Evaluation of modelling approaches for predicting the spatial distribution of soil organic carbon stocks at the national scale

Geoderma

Volumn 223-225, Issue 1, 2014, Pages 97-107

  Martin, M P ^a   Orton, T G ^b   Lacarce, E ^a   Meersmans, J ^c   Saby, N P A ^a   Paroissien, J B ^a   Jolivet, C ^a   Boulonne, L ^a   Arrouays, D ^a  

^a Centre d'Orléans   (France)

^b UNIVERSITY OF SYDNEY   (Australia)

^c UNIVERSITY OF EXETER   (United Kingdom)

Author keywords

Boosted regression trees; Geostatistics; National accounting; Soil organic carbon; Spatial distributions

Indexed keywords

CARBON; CLIMATE CHANGE; COMPLEX NETWORKS; FORECASTING; FORESTRY; REGRESSION ANALYSIS; SOILS; SPATIAL DISTRIBUTION; SPATIAL VARIABLES MEASUREMENT; STATISTICAL TESTS;

BOOSTED REGRESSION TREES; GEO-STATISTICS; GEOSTATISTICAL MODELLING; MULTIPLE REGRESSION MODEL; NATIONAL ACCOUNTING; SOIL ORGANIC CARBON; SOIL ORGANIC CARBON STOCKS; SPATIAL AUTOCORRELATIONS;

SOIL TESTING;

AUTOCORRELATION; CARBON BUDGET; DATA SET; GEOSTATISTICS; MONITORING SYSTEM; NUMERICAL MODEL; ORGANIC CARBON; PREDICTION; SOIL ORGANIC MATTER; SPATIAL DISTRIBUTION;

CARBON; FORECASTS; REGRESSION ANALYSIS; SEASONAL VARIATION; SOIL; STATISTICAL ANALYSIS;

FRANCE;

EID: 84897409715     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2014.01.005     Document Type: Article

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