TR32-Database: Database of Transregio 32

[529] - Soil moisture estimation under vegetation from PALSAR FBD data by means of polarimetric decomposition techniques

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Koyama, C. N., Fiener, P., Schneider, K., 2011. Soil moisture estimation under vegetation from PALSAR FBD data by means of polarimetric decomposition techniques. In: Lenz-Wiedemann, V., Bareth, G. (Eds.): Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling. Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten, Cologne, Germany, 63 - 70. DOI: 10.5880/TR32DB.KGA92.9.
Identification
Title(s):Main Title: Soil moisture estimation under vegetation from PALSAR FBD data by means of polarimetric decomposition techniques
Description(s):Abstract: The disturbing effects caused by vegetation and surface roughness are major impediments to accurate quantitative retrievals of soil moisture from Synthetic Aperture Radar (SAR). With most of the operational spaceborne systems it is not possible to separate the different scattering contributions of the soil and vegetation components. In this study we use the coherent-on-receive dual-pol standard acquisitions (FBD343) of Phased Array type L-band Synthetic Aperture Radar (PALSAR) aboard the Advanced Land Observing Satellite (ALOS “Daichi”) acquired over an arable land test site in Western Germany. By applying a PolSAR decomposition technique, namely the H/A/Alpha decomposition, we exploit the phase information to increase the amount of observables. The potential to derive information on biomass and surface roughness from the dual-pol data is investigated based on correlation analyses between PALSAR observables and in-situ measurements. High sensitivities towards surface roughness and crop biomass could be ascertained. Using these findings, we estimate surface roughness ks and sugar beet total wet weight with RMS errors of 0.11 and 2.66 kg/m², respectively. The good quality of the estimates allows correcting the backscattering coefficients for the surface roughness and vegetation effects. The accuracy of soil moisture retrievals could be increased from 4.5 to 3.6 Vol.-% using the roughness correction for bare soil and from > 10.0 to 3.6 Vol.-% using the biomass correction for sugar beet. The results give a promising outlook in terms of the possibility to develop an operational soil moisture retrieval model for PALSAR data collected in the Fine Beam Dual Polarization (FBD) mode.
Identifier(s):DOI: 10.5880/TR32DB.KGA92.9
Citation Advice:Koyama, C. et al., 2011. Soil moisture estimation under vegetation from PALSAR FBD data by means of polarimetric decomposition techniques. In: Lenz-Wiedemann, V., Bareth, G. (Eds.), Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling. Geographisches Institut der Universität zu Köln (Kölner Geographische Arbeiten, 92), Cologne, Germany, 63-70. doi: 10.5880/TR32DB.KGA92.9
Responsible Party
Creator(s):Author: Christian N. Koyama
Author: Peter Fiener
Author: Karl Schneider
Publisher:Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten
Topic
TR32 Topic:Other
Subject(s):CRC/TR32 Keywords: ALOS, PALSAR, Polarimetry, Soil Moisture, Vegetation, Surface Roughness
File Details
File Name:Koyama_et_al_2011_KGA92.pdf
Data Type:Text
Size(s):8 Pages
File Size:1686 kB (1.646 MB)
Date(s):Created: 2010-11-18
Issued: 2010-10-05
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:Free
Licence:Creative Commons Attribution 4.0 International (CC BY 4.0)
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:None
Measurement Location:--None--
Specific Informations - Publication
Status:Published
Review:NoPeerReview
Year:2011
Type:Book Section
Book Title:Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling
Book Editor:Lenz-Wiedemann, V., Bareth, G.
SeriesTitle:Kölner Geographische Arbeiten
City:Cologne, Germany
Volume:92
Number Of Pages:8
Page Range:63 - 70
Metadata Details
Metadata Creator:Christian N. Koyama
Metadata Created:2013-08-05
Metadata Last Updated:2013-08-05
Subproject:C3
Funding Phase:2
Metadata Language:English
Metadata Version:V31
Dataset Metrics
Page Visits:310
Metadata Downloads:0
Dataset Downloads:12
Dataset Activity
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