Predicting mattic epipedons in the northeastern Qinghai-Tibetan Plateau using Random Forest

Baker, 2008, Optimisation of pedotransfer functions using an artificial neural network ensemble method, Geoderma, 144, 212, 10.1016/j.geoderma.2007.11.016 Barik, 2014, Spatial variability in soil compaction properties associated with field traffic operations, Catena, 120, 122, 10.1016/j.catena.2014.04.013 Becker, 1988, Relative sensitivity of normalized difference vegetation index (NDVI) and microwave polarization difference index (MPDI) for vegetation and desertification monitoring, Remote Sens. Environ., 24, 297, 10.1016/0034-4257(88)90031-4 Böhner, 2002, Soil regionalization by means of terrain analysis and process parameterization, European Soil Bureau-Research Report, 7, 213 Breiman, 2001, Random forests, Mach. Learn., 45, 5, 10.1023/A:1010933404324 de Bruin, 1998, Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM), Geoderma, 83, 17, 10.1016/S0016-7061(97)00143-2 Cambule, 2015, Rescue and renewal of legacy soil resource inventories: a case study of the Limpopo National Park, Mozambique, Catena, 125, 169, 10.1016/j.catena.2014.10.019 Chen, 2008, Mapping soil organic carbon concentration for multiple fields with image similarity analysis, Soil Sci. Soc. Am. J., 72, 186, 10.2136/sssaj2007.0028 Chen, 2010, Consistency of accuracy assessment indices for soft classification: simulation analysis, ISPRS J. Photogramm. Remote Sens., 65, 156, 10.1016/j.isprsjprs.2009.10.003 Chen, 2014, Forested landslide detection using LiDAR data and the random forest algorithm: a case study of the Three Gorges, China, Remote Sens. Environ., 152, 291, 10.1016/j.rse.2014.07.004 Cooper, 2015, Pre-operative prediction of surgical morbidity in children: comparison of five statistical models, Comput. Biol. Med., 57, 54, 10.1016/j.compbiomed.2014.11.009 Cooperative Research Group on Chinese Soil Taxonomy, 2001, 22 Cracknell, 2014, Mapping geology and volcanic-hosted massive sulfide alteration in the Hellyer - Mt Charter region, Tasmania, using Random Forests™ and Self-Organising Maps, Aust. J. Earth Sci., 61, 287, 10.1080/08120099.2014.858081 Diaz-Uriarte, 2006, Gene selection and classification of microarray data using random forest, BMC Bioinformatics, 7, 10.1186/1471-2105-7-3 Florinsky, 1998, Accuracy of local topographic variables derived from digital elevation models, Int. J. Geogr. Inf. Sci., 12, 47, 10.1080/136588198242003 Gallaher, 1976, A semiautomated procedure for total nitrogen in plant and soil samples, Soil Sci. Soc. Am. J., 40, 887, 10.2136/sssaj1976.03615995004000060026x Gong, 1999, 1 Grimm, 2008, Soil organic carbon concentrations and stocks on Barro Colorado Island - digital soil mapping using Random Forests analysis, Geoderma, 146, 102, 10.1016/j.geoderma.2008.05.008 Grunwald, 2009, Multi-criteria characterization of recent digital soil mapping and modeling approaches, Geoderma, 152, 195, 10.1016/j.geoderma.2009.06.003 Guo, 2015, Digital mapping of soil organic matter for rubber plantation at regional scale: an application of random forest plus residuals kriging approach, Geoderma, 237-238, 49, 10.1016/j.geoderma.2014.08.009 Henderson, 2005, Australia-wide predictions of soil properties using decision trees, Geoderma, 124, 383, 10.1016/j.geoderma.2004.06.007 Heung, 2014, Predictive soil parent material mapping at a regional-scale: a Random Forest approach, Geoderma, 214-215, 141, 10.1016/j.geoderma.2013.09.016 Huete, 1988, A soil-adjusted vegetation index (SAVI), Remote Sens. Environ., 25, 295, 10.1016/0034-4257(88)90106-X IUSS Working Group WRB, 2014, World reference base for soil resources 2014, update 2015 Jafari, 2012, Spatial prediction of USDA- great soil groups in the arid Zarand region, Iran: comparing logistic regression approaches to predict diagnostic horizons and soil types, Eur. J. Soil Sci., 63, 284, 10.1111/j.1365-2389.2012.01425.x Kempen, 2012, Efficiency comparison of conventional and digital soil mapping for updating soil maps, Soil Sci. Soc. Am. J., 76, 2097, 10.2136/sssaj2011.0424 Knotters, 1995, A comparison of kriging, co-kriging and kriging combined with regression for spatial interpolation of horizon depth with censored observations, Geoderma, 67, 227, 10.1016/0016-7061(95)00011-C Kohavi, 1997, Wrappers for feature subset selection, Artif. Intell., 97, 273, 