Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements

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Title:Main Title: Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements
Description:Abstract: Patterns in crop development and yield are often directly related to lateral and vertical changes in soil texture causing changes in available water and resource supply for plant growth, especially under dry conditions. Relict geomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions of uniformity in precision agriculture, subsurface hydrology, and crop modelling. Hence a better detection of these subsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area index (LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for the first time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensor measuring soil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0-0.25 to 0-1.9 m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomography (ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties at ten arable fields. The moderate to excellent spatial consistency of LAI crop marks that indicate a higher water storage capacity and ECa patterns as well as the increased correlations between large-offset ECa data and the subsoil clay content and soil profile depth, indicates that along paleo river structures the subsoil is mainly responsible for the crop performance in drought periods. Furthermore, observed stagnant water in the subsoil indicates that these paleo-river structures still play an important role in subsurface hydrology. These insights can be implemented in local hydrological as well as crop models
Identifier:10.1016/j.geoderma.2014.11.015 (DOI)
Related Resource:References http://www.tr32db.uni-koeln.de/data.php?dataID=1300 (URL)
Responsible Party
Creators:Sebastian Rudolph (Author), Jan van der Kruk (Author), Christian von Hebel (Author), Muhammad Ali (Author), Michael Herbst (Author), Carsten Montzka (Author), Stefan Pätzold (Author), David Robinson (Author), Harry Vereecken (Author)
Contributor:Jan van der Kruk (Supervisor)
Publisher:Elsevir
Publication Year:2015
Topic
TR32 Topic:Soil
Related Subprojects:B6, B1
Subject:Keyword: Soil Texture
File Details
Filename:Rudolph_et_al_Geoderma.pdf
Data Type:Text - Article
Size:10 Pages
File Size:2.2 MB
Dates:Accepted: 20.11.2014
Available: 06.12.2014
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Free
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[TR32DB] Data policy agreement
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Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Article Type:Journal
Source:Geoderma
Volume:241-242
Number of Pages:10 (262 - 271)
Metadata Details
Metadata Creator:Christian von Hebel
Metadata Created:15.01.2015
Metadata Last Updated:15.01.2015
Subproject:B6
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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