Mapping soil properties of Africa at 250 m resolution: Random forests significantly improve current predictions

PLoS ONE

Volumn 10, Issue 6, 2015, Pages

  Hengl, Tomislav ^a   Heuvelink, Gerard B M ^a   Kempen, Bas ^a   Leenaars, Johan G B ^a   Walsh, Markus G ^b,c   Shepherd, Keith D ^d   Sila, Andrew ^d   MacMillan, Robert A ^e   De Jesus, Jorge Mendes ^a   Tamene, Lulseged ^f   Tondoh, Jérôme E ^d  

^a ISRIC WORLD SOIL INFORMATION   (Netherlands)

^b Earth Institute Columbia University ^*  (United States)

^c Selian Agricultural Research Institute   (Tanzania)

^d WORLD AGROFORESTRY CENTRE ICRAF   (Kenya)

^e LandMapper Environmental Solutions   (Canada)

^f International Center for Tropical Agriculture   (Malawi)

Author keywords

[No Author keywords available]

Indexed keywords

ALUMINUM; CALCIUM; MAGNESIUM; NITROGEN; ORGANIC CARBON; POTASSIUM; SODIUM; SOIL;

ACCURACY; ACIDITY; AFRICA; AGRICULTURAL MANAGEMENT; ALGORITHM; ARTICLE; BULK DENSITY; CATION EXCHANGE; CONCENTRATION (PARAMETERS); DATA BASE; GEOGRAPHIC MAPPING; INFORMATION SERVICE; INTERMETHOD COMPARISON; LINEAR REGRESSION ANALYSIS; PH; PREDICTION; QUALITY CONTROL PROCEDURES; RANDOM FOREST; SAND; SOIL ANALYSIS; SOIL MANAGEMENT; SOIL PROPERTY; TAXONOMY; VALIDATION PROCESS; CHEMISTRY; ENVIRONMENTAL MONITORING; PROCEDURES; SOIL; THEORETICAL MODEL;

AFRICA; ENVIRONMENTAL MONITORING; MODELS, THEORETICAL; SOIL;

EID: 84938613517     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0125814     Document Type: Article

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