Soil depth prediction by digital soil mapping and its impact in pine forestry productivity in South Brazil

Competition and water stress indices as predictors of Pinus halepensis Mill. radial growth under drought

(2020) Manon Helluy et al.   FOREST ECOLOGY AND MANAGEMENT

Modeling forest site productivity using climate data and topographic imagery in Pinus elliottii plantations of central Argentina

(2020) Santiago Fiandino et al.   ANNALS OF FOREST SCIENCE

An integrated method of selecting environmental covariates for predictive soil depth mapping

(2019) Yuan-yuan LU et al.   Journal of Integrative Agriculture

Probability mapping of soil thickness by random survival forest at a national scale

(2019) Songchao Chen et al.   GEODERMA

The challenge of soil science meeting society's demands in a “post-truth”, “fact free” world

(2018) Johan Bouma   GEODERMA

Soil depth prediction supported by primary terrain attributes: a comparison of methods

(2018) V. Penížek et al.   PLANT SOIL AND ENVIRONMENT

Predicting soil thickness on soil mantled hillslopes

(2018) Nicholas R. Patton et al.   Nature Communications

Mapping the global depth to bedrock for land surface modeling

(2017) Wei Shangguan et al.   Journal of Advances in Modeling Earth Systems

SoilGrids250m: Global gridded soil information based on machine learning

(2017) Tomislav Hengl et al.   PLoS One

Predicting soil depth using simple ground-based measurements of stem shape and taper in the butt swell section of individual Pinus radiata trees

(2016) Jie-Lian Beh et al.   AUSTRALIAN FORESTRY

Unidades de manejo para pinus: desenvolvimento e aplicação de metodologia em áreas de produção no oeste catarinense

(2016) Joao Bosco Vasconcellos Gomes et al.   Scientia Forestalis

A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling

(2016) Jon D. Pelletier et al.   Journal of Advances in Modeling Earth Systems

Unidades de manejo para pinus: desenvolvimento e aplicação de metodologia em áreas de produção no oeste catarinense

(2016) Joao Bosco Vasconcellos Gomes et al.   Scientia Forestalis

Darcy's law predicts widespread forest mortality under climate warming

(2015) Nathan G. McDowell et al.   Nature Climate Change

Qualidade do solo e produtividade de Pinus taeda no planalto catarinense

(2015) Cedinara Arruda Santana Morales et al.   CIENCIA FLORESTAL

Building Predictive Models inRUsing thecaretPackage

(2015) Max Kuhn   Journal of Statistical Software

Soil depth affects simulated carbon and water in the MC2 dynamic global vegetation model

(2014) Wendy Peterman et al.   ECOLOGICAL MODELLING

Relationship between soil depth and terrain attributes in karst region in Southwest China

(2014) Qiyong Yang et al.   JOURNAL OF SOILS AND SEDIMENTS

Köppen's climate classification map for Brazil

(2014) Clayton Alcarde Alvares et al.   METEOROLOGISCHE ZEITSCHRIFT

Predicting regolith thickness in the complex weathering setting of the central Mt Lofty Ranges, South Australia

(2013) J. Wilford et al.   GEODERMA

Relationships between soil depth and terrain attributes in a semi arid hilly region in western Iran

(2013) Abdolmohammad Mehnatkesh et al.   Journal of Mountain Science

Sampling for validation of digital soil maps

(2011) D.J. Brus et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Digital Soil Mapping and Modeling at Continental Scales: Finding Solutions for Global Issues

(2011) S. Grunwald et al.   SOIL SCIENCE SOCIETY OF AMERICA JOURNAL

Hydrologic controls on equilibrium soil depths

(2011) L. Nicótina et al.   WATER RESOURCES RESEARCH

An empirical geomorphology-based approach to the spatial prediction of soil thickness at catchment scale

(2010) Filippo Catani et al.   WATER RESOURCES RESEARCH

Water table is a relevant source for water uptake by a Scots pine (Pinus sylvestris L.) stand: Evidences from continuous evapotranspiration and water table monitoring

(2008) Caroline Vincke et al.   AGRICULTURAL AND FOREST METEOROLOGY