Spatial soil nutrients prediction using three supervised learning methods for assessment of land potentials in complex terrain

Catena

Volumn 154, Issue , 2017, Pages 73-84

  Jeong, Gwanyong ^a   Oeverdieck, Hannes ^a   Park, Soo Jin ^b   Huwe, Bernd ^a   Ließ, Mareike ^a  

^a UNIVERSITY OF BAYREUTH   (Germany)

^b Seoul National University   (South Korea)

Author keywords

Digital soil mapping; Land potential assessment; Mountain soil; Soil nutrients

Indexed keywords

COMPLEX TERRAIN; DIGITAL MAPPING; NUTRIENT AVAILABILITY; PHOSPHORUS; SOIL ANALYSIS; SOIL NITROGEN; SOIL NUTRIENT; SUPERVISED LEARNING; TOPSOIL; VEGETATION INDEX;

KANGWON; LAKE SOYANG; SOUTH KOREA;

EID: 85014316135     PISSN: 03418162     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.catena.2017.02.006     Document Type: Article

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