Mots-clés
Autocorrélation spatiale Corée du Sud Distribution spatiale Dune Humidité du sol Littoral Modèle Méthode des moindres carrés Sindu Sol Surface de tendance Coastal environment Dune Least squares method Model Soil Soil moisture South Korea Spatial autocorrelation Spatial distribution Trend surface Autocorrelación espacial Corea del Sur Distribución espacial Duna Humedad del suelo Litoral Modelo Método de los minimos cuadrados Suelo Superficie de tendenciaIncorporation of multi-scale spatial autocorrelation in soil moisture–landscape modeling
Auteur(s) et Affiliation(s)
KIM, D.
Dept. of Geography, Biogeomorphology Research and Analysis Group, Univ. of Kentucky, Lexington, Etats-Unis
Description :
Based on soil, vegetation, and topographic data collected in the Sindu coastal dunefield in western Korea, this research developed 3 soil moisture–landscape models, each incorporating spatial autocorrelation (SAC) at fine, broad, and multiple scales, respectively, into a non-spatial ordinary least squares (OLS) model. All of these spatially explicit models showed better performance than the OLS model. In particular, the best model was proved to be the one using spatial eigenvector mapping, a technique that accounts for spatial structure at multiple scales simultaneously. It is highlighted that the conventional regression modeling may have a reduced predictive power in reality, in cases where they possess a significant amount of SAC. This research demonstrates that accounting for spatial structure allows a better understanding of dynamic soil hydrological processes occurring at different spatial scales.
Type de document :
Article de périodique
Source :
Physical geography, issn : 0272-3646, 2013, vol. 34, n°. 6, p. 441-455, nombre de pages : 15, Références bibliographiques : 39 ref.
Date :
2013
Editeur :
Pays édition : Royaume-Uni, Abingdon, Taylor and Francis
Langue :
Anglais
Anglais
Droits :
Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI)
Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI)