Chapter 15
Development of a New Wetness Index Based
on RADARSAT-1 ScanSAR Data
Quazi K. Hassan and Charles P.-A. Bourque
Abstract A new wetness index (WI) was developed based on the temporal patterns
in radar brightness (β
0 ) in a timeseries of RADARSAT-1 ScanSAR images collected over the July–September period of 2005. The WI proposed here provided an
indirect measure of soil water content (SWC), as β
0 was documented to vary with
land-surface water content. Hydrological factors affecting SWC, such as soil
texture, topography, evapotranspiration, etc., were not considered in the current
determination of WI. WI-values generated with the proposed method were subsequently compared against field measurements of SWC collected from three separate
areas, including densely- and sparsely-forested and non-forested areas (i.e., bare
fields), all located in southcentral New Brunswick (NB), Canada. The comparison
revealed adequate agreement between WI and SWC for all three areas, including
dense forests, yielding coefficients of determination (r
2
’s) of 74–99 %. Reasonable
agreement for dense forests (r
2
¼ 74 %) indicated the potential of the method in
determining SWC under heavily-vegetated conditions. This correlation would arise
because of the equilibrium established between foliage water content (picked up by
the radar signal) and SWC under normal, non-stressed conditions. A second
evaluation of the method was conducted by comparing WI-values with spatial
calculations of SWC obtained with the Soil Water Assessment Tool (SWAT) for
bare-field conditions common to the potato-growing area of northwestern
NB. Again, suitable agreement was obtained, yielding r
2 -values ranging from
65 % to 81 %. However, further research is needed to evaluate the usefulness of
the method for other forested and non-forested regions of the world. In principle,
because the method relies mostly on β
0 , it is highly likely the method can be used to
assess SWC in many different types of natural environments.
Q.K. Hassan (*)
Department of Geomatics Engineering, Schulich School of Engineering, University
of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
e-mail: qhassan@ucalgary.ca
C.P.-A. Bourque
Faculty of Forestry and Environmental Management, University of New Brunswick,
28 Dineen Drive, PO Box 4400, Fredericton, NB E3B 5A3, Canada
e-mail: cbourque@unb.ca
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_15
301
Development of a New Wetness Index Based
on RADARSAT-1 ScanSAR Data
Quazi K. Hassan and Charles P.-A. Bourque
Abstract A new wetness index (WI) was developed based on the temporal patterns
in radar brightness (β
0 ) in a timeseries of RADARSAT-1 ScanSAR images collected over the July–September period of 2005. The WI proposed here provided an
indirect measure of soil water content (SWC), as β
0 was documented to vary with
land-surface water content. Hydrological factors affecting SWC, such as soil
texture, topography, evapotranspiration, etc., were not considered in the current
determination of WI. WI-values generated with the proposed method were subsequently compared against field measurements of SWC collected from three separate
areas, including densely- and sparsely-forested and non-forested areas (i.e., bare
fields), all located in southcentral New Brunswick (NB), Canada. The comparison
revealed adequate agreement between WI and SWC for all three areas, including
dense forests, yielding coefficients of determination (r
2
’s) of 74–99 %. Reasonable
agreement for dense forests (r
2
¼ 74 %) indicated the potential of the method in
determining SWC under heavily-vegetated conditions. This correlation would arise
because of the equilibrium established between foliage water content (picked up by
the radar signal) and SWC under normal, non-stressed conditions. A second
evaluation of the method was conducted by comparing WI-values with spatial
calculations of SWC obtained with the Soil Water Assessment Tool (SWAT) for
bare-field conditions common to the potato-growing area of northwestern
NB. Again, suitable agreement was obtained, yielding r
2 -values ranging from
65 % to 81 %. However, further research is needed to evaluate the usefulness of
the method for other forested and non-forested regions of the world. In principle,
because the method relies mostly on β
0 , it is highly likely the method can be used to
assess SWC in many different types of natural environments.
Q.K. Hassan (*)
Department of Geomatics Engineering, Schulich School of Engineering, University
of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
e-mail: qhassan@ucalgary.ca
C.P.-A. Bourque
Faculty of Forestry and Environmental Management, University of New Brunswick,
28 Dineen Drive, PO Box 4400, Fredericton, NB E3B 5A3, Canada
e-mail: cbourque@unb.ca
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_15
301