Grant Gunn

UW-Scat: A Ground-Based Dual-Frequency Scatterometer for Observation of Snow Properties

The University of Waterloo scatterometer, which is a system developed for observation of snow and ice properties, is described. The system is composed of two frequency-modulated continuous-wave radars operating at center frequencies of 17.2 and 9.6 GHz. A field-deployable platform allows a rapid setup and observation at remote sites under harsh environmental conditions. A two-axis positioning system moves the radar beam across a user-programmable range of azimuth (±180°) and elevation angles (15°-105°). Typical azimuth scans of 60° angular width generate between 21 and 586 independent samples, depending on the wavelength and the elevation angle. The backscatter response of terrestrial snow in the Canadian Subarctic is demonstrated with two experiments conducted in Churchill, MB, Canada, between 2009 and 2011.

Microwave Backscatter From Arctic Lake Ice and Polarimetric Implications

Polarimetric synthetic aperture radar satellite and ground-based Ku- and X-band scatterometer measurements are used to explore the scattering mechanism for ice in shallow Arctic lakes, wherein strong radiometric responses are seen for floating ice, and low returns are evident where the ice has grounded. Scatterometer measurements confirm that high backscatter is from the ice/water interface, whereas polarimetric decomposition suggests that the dominant scattering mechanism from that interface is single bounce. Using Fresnel equations, a simple model for surface bounce from the ice/water interface is proposed, and its predictions are supported by experimental parameters such as co-pol phase difference, co-pol ratio, and the results of rigorous numerical modeling. Despite early research suggesting double-bounce scattering from columnar air bubbles and the ice/water interface as the dominant scattering mechanism in shallow lakes, this paper strongly supports a single-bounce model.

Observation and Modeling of X- and Ku-Band Backscatter of Snow-Covered Freshwater Lake Ice

This study is the first assessment of winter season backscatter (σ°) evolution for snow-covered lake ice observed by X(9.6 Gnz) and Ku-band (17.2 Gnz) ground-based scatterometers (UW-SCAT), collected during the Canadian Snow and Ice Experiment in 2010-2011. The σ° evolution of three ice cover scenarios is observed and simulated using a bubbled ice σ° model. The range resolution of UW-SCAT provides separation of interaction at the snow-ice interface (P1), and within the ice volume and ice-water interface (P2). Ice cores extracted at the end of the observation period indicate a P2 σ° increase of approximately 10-12 decibels (dB) (nn & VV) at Xand Ku-band coincident to tubular bubble development. Similarly, complexity of the ice surface (gray ice) results in increased P1 σ° (~7dB). P1 observations indicate that Ku-band is sensitive to snowpack overlying lake ice, with σ° exhibiting a 5 (6) dB drop for VV (nn) when 0.235 m snow is removed. X-band is insensitive to changes in overlying snowpack. A bubbled ice σ° model is presented using dense medium-radiative transfer theory under the quasicrystalline approximation (DMRT-QCA), which treats bubbles as spherical inclusions within an ice volume. Model runs demonstrate the capability of DMRT to produce observed σ° magnitude using snow and ice observations as input. This study improves the understanding of microwave interaction with bubbled ice near the surface or within the volume. Results from this study indicate that further model development involves bubble shape modification within the ice from spherical to tubular.

Observing Scattering Mechanisms of Bubbled Freshwater Lake Ice Using Polarimetric RADARSAT-2 (C-Band) and UW-Scat (X- and Ku-Bands)

A winter time series of ground-based (X- and Ku-bands) scatterometer and spaceborne synthetic aperture radar (SAR) (C-band) fully polarimetric observations coincident with in situ snow and ice measurements are used to identify the dominant scattering mechanism in bubbled freshwater lake ice in the Hudson Bay Lowlands near Churchill, Manitoba. Scatterometer observations identify two physical sources of backscatter from the ice cover: the snow–ice and ice–water interfaces. Backscatter time series at all frequencies show increases from the ice–water interface prior to the inclusion of tubular bubbles in the ice column based on in situ observations, indicating scattering mechanisms independent of double-bounce scatter. The co-polarized phase difference of interactions at the ice–water interface from both scatterometer and SAR observations is centered at 0° during the time series, also indicating a scattering regime other than double bounce. A Yamaguchi three-component decomposition of the RADARSAT-2 C-band time series is presented, which suggests the dominant scattering mechanism to be single-bounce off the ice–water interface with appreciable surface roughness or preferentially oriented facets, regardless of the presence, absence, or density of tubular bubble inclusions. This paper builds on newly established evidence of single-bounce scattering mechanism for freshwater lake ice and is the first to present a winter time series of ground-based and spaceborne fully polarimetric active microwave observations with polarimetric decompositions for bubbled freshwater lake ice.

