The Arctic and sub-Arctic environments have seen a rapid growth of shrub vegetation at the expense of the Arctic tundra in recent decades. In order to develop better tools to assess and understand this phenomenon, the sensitivity of multi-polarized SAR backscattering at C and X band to shrub density and height is studied under various conditions. RADARSAT-2 and TerraSAR-X images were acquired from November 2011 to March 2012 over the Umiujaq community in northern Quebec (56.55°N, 76.55°W) and compared to in situ measurements of shrub vegetation density and height collected during the summer of 2009. The results show that σ0 is sensitive to changes in shrub coverage up to 20% and is sensitive to changes in shrub height up to around 1 m. The cross-polarized backscattering (σ⁰ HV ) displays the best sensitivity to both shrub height and density, and RADARSAT-2 is more sensitive to shrub height, as TerraSAR-X tends to saturate more rapidly with increasing volume scattering from the shrub branches. These results demonstrate that SAR data could provide essential information, not only on the spatial expansion of shrub vegetation, but also on its vertical growth, especially at early stages of colonization.

Understanding the hydrological dynamics of boreal wetland ecosystems (peatlands) is essential in order to better manage hydropower inter-annual productivity at the La Grande basin (Northern Quebec, QC, Canada). Given the remoteness and the huge dimension of the La Grande basin, it is imperative to develop remote sensing monitoring techniques to retrieve hydrological parameters. The main objective of this study is to find out if multi-date and multi-polarization Radar Satellite 2 (RADARSAT-2) (C-band) image analysis could detect seasonal variations of surface soil moisture conditions of the acrotelm. A change detection approach through the use of multi temporal indexes was chosen based on the assumption that the temporal variability of surface roughness and natural vegetation biomass is generally at a much longer time scale than that of surface soil moisture (Δ-Index is based on a reference image that represents dry soil, in order to maximize the sensitivity of σ° to changes in soil moisture with respect to the same location when soil is wet). The Δ-Index approach was tested with each polarization: σ° for fully polarimetric mode (HH, HV, VV) and the cross-polarization coefficient (HV/HH). Results show that the best regression adjustment with regard to surface soil moisture content in boreal wetlands was obtained with the cross-polarization coefficient. The cross-polarization multi-temporal index enables precise volumetric surface soil moisture estimation and monitoring on boreal wetlands, regardless of the influence of vegetation cover and surface roughness conditions (bias was under 1%, standard deviation and RMSE were under 10% for almost all estimation errors). Surface soil moisture estimation was more precise over permanently flooded areas than seasonally flooded ones (standard deviation is systematically greater for the seasonally flooded areas, at all analyzed scales), although the overall quality of the estimation is still precise. Cross-polarization ratio image analysis appears to be a useful mean to exploit radar data spatially, as we were able to relate changes in wetland eco-hydrological dynamics to variations in the intensity of the ratio.

The La Grande River watershed, located in the James Bay region (54°N, Quebec, Canada), is a major contributor to the production of hydroelectricity in the province. Peatlands cover up to 20% of the terrestrial environment in this region. Their hydrological behavior is not well understood. The present study is part of a multidisciplinary project which is aimed at analyzing the hydrological processes in these minerotrophic peatlands (fens) in order to provide effective monitoring tools to water managers. The objective of this study was to use VHR remote sensing data to understand the seasonal dynamics of the hydrology in fens. A series of 10 multispectral pan-sharpened GeoEye-1 images (with a spatial resolution of 40 cm) were acquired during the snow-free season (May to October) in 2009 and 2010, centered on two study sites in the Laforge sector (54°06'N; 72°30'W). These are two fens instrumented for continuous hydrometeorological monitoring (water level, discharge, precipitation, air temperature). An object-based classification procedure was set up and applied. It consisted of segmenting the imagery into objects using the multiresolution segmentation algorithm (MRIS) to delineate internal structures in the peatlands (aquatic, semi-aquatic, and terrestrial). Then, the objects were labeled using a fuzzy logic based algorithm. The overall classification accuracy of the 10 images was assessed to be 82%. The time series of the peatland mapping demonstrated the existence of important intra-seasonal spatial dynamics in the aquatic and semi-aquatic compartments. It was revealed that the dynamics amplitude depended on the morphological features of the fens. The observed spatial dynamics was also closely related to the evolution of the measured water levels.

