|Title||Improvement of clustering methods for modelling abrupt land surface changes in satellite image fusions|
|Author||Zhong, D; Zhou,
|Source||Remote Sensing vol. 11, issue 15, 1759, 2019 p. 1-20, https://doi.org/10.3390/rs11151759 Open Access|
|Alt Series||Natural Resources Canada, Contribution Series 20190629|
|Media||paper; on-line; digital|
|Subjects||geophysics; Science and Technology; remote sensing; satellite imagery; models; modelling; reflectance; floods; Environmental hazards; Methodology; Forest fires|
|Illustrations||flow diagrams; satellite images; sketch maps; bar graphs|
|Program||Canada Centre for Remote Sensing Divsion|
|Released||2019 07 26|
|Abstract||The complementarity of the 'scattered' and 'received' wave polarization signatures is demonstrated for enhanced characterization of peatlands and surrounding upland forest scattering. Polarimetric
L-band ALOS-PALSAR collected in the Athabasca oil sand exploration region, with peatlands and upland forests partially affected by multiple wildfire, are used. It is shown that the scattered wave polarization signature, which represents the
explicit variations of the degree of polarization (DoP) and the total scattered intensity R0 with transmitted polarization, permits enhanced discrimination of treed bogs from upland forests, and improved identification of fire damages in peat-lands
and surrounding forests. The technique introduced in  for scattered wave optimization is used as a convenient method for efficient exploitation of the scattered wave polarization signature. The Touzi decomposition  is adopted for the
optimization of the received wave polarization signature. The unique potential of the scattering type phase generated with the Touzi decomposition is confirmed for enhanced discrimination of poor fens from bogs. These two important pealand classes
cannot be separated with the scattered wave optimization, the conventional multi-polarization (HH-HV-VV) channels, the Freeman and Cloude-Pottier decompositions , . Finally, the Touzi decomposition is combined with the extrema of the scattered
wave main parameters (DoP and R0) for optimum extraction of polarimetric PALSAR information. The comparison with optical Landsat-TM confirms the valuable added information that long penetrating polarimetric L-band PALSAR can provide for enhanced
peatland classification and efficient assessment of peat health in burned peatlands. |
|Summary||(Plain Language Summary, not published)|
This publication focuses on improving the characterization of peatlands and upland forests using polarimetric radar data collected by the ALOS-PALSAR
satellite in the Athabasca oil sands region. This region has peatlands and forests affected by wildfires. The researchers found that by analyzing the polarization signature of the scattered radar waves, they could better distinguish between treed
bogs and upland forests and identify fire damage in these areas.
They used a technique for optimizing the scattered wave polarization signature and the Touzi decomposition method to make the most of the received wave polarization signature. The
combination of these methods allowed for improved classification of different types of peatlands, specifically poor fens and bogs. These distinctions were challenging to make using other polarization channels and decomposition methods.
comparing the radar data with optical data from the Landsat satellite, the study demonstrated the added value of using polarimetric radar for classifying peatlands and assessing their health after wildfires.
The scientific impact of this research
lies in its contribution to better understanding and monitoring peatlands, which are vital for carbon storage and play a significant role in climate change mitigation. Improved classification and assessment methods are essential for managing and
protecting these ecosystems effectively.