TR32-Database: Database of Transregio 32

[742] - A novel approach to estimate soil moisture under vegetation using partial polarimetric ALOS PALSAR data

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Features
Citation
Koyama, C. N., Schneider, K., 2010. A novel approach to estimate soil moisture under vegetation using partial polarimetric ALOS PALSAR data. In: Kajiwara, K., Muramatsu, K., Soyama, N., Endo, T., Ono, A., Akatsuka S. (Eds.): Networking the World with Remote Sensing. Proc. of ISPRS Technical Commission VIII Symposium, August 09 - 12, 2010, Kyoto, Japan, 421 - 426.
Identification
Title(s):Main Title: A novel approach to estimate soil moisture under vegetation using partial polarimetric ALOS PALSAR data
Description(s):Abstract: A major impediment to accurate quantitative retrievals of soil moisture from SAR is the disturbing effect caused by vegetation and surface roughness. With most operational space borne systems it is not possible to separate the different scattering contributions of the soil and vegetation components. In this paper we use the coherent-on-receive dual-polarized standard acquisitions (FBD343) of 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 effects. In a first test the accuracy of soil moisture retrievals on bare soil could be increased from 4.5 to 3.6 Vol.-% using the roughness correction. Our findings give a promising outlook in terms of the possibility to develop an operational soil moisture retrieval model for PALSAR data collected in the FBD mode.
Responsible Party
Creator(s):Author: Christian N. Koyama
Author: Karl Schneider
Publisher:-
Topic
TR32 Topic:Remote Sensing
Subject(s):CRC/TR32 Keywords: PALSAR, ALOS, Soil Moisture
File Details
File Name:2010_Koyama_ISPRS2010.pdf
Data Type:Text
Size(s):6 Pages
File Size:484 kB (0.473 MB)
Date(s):Issued: 2010-08-09
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Geographic
North:50.8730035
East:6.4580805
South:50.8621697
West:6.4409143
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2010
Type:Event Paper
Proceedings Title:Networking the World with Remote Sensing
Proceedings Editor:Kajiwara, K., Muramatsu, K., Soyama, N., Endo, T., Ono, A., Akatsuka S.
Number Of Pages:6
Page Range:421 - 426
Event Name:ISPRS Technical Commission VIII Symposium
Event Type:Conference
Event Location:Kyoto, Japan
Event Period:9th of August, 2010 - 12th of August, 2010
Metadata Details
Metadata Creator:Christian N. Koyama
Metadata Created:2013-12-03
Metadata Last Updated:2013-12-03
Subproject:C3
Funding Phase:1
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:187
Metadata Downloads:0
Dataset Downloads:3
Dataset Activity
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