Paper Info
Title
Peatland Subsurface Water Flow Monitoring Using Polarimetric L-Band Palsar
Abstract
The potential of L-band PALSAR for monitoring water flow beneath the peat surface is demonstrated on a bog near Lac Saint Pierre (Canada). Two polarimetric ALOS acquisitions collected at spring and fall under different water conditions are used. The Touzi decomposition [1], which was shown to be very promising for peatland characterization using the C-band Convair 580 SAR [2], is applied. Like in [2], the information provided by the multi-polarization (HH, HV, and VV), the scattering type magnitude (the Cloude alpha or the Touzi alpha(s)), the single scattering eigenvalues and the entropy, cannot detect the presence of water underneath the peat surface. The Touzi scattering phase is shown to be the only target scattering decomposition parameter that can detect water flow variations beneath the peat surface. The fall acquisition that took place after two days rain permits demonstrating that the wave can penetrate deep into the acrotelm layer to detect the rain water that has sinked rapidly into the peat layer of high hydraulic conductivity. The spring acquisition at dry conditions permits better discrimination of poor fen from bog. The wave, which cannot detect deep water flow in the bog sublayer of low hydraulic conductivity (the catotelm), is more sensitive to the shallower fen subsurface water and this makes possible the separation of poor fen from shrub bog. The requirement for polarimetric PALSAR acquisition during summer is brought out for more effective exploitation of PALSAR unique long wavelength penetration capabilities in monitoring arctic peatland transformations related to climate change stress.
Year
DOI
Venue
2010
10.1109/IGARSS.2010.5653607
2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Keywords
Field
DocType
l band,hydraulic conductivity,snow,conductivity,climate change,bogs,synthetic aperture radar,scattering,hydrology
Peat,Water flow,Hydraulic conductivity,Computer science,Acrotelm,Subsurface flow,Remote sensing,Bog,Poor fen,Snow
Conference
ISSN
Citations 
PageRank 
2153-6996
1
0.42
References 
Authors
0
2
Name
Order
Citations
PageRank
Ridha Touzi121425.43
G. Gosselin210.42