10.1016/S0004-3702(97)00043-X Kotsiantis, 2007, Supervised machine learning: a review of classification techniques, Informatica, 31, 249 Kursa, 2010, Feature selection with the Boruta Package, J. Stat. Softw., 36, 1, 10.18637/jss.v036.i11 Lamorski, 2008, Using support vector machines to develop pedotransfer functions for water retention of soils in Poland, Soil Sci. Soc. Am. J., 72, 1243, 10.2136/sssaj2007.0280N Lane, 2002, Generalized linear models in soil science, Eur. J. Soil Sci., 53, 241, 10.1046/j.1365-2389.2002.00440.x Liaw, 2002, Classification and regression by randomForest, R News, 2, 18 Liess, 2012, Uncertainty in the spatial prediction of soil texture: comparison of regression tree and Random Forest models, Geoderma, 170, 70, 10.1016/j.geoderma.2011.10.010 Lin, 2010, Effects of human activities on organic carbon storage in the Kobresia hummilis meadow ecosystem on the Tibetan Plateau, Acta Ecol. Sin., 30, 4012 Liu, 2008, Mapping within-field soil drainage using remote sensing, DEM and apparent soil electrical conductivity, Geoderma, 143, 261, 10.1016/j.geoderma.2007.11.011 McBratney, 2003, On digital soil mapping, Geoderma, 117, 3, 10.1016/S0016-7061(03)00223-4 McKenzie, 1999, Spatial prediction of soil properties using environmental correlation, Geoderma, 89, 67, 10.1016/S0016-7061(98)00137-2 Minasny, 2007, Incorporating taxonomic distance into spatial prediction and digital mapping of soil classes, Geoderma, 142, 285, 10.1016/j.geoderma.2007.08.022 Moore, 1993, Soil attribute prediction using terrain analysis, Soil Sci. Soc. Am. J., 57, 443, 10.2136/sssaj1993.03615995005700020026x Nelson, 1982, Total carbon, organic carbon, and organic matter, 539 Pahlavan Rad, 2014, Updating soil survey maps using random forest and conditioned Latin hypercube sampling in the loess derived soils of northern Iran, Geoderma, 232-234, 97, 10.1016/j.geoderma.2014.04.036 Pal, 2005, Random forest classifier for remote sensing classification, Int. J. Remote Sens., 26, 217, 10.1080/01431160412331269698 Pouteau, 2011, Downscaling MODIS-derived maps using GIS and boosted regression trees: the case of frost occurrence over the arid Andean highlands of Bolivia, Remote Sens. Environ., 115, 117, 10.1016/j.rse.2010.08.011 Prasad, 2006, Newer classification and regression tree techniques: bagging and random forests for ecological prediction, Ecosystems, 9, 181, 10.1007/s10021-005-0054-1 Qi, 1994, A modified soil adjusted vegetation index, Remote Sens. Environ., 48, 119, 10.1016/0034-4257(94)90134-1 Qi, 2006, Fuzzy soil mapping based on prototype category theory, Geoderma, 136, 774, 10.1016/j.geoderma.2006.06.001 R Development Core Team, 2014 Riley, 1999, A terrain ruggedness index that quantifies topographic heterogeneity, Intermountain Journal of Sciences, 5, 23 Saga Development Team, 2011 Selige, 2006, High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures, Geoderma, 136, 235, 10.1016/j.geoderma.2006.03.050 Simbahan, 2006, Fine-resolution mapping of soil organic carbon based on multivariate secondary data, Geoderma, 132, 471, 10.1016/j.geoderma.2005.07.001 Soil Survey Staff, 2014, 37 Svetnik, 2003, Random forest: a classification and regression tool for compound classification and QSAR modeling, J. Chem. Inf. Model., 43, 1947 2000, 1 Wu, 2014, Relative effects of climatic and local factors on fire occurrence in boreal forest landscapes of northeastern China, Sci. Total Environ., 493, 472, 10.1016/j.scitotenv.2014.06.011 Yang, 2014, Organic matter controls of soil water retention in an alpine grassland and its significance for hydrological processes, J. Hydrol., 519, 3086, 10.1016/j.jhydrol.2014.10.054 Yang, 2016, Comparison of boosted regression tree and random forest models for mapping topsoil organic carbon concentration in an alpine ecosystem, Ecol. Indic., 60, 870, 10.1016/j.ecolind.2015.08.036 Yu, 2004, Efficient feature selection via analysis of relevance and redundancy, J. Mach. Learn. Res., 5, 1205 Zeng, 2013, Impact of alpine meadow degradation on soil hydraulic properties over the Qinghai-Tibetan Plateau, J. Hydrol., 478, 148, 10.1016/j.jhydrol.2012.11.058 Zevenbergen, 1987, Quantitative analysis of land surface topography, Earth Surf. Proc. Land., 12, 47, 10.1002/esp.3290120107 Zhu, 2008, Purposive sampling for digital soil mapping for areas with limited data, 233