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Jeong, Gwanyong, Oeverdieck, Hannes, Park, Soo Jin, Huwe, Bernd, Ließ, Mareike (2017) Spatial soil nutrients prediction using three supervised learning methods for assessment of land potentials in complex terrain. CATENA, 154. 73-84 doi:10.1016/j.catena.2017.02.006

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Reference TypeJournal (article/letter/editorial)
TitleSpatial soil nutrients prediction using three supervised learning methods for assessment of land potentials in complex terrain
JournalCATENA
AuthorsJeong, GwanyongAuthor
Oeverdieck, HannesAuthor
Park, Soo JinAuthor
Huwe, BerndAuthor
Ließ, MareikeAuthor
Year2017 (July)Volume154
PublisherElsevier BV
DOIdoi:10.1016/j.catena.2017.02.006Search in ResearchGate
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Mindat Ref. ID16572016Long-form Identifiermindat:1:5:16572016:8
GUID0
Full ReferenceJeong, Gwanyong, Oeverdieck, Hannes, Park, Soo Jin, Huwe, Bernd, Ließ, Mareike (2017) Spatial soil nutrients prediction using three supervised learning methods for assessment of land potentials in complex terrain. CATENA, 154. 73-84 doi:10.1016/j.catena.2017.02.006
Plain TextJeong, Gwanyong, Oeverdieck, Hannes, Park, Soo Jin, Huwe, Bernd, Ließ, Mareike (2017) Spatial soil nutrients prediction using three supervised learning methods for assessment of land potentials in complex terrain. CATENA, 154. 73-84 doi:10.1016/j.catena.2017.02.006
In(2017) CATENA Vol. 154. Elsevier BV

See Also

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Ließ, Mareike, Glaser, Bruno, Huwe, Bernd (2012) Uncertainty in the spatial prediction of soil texture. Geoderma, 170. 70-79 doi:10.1016/j.geoderma.2011.10.010
Ließ, Mareike, Glaser, Bruno, Huwe, Bernd (2012) Making use of the World Reference Base diagnostic horizons for the systematic description of the soil continuum — Application to the tropical mountain soil-landscape of southern Ecuador. CATENA, 97. 20-30 doi:10.1016/j.catena.2012.05.002
Kim, Daehyun, Šamonil, Pavel, Jeong, Gwanyong, Tejnecký, Václav, Drábek, Ondřej, Hruška, Jakub, Park, Soo Jin (2019) Incorporation of spatial autocorrelation improves soil–landform modeling at A and B horizons. CATENA, 183. 104226 doi:10.1016/j.catena.2019.104226
Ließ, Mareike, Glaser, Bruno, Huwe, Bernd (2011) Functional soil-landscape modelling to estimate slope stability in a steep Andean mountain forest region. Geomorphology, 132 (3) 287-299 doi:10.1016/j.geomorph.2011.05.015
Debella-Gilo, Misganu, Etzelmüller, Bernd (2009) Spatial prediction of soil classes using digital terrain analysis and multinomial logistic regression modeling integrated in GIS: Examples from Vestfold County, Norway. CATENA, 77 (1) 8-18 doi:10.1016/j.catena.2008.12.001
Guio Blanco, Carlos M., Brito Gomez, Victor M., Crespo, Patricio, Ließ, Mareike (2018) Spatial prediction of soil water retention in a Páramo landscape: Methodological insight into machine learning using random forest. Geoderma, 316. 100-114 doi:10.1016/j.geoderma.2017.12.002
Tziachris, Panagiotis, Aschonitis, Vassilis, Chatzistathis, Theocharis, Papadopoulou, Maria (2019) Assessment of spatial hybrid methods for predicting soil organic matter using DEM derivatives and soil parameters. CATENA, 174. 206-216 doi:10.1016/j.catena.2018.11.010
Haruna, Samuel I. (2021) Spatial and fractal characterization of selected soil nutrients along a catena. CATENA, 204. 105443 doi:10.1016/j.catena.2021.105443
Liu, Congtan, Fan, Haoming, Wang, Yixuan (2024) Gully erosion susceptibility assessment using three machine learning models in the black soil region of Northeast China. CATENA, 245. 108275 doi:10.1016/j.catena.2024.108275
Prăvălie, Remus, Săvulescu, Ionuţ, Patriche, Cristian, Dumitraşcu, Monica, Bandoc, Georgeta (2017) Spatial assessment of land degradation sensitive areas in southwestern Romania using modified MEDALUS method. CATENA, 153. 114-130 doi:10.1016/j.catena.2017.02.011
Chen, Xi, Chen, Wei (2021) GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods. CATENA, 196. 104833 doi:10.1016/j.catena.2020.104833
 
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