3D mapping of soil organic carbon content and soil moisture with multiple geophysical sensors and machine learning

dc.contributor.author	Rentschler, Tobias
dc.contributor.author	Ahner, Mario
dc.contributor.author	Behrens, Thorsten
dc.contributor.author	Gries, Philipp
dc.contributor.author	Scholten, Thomas
dc.contributor.author	Teuber, Sandra
dc.contributor.author	Schmidt, Karsten
dc.date.accessioned	2022-04-22T08:05:40Z
dc.date.available	2022-04-22T08:05:40Z
dc.date.issued	2020
dc.identifier.issn	1539-1663
dc.identifier.uri	http://hdl.handle.net/10900/126312
dc.language.iso	en	en
dc.publisher	Wiley	de_DE
dc.relation.uri	http://dx.doi.org/10.1002/vzj2.20062
dc.subject.ddc	570	de_DE
dc.subject.ddc	550	de_DE
dc.title	3D mapping of soil organic carbon content and soil moisture with multiple geophysical sensors and machine learning	de_DE
dc.type	Article	de_DE
utue.quellen.id	20220224105258_00239
utue.personen.roh	Rentschler, Tobias
utue.personen.roh	Werban, Ulrike
utue.personen.roh	Ahner, Mario
utue.personen.roh	Behrens, Thorsten
utue.personen.roh	Gries, Philipp
utue.personen.roh	Scholten, Thomas
utue.personen.roh	Teuber, Sandra
utue.personen.roh	Schmidt, Karsten
dcterms.isPartOf.ZSTitelID	Vadose Zone Journal	de_DE
dcterms.isPartOf.ZS-Issue	1	de_DE
dcterms.isPartOf.ZS-Volume	19	de_DE
utue.fakultaet	07 Mathematisch-Naturwissenschaftliche Fakultät
utue.fakultaet	Sonstige