[1783] - Soil moisture index from ERS-SAR and its application to the analysis of spatial patterns in agricultural areas

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Citation
Esch, S., 2018. Soil moisture index from ERS-SAR and its application to the analysis of spatial patterns in agricultural areas. Journal of Applied Remote Sensing, 12 (2), 1 - 23. DOI: 10.1117/1.JRS.12.022206.
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Identification
Title(s):Main Title: Soil moisture index from ERS-SAR and its application to the analysis of spatial patterns in agricultural areas
Description(s):Abstract: Soil moisture is an important factor influencing hydrological and meteorological exchange processes at the land surface. Synthetic Aperture Radar (SAR) backscatter is strongly affected by the volumetric soil moisture content, thus providing the potential to derive spatially distributed soil moisture information. Archives of historic SAR data exist which use is limited by the lack of corresponding ground truth measurements. This study analyses the potential of using a soil moisture index (SMI) with high spatial resolution to assess the soil moisture status in the absence of ground truth data. The index method is applied to agricultural areas in the catchment of the river Rur in Germany. The SMI was evaluated using antecedent precipitation and the wetting and drying behaviour. The spatial patterns of the SMI were analysed using semivariograms. This study confirms the applicability of a high resolution soil moisture index for monitoring near surface soil moisture changes, to analyse soil moisture patterns and indicates the possibility to complement antecedent precipitation as an input to hydrological models.
Identifier(s):DOI: 10.1117/1.JRS.12.022206
Citation Advice:Esch, S., Korres, W., Reichenau, T.G., Schneider, K. (2018): Soil moisture index from ERS-SAR and its application to the analysis of spatial patterns in agricultural areas. Journal of Applied Remote Sensing (JARS). [accepted for publication]
Responsible Party
Creator(s):Author: Sabrina Esch
Contributor(s):Related Person: Wolfgang Korres
Related Person: Tim G. Reichenau
Related Person: Karl Schneider
Publisher:SPIE - The international society for optics and photonics
Topic
TR32 Topic:Remote Sensing
Related Sub-project(s):C3
Subject(s):CRC/TR32 Keywords: Soil Moisture, SAR
File Details
File Name:SMI_Esch_2017_TR32_db.pdf
Data Type:Text
File Size:2055 kB (2.007 MB)
Date(s):Date Accepted: 2018-03-15
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:In Process
Constraints
Download Permission:OnlyTR32
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
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2018
Type:Article
Article Type:Journal
Source:Journal of Applied Remote Sensing
Issue:2
Volume:12
Number Of Pages:23
Page Range:1 - 23
Metadata Details
Metadata Creator:Sabrina Esch
Metadata Created:2018-03-20
Metadata Last Updated:2018-03-20
Subproject:C3
Funding Phase:3
Metadata Language:English
Metadata Version:V42
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