Spatial variation of shear strength properties incorporating auxiliary variables

[1]  G. Najar,et al.  Application of predictor variables in spatial quantification of soil organic carbon and total nitrogen using regression kriging in the North Kashmir forest Himalayas , 2020 .

[2]  H. Rahardjo,et al.  Role of Unsaturated Soil Properties in The Development of Slope Susceptibility Map , 2020 .

[3]  A. Marchetti,et al.  Predictive mapping of soil organic carbon in Northeast Algeria , 2020 .

[4]  H. Rahardjo,et al.  Three-dimensional slope stability analysis incorporating unsaturated soil properties in Singapore , 2020 .

[5]  Brian G. Peterson,et al.  Econometric Tools for Performance and Risk Analysis [R package PerformanceAnalytics version 2.0.4] , 2020 .

[6]  H. Oh,et al.  Influence of subsurface flow by Lidar DEMs and physical soil strength considering a simple hydrologic concept for shallow landslide instability mapping , 2019, CATENA.

[7]  Xiao-Lin Sun,et al.  Can regression determination, nugget-to-sill ratio and sampling spacing determine relative performance of regression kriging over ordinary kriging? , 2019, CATENA.

[8]  Chunying Ren,et al.  Assessment of multi-wavelength SAR and multispectral instrument data for forest aboveground biomass mapping using random forest kriging , 2019, Forest Ecology and Management.

[9]  M. Goyal,et al.  Influences of watershed characteristics on long-term annual and intra-annual water balances over India , 2019, Journal of Hydrology.

[10]  Wengang Zhang,et al.  Engineering properties of the Bukit Timah Granitic residual soil in Singapore , 2019, Underground Space.

[11]  H. Rahardjo,et al.  Spatial variations of air-entry value for residual soils in Singapore , 2019, CATENA.

[12]  Marvin N. Wright,et al.  Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables , 2018, PeerJ.

[13]  T. Behrens,et al.  Spatial modelling with Euclidean distance fields and machine learning , 2018, European Journal of Soil Science.

[14]  Binh Thai Pham,et al.  Prediction of shear strength of soft soil using machine learning methods , 2018, CATENA.

[15]  G. Raspa,et al.  Spatial variability analysis of soil strength to slope stability assessment , 2017 .

[16]  M. R. Taharin,et al.  Comparison of Cohesion (c’), and Angle of Internal Friction (Ф’) Distribution in Highland Area of Kundasang by using Ordinary Kriging and Simple Kriging. , 2017 .

[17]  Katarzyna Pentoś,et al.  Applying an artificial neural network approach to the analysis of tractive properties in changing soil conditions , 2017 .

[18]  P. Raha,et al.  Deterministic approach for susceptibility assessment of shallow debris slide in the Darjeeling Himalayas, India , 2016 .

[19]  Edzer Pebesma,et al.  Spatio-Temporal Interpolation using gstat , 2016, R J..

[20]  Hehua Zhu,et al.  Combination of Kriging methods and multi-fractal analysis for estimating spatial distribution of geotechnical parameters , 2016, Bulletin of Engineering Geology and the Environment.

[21]  E. Pebesma,et al.  Classes and Methods for Spatial Data , 2015 .

[22]  Philippe Lagacherie,et al.  Evaluating Digital Soil Mapping approaches for mapping GlobalSoilMap soil properties from legacy data in Languedoc-Roussillon (France) , 2015 .

[23]  Zhi-Wei Liu,et al.  Digital mapping of soil organic matter for rubber plantation at regional scale: An application of random forest plus residuals kriging approach , 2015 .

[24]  Florian Hartig,et al.  Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass , 2014 .

[25]  Raphael A. Viscarra Rossel,et al.  Mapping gamma radiation and its uncertainty from weathering products in a Tasmanian landscape with a proximal sensor and random forest kriging , 2014 .

[26]  S. Joost,et al.  Spatial variability of soil phosphorus in the Fribourg canton, Switzerland , 2014 .

[27]  Jean Canou,et al.  Effects of fines and water contents on the mechanical behavior of interlayer soil in ancient railway sub-structure , 2013 .

[28]  Seung-Rae Lee,et al.  Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event , 2013 .

[29]  Edzer Pebesma,et al.  Spatial Data Import and Export , 2013 .

[30]  Delwyn G. Fredlund,et al.  Unsaturated Soil Mechanics in Engineering Practice , 2012 .

[31]  E. Leong,et al.  Variability of residual soil properties , 2012 .

[32]  David J. Chittleborough,et al.  The effect of terrain and management on the spatial variability of soil properties in an apple orchard , 2012 .

[33]  S. Harwant,et al.  Residual soils of Southeast Asia , 2012 .

[34]  J. H. Curran,et al.  On Using Spatial Methods For Heterogeneous Slope Stability Analysis , 2012 .