A model for downscaling SMOS soil moisture using Sentinel-1 SAR data

Abstract A model for downscaling SMOS (Soil Moisture Ocean Salinity) soil moisture products is developed by using multi-temporal dual-polarized (HH+HV) C-band SAR data. In this model, the effect of vegetation on soil moisture retrieval from SAR data is minimized by using the water-cloud model (WCM), in which vegetation contribution is quantified using the backscatter coefficient of HV polarization. The wavelet transform is used to fuse high resolution Sentinel-1A SAR backscatter with low resolution SMOS soil moisture, where the difference in spatial heterogeneity between scales is also accounted for. The influence of soil surface roughness is eliminated by using multi-temporal data. The multi-temporal SMOS soil moisture and dual-pol Sentinel-1/SAR data are the only inputs of this downscaling model. The model is tested in southern Ontario, Canada to downscale 40 km resolution SMOS soil moisture to 1.25 km and 2.5 km resolutions. The downscaled results show good agreements with the in-situ soil moisture collected in May and July of 2016 with an unbiased root-mean-square-error (RMSE) of 0.045 m3/m3 and 0.047 m3/m3 and a coefficient of determination (R2) of 0.54 and 0.70 at 1.25 km and 2.5 km resolutions respectively. The results suggest that the model can be applied for C-band at regional scales to provide continuous soil moisture mapping at higher resolutions. The high revisit frequency of the up-coming Radarsat Constellation Mission (RCM) combined with its large areal coverage characteristics are ideal for the generation of downscaled products.

Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine

Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has been challenging due to persistent cloud and snow cover issues and the spectrally similar land cover types. Google Earth Engine (GEE) represents a powerful tool to efficiently investigate these changes using a large repository of available optical imagery. This work examines land cover change in the Lower Yenisei River region of arctic central Siberia and exemplifies the application of GEE using the random forest classification algorithm for Landsat dense stacks spanning the 32-year period from 1985 to 2017, referencing 1641 images in total. The semiautomated methodology presented here classifies the study area on a per-pixel basis utilizing the complete Landsat record available for the region by only drawing from minimally cloudand snow-affected pixels. Climatic changes observed within the study area’s natural environments show a statistically significant steady greening (~21,000 km2 transition from tundra to taiga) and a slight decrease (~700 km2) in the abundance of large lakes, indicative of substantial permafrost degradation. The results of this work provide an effective semiautomated classification strategy for remote sensing in permafrost regions and map products that can be applied to future regional environmental modeling of the Lower Yenisei River region.

Investigating the influence of variable freshwater ice types on passive and active microwave observations

Dual-polarized airborne passive microwave (PM) brightness temperatures (Tb) at 6.9 GHz H/V, 19 GHz H/V and 37 GHz H/V and spaceborne active microwave (AM) X-band (9.65 GHz VV, VH) backscatter (σ0) are observed coincident to in situ snow and lake-ice measurements collected over two lakes near Inuvik, Canada. Lake-ice thickness is found to be positively correlated with 19 GHz V emission (R = 0.67) and negatively with 19 GHz H emission (R = −0.79), indicating surface ice conditions influence microwave interaction. Lake ice types are delineated from TerraSAR-X synthetic aperture radar (SAR) images using the iterative region growing with semantics (IRGS) segmentation algorithm implemented in the MAGIC (MAp Guided Ice Classification) system. The spatial extent of derived ice type classes correspond well to in situ observations. The overall magnitude of emission at 19 GHz H and X-band VH σ0 increase with the scattering potential of associated ice types (grey/rafted ice). Transects of 6.9 GHz PM and 19 GHz PM exhibit positive relationships with VH σ0 over freshwater lake ice, with the greatest R coefficients at H-pol (R = 0.64, 0.46). Conversely, 6.9 GHz Tb and 19 GHz Tb exhibit negative R coefficients in regions of brackish water due to tubular bubble and brine inclusions in the ice. This study identifies congruency between PM and AM scattering mechanisms over lake ice for the purpose of identifying the influence of ice types on overall microwave interaction within the lake-ice system.

Ground-based scatterometer observations of snow-covered freshwater lake ice using UW-SCAT (9.6/17.2 GHz)

Winter season backscatter (σ°) evolution of snow covered lake ice was observed by ground-based University of Waterloo X-(9.6 GHz) and Ku-band (17.2 GHz) scatterometers (UW-SCAT) during the winter of 2010-11. The UW-SCAT post-processing procedure allowed for the observation of σ° at the surface (snow/ice interface, ice types) and the ice volume. Observations indicated that: (1) σ° associated with the development of tubular bubbles within the ice volume causes double-bounce of the signal and high returns at X- and Ku-bands; (2) ice types at the surface (grey ice) composed of high density spherical micro-bubbles result in σ° increases at both X- and Ku-bands; and (3) the removal of snow overlying ice results in a drop in Ku-band σ° up to 5.5 dB, exhibiting sensitivity to snow water equivalent.