S.L.

United Nations University - ITC School for Disaster Geo-Information Management. International Inst. for Geo-information Science and Earth Observation, Enschede, Pays-Bas

DEVKOTA, S.

Forum for Energy and Environmental Development (FEED), Kathmandu, Nepal

ROSSITER, D.G.

United Nations University - ITC School for Disaster Geo-Information Management. International Inst. for Geo-information Science and Earth Observation, Enschede, Pays-Bas

JETTEN, V.G.

United Nations University - ITC School for Disaster Geo-Information Management. International Inst. for Geo-information Science and Earth Observation, Enschede, Pays-Bas

Description :
This study compares empirico-statistical methods with geostatistical methods for predicting soil depth in such a landscape: Aruvikkal catchment in the Western Ghats of Kerala, India. Regression kriging applied on blocks of 20 m by 20 m using the environmental covariates elevation, slope, aspect, curvature, wetness index, land use and distance from streams, proved to be the best predictor of soil depth. This model explains 52% of the variability of soil depth in the catchment; with a prediction variance of 0.05 to 0.19. A Gaussian simulation was attempted for a more realistic visualization of the depth, as opposed to the smooth kriging prediction. The most important explanatory variable of soil depth in this landscape is land use, as expected from the strong human intervention.

Type de document :
Article de périodique

Source :
Catena (Giessen), issn : 0341-8162, 2009, vol. 79, n°. 1, p. 27-38, nombre de pages : 12, Références bibliographiques : 1 p.

Date :
2009

Editeur :
Pays édition : Allemagne, Cremlingen-Destedt, Catena

Langue :
Anglais