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Using Machine Learning to derive Soil Information from Soil Reflectance Composites (SCMaP)

Donike, Simon (2020) Using Machine Learning to derive Soil Information from Soil Reflectance Composites (SCMaP). Bachelor's, Universität zu Köln.

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Item URL in elib:https://elib.dlr.de/134317/
Document Type:Thesis (Bachelor's)
Title:Using Machine Learning to derive Soil Information from Soil Reflectance Composites (SCMaP)
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Donike, SimonUNSPECIFIEDUNSPECIFIED
Date:2020
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:63
Status:Published
Keywords:Machine Learning, Landsat, remote sensing of soils, timeseries, soil
Institution:Universität zu Köln
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Zepp, Simone
Deposited On:21 Jul 2020 11:02
Last Modified:21 Jul 2020 11:02

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