Abstract
For this research, the Random Forest (RF) classifier was used to evaluate the potential of simulated RADARSAT Constellation Mission (RCM) data for mapping landcover within peatlands. Alfred Bog, a large peatland complex in Southern Ontario, was used as a test case. The goal of this research was to prepare for the launch of the upcoming RCM by evaluating three simulated RCM polarizations for mapping landcover within peatlands. We examined (1) if a lower RCM noise equivalent sigma zero (NESZ) affects classification accuracy, (2) which variables are most important for classification, and (3) whether classification accuracy is affected by the use of simulated RCM data in place of the fully polarimetric RADARSAT-2. Results showed that the two RCM NESZs (−25 dB and −19 dB) and three polarizations (compact polarimetry, HH+HV, and VV+VH) that were evaluated were all able to achieve acceptable classification accuracies when combined with optical data and a digital elevation model (DEM). Optical variables were consistently ranked to be the most important for mapping landcover within peatlands, but the inclusion of SAR variables did increase overall accuracy, indicating that a multi-sensor approach is preferred. There was no significant difference between the RF classifications which included RADARSAT-2 and simulated RCM data. Both medium- and high-resolution compact polarimetry and dual polarimetric RCM data appear to be suitable for mapping landcover within peatlands when combined with optical data and a DEM.
Highlights
Peatlands are a unique class of wetlands with many important functions including storing carbon, providing habitat for several wildlife species, mitigating floods and droughts, as well as retaining, purifying, and releasing water [1]
We compared Random Forest (RF) models using simulated RADARSAT Constellation Mission (RCM) data and a noise equivalent sigma zero (NESZ) of −19 dB and −25 dB in combination with Landsat-8 and a digital elevation model (DEM) to determine if the difference in radiometry affects the accuracy of mapping landcover within peatlands
We compared RF models with three simulated RCM polarizations (HH+HV, VV+VH, and compact polarimetry (CP)) in combination with Landsat-8 and a DEM to assess if the difference in polarization improves the ability to classify peatlands
Summary
Peatlands are a unique class of wetlands with many important functions including storing carbon, providing habitat for several wildlife species, mitigating floods and droughts, as well as retaining, purifying, and releasing water [1]. RCM will be comprised of three identical C-band SAR satellites launched simultaneously allowing for daily coverage over Canada with 350 km imaging swaths [34]. This will allow for a much shorter repeat cycle, offering a coherent change detection (CCD) timeframe of 4 days (resulting from the three satellites) [34], temporal datasets, and more flexibility and reliability compared to RADARSAT-1 and RADARSAT-2 [35]. Future research will focus on evaluating CCD with RCM for mapping seasonal changes in wetlands, as RADARSAT-2 has shown promising results [36]
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