[35]  Yong Li,et al.  Can the spatial prediction of soil organic matter contents at various sampling scales be improved by using regression kriging with auxiliary information , 2010 .

[36]  Henry Lin,et al.  Comparing Ordinary Kriging and Regression Kriging for Soil Properties in Contrasting Landscapes , 2010 .

[37]  Leonardo Cascini,et al.  Susceptibility analysis of shallow landslides source areas using physically based models , 2010 .

[38]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[39]  Kang-Tsung Chang,et al.  Application of radar data to modeling rainfall-induced landslides , 2009 .

[40]  M. S. D. Junior,et al.  Relation of strength and mineralogical attributes in Brazilian latosols , 2009 .

[41]  Rex L. Baum,et al.  Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework , 2008 .

[42]  G. Exadaktylos,et al.  A spatial estimation model for continuous rock mass characterization from the specific energy of a TBM , 2008 .

[43]  Gerard B. M. Heuvelink,et al.  About regression-kriging: From equations to case studies , 2007, Comput. Geosci..

[44]  B. Minasny,et al.  Spatial prediction of soil properties using EBLUP with the Matérn covariance function , 2007 .

[45]  Z. Shi,et al.  Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods , 2007 .

[46]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[47]  Thiam-Soon Tan,et al.  Equivalent granular void ratio for characterization of Singapore's Old Alluvium , 2006 .

[48]  B. Diekkrüger,et al.  Geostatistical co-regionalization of soil hydraulic properties in a micro-scale catchment using terrain attributes , 2006 .

[49]  Ramón Díaz-Uriarte,et al.  Gene selection and classification of microarray data using random forest , 2006, BMC Bioinformatics.

[50]  H. Marui,et al.  A New Method for the Correlation of Residual Shear Strength of the Soil with Mineralogical Composition , 2005 .

[51]  Edzer J. Pebesma,et al.  Multivariable geostatistics in S: the gstat package , 2004, Comput. Geosci..

[52]  R. B. Rezaur,et al.  Characteristics of residual soils in Singapore as formed by weathering , 2004 .

[53]  G. Heuvelink,et al.  A generic framework for spatial prediction of soil variables based on regression-kriging , 2004 .

[54]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[55]  M. Van Meirvenne,et al.  Kriging soil texture under different types of nonstationarity , 2003 .

[56]  Alex B. McBratney,et al.  A comparison of prediction methods for the creation of field-extent soil property maps , 2001 .

[57]  R. Webster,et al.  Geostatistics for Environmental Scientists , 2001 .

[58]  E. Harp,et al.  A method for producing digital probabilistic seismic landslide hazard maps , 2000 .

[59]  Timothy C. Coburn,et al.  Geostatistics for Natural Resources Evaluation , 2000, Technometrics.

[60]  Dominique King,et al.  Comparison of kriging with external drift and simple linear regression for predicting soil horizon thickness with different sample densities. , 2000 .

[61]  Kelly Elder,et al.  Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed , 2000 .

[62]  Jian Zhao,et al.  Geological and geotechnical features of Singapore: An overview , 1999 .

[63]  J. Lester,et al.  Geostatistical analysis of sampling uncertainty at the Tollesbury Managed Retreat site in Blackwater Estuary, Essex, UK: Kriging and cokriging approach to minimise sampling density , 1998 .

[64]  K. W. Glennie,et al.  Geology and Geomorphology , 1998 .

[65]  A. McBratney,et al.  Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging , 1995 .

[66]  V. Choa,et al.  A study of the weathering of the bukit timah granite part a: Review, field observations and geophysical survey , 1994 .

[67]  Roger Moore,et al.  The chemical and mineralogical controls upon the residual strength of pure and natural clays , 1991 .

[68]  Alex B. McBratney,et al.  Further Comparison of Spatial Methods for Predicting Soil pH , 1990 .

[69]  R. Cantoni,et al.  A CORRELATION BETWEEN RESIDUAL FRICTION ANGLE, GRADATION AND THE INDEX PROPERTIES OF COHESIVE SOILS. TECHNICAL NOTE , 1989 .

[70]  Noel A Cressie,et al.  Spatial prediction and ordinary kriging , 1988 .

[71]  M. A. Oliver,et al.  The elucidation of soil pattern in the Wyre Forest of the West Midlands, England. II. Spatial distribution. , 1987 .

[72]  J. Pitts.  A review of geology and engineering geology in Singapore , 1984, Quarterly Journal of Engineering Geology.

[73]  P. R. Vaughan,et al.  The drained residual strength of cohesive soils , 1981 .

[74]  Peter Lumb,et al.  Safety factors and the probability distribution of soil strength , 1970 .

[75]  G. Matheron.  Principles of geostatistics , 1963 .

[76]  D. Krige.  A statistical approach to some basic mine valuation problems on the Witwatersrand, by D.G. Krige, published in the Journal, December 1951 : introduction by the author , 1951 .