Digital Soil Texture Mapping and Spatial Transferability of Machine Learning Models Using Sentinel-1, Sentinel-2, and Terrain-Derived Covariates

dc.contributor.author	Taghizadeh-Mehrjardi, Ruhollah
dc.date.accessioned	2023-05-22T09:18:58Z
dc.date.available	2023-05-22T09:18:58Z
dc.date.issued	2022
dc.identifier.issn	2072-4292
dc.identifier.uri	http://hdl.handle.net/10900/141286
dc.language.iso	en	de_DE
dc.publisher	Mdpi	de_DE
dc.relation.uri	http://dx.doi.org/10.3390/rs14235909	de_DE
dc.subject.ddc	550	de_DE
dc.subject.ddc	570	de_DE
dc.subject.ddc	600	de_DE
dc.subject.ddc	610	de_DE
dc.title	Digital Soil Texture Mapping and Spatial Transferability of Machine Learning Models Using Sentinel-1, Sentinel-2, and Terrain-Derived Covariates	de_DE
dc.type	Article	de_DE
utue.quellen.id	20230202000000_00275
utue.personen.roh	Mirzaeitalarposhti, Reza
utue.personen.roh	Shafizadeh-Moghadam, Hossein
utue.personen.roh	Taghizadeh-Mehrjardi, Ruhollah
utue.personen.roh	Demyan, Michael Scott
dcterms.isPartOf.ZSTitelID	Remote Sensing	de_DE
dcterms.isPartOf.ZS-Issue	23	de_DE
dcterms.isPartOf.ZS-Volume	14	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät	de_DE