As the number of operational wind scatterometers is getting smaller, other sources of spaceborne sensors are now included in global wind mapping. One of the prominent sensors is the Synthetic Aperture Radar (SAR). Besides serving as a generic scatterometer, SAR systems are the only type of radar systems that can provide sub-km resolution sea surface wind data and offers near shore mapping capability. This unique feature is important for assessing the offshore wind resources. As an important source of renewable energy, offshore wind farms are growing rapidly. Furthermore, recent research shows that the cross-polarization radar backscatter does not seem to saturate in high winds, and provides an excellent supplement for scatterometer wind sensing in storm conditions. The saturation issues of co-polarization radar returns have so far made it difficult to resolve wind speeds beyond roughly 20 m/s, or even less for lower incidence angles. The scope of this paper is to show the potential of RADARSAT-2's polarimetric modes for wind speed retrieval. RADARSAT-2 is the first operational fully polarimetric (HH VV HV VH) C-band satellite. Standard Quad-pol images have been collected in the St. Lawrence Gulf and compared against the Mont-Louis buoy and QuikSCAT scatterometer data. Co-polarization wind speeds were computed with CMOD-5 algorithms. A few polarization ratios were tested to determine the most suitable one for RADARSAT-2's HH polarization mode. For Cross-polarization, two different models were compared. Cross-polarization gives excellent results when wind exceeds 5 m/s. In general, SAR wind retrieval is suitable for resolution of 400 m.

Permafrost-affected soils cover about 40–45 % of Canada. The environment in such areas, especially those located within the discontinuous permafrost zone, has been impacted more than any other by recorded climatic changes. A number of changes, such as surface subsidence and the degradation of frost mounds due to permafrost thawing, have already been observed at many locations. We surveyed three frost mounds (lithalsas) in the subarctic, close to Umiujaq in northern Quebec, using high-precision differential global positioning system (d-GPS) technology during field visits in 2009, 2010 and 2011, thus obtaining detailed information on their responses to the freezing and thawing that occur during the course of the annual temperature cycle. Seasonal pulsations were detected in the frost mounds, and these responses were shown to vary with their state of degradation and the land cover. The most degraded lithalsa showed a maximum amplitude of vertical movement (either up or down) between winter (freezing) and summer (thawing) of 0.19 ± 0.09 m over the study period, while for the least degraded lithalsa this figure was far greater (1.24 ± 0.47 m). Records from areas with little or no vegetation showed far less average vertical movement over the study period (0.17 ± 0.03 m) than those with prostrate shrubs (0.56 ± 0.02 m), suggesting an influence from the land cover. A differential interferometric synthetic aperture radar (D-InSAR) analysis was also completed over the lithalsas using selected TerraSAR-X images acquired from April to October 2009 and from March to October 2010, with a repeat cycle of 11 days. Interferograms with baselines shorter than 200 m were computed revealing a generally very low interferometric coherence, restricting the quantification of vertical movements of the lithalsas. Vertical surface movements of the order of a few centimeters were recorded in the vicinity of Umiujaq.

The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflective/emissive bands. Hybrid cloud-masking using both the MOD35 mask and a visibility mask, combined with downscaling of Bands 3–7 to 250 m, are utilized to delineate sea ice extent using a decision tree approach. IceMap250 was tested on scenes from the freeze-up, stable cover, and melt seasons in the Hudson Bay complex, in Northeastern Canada. IceMap250 first product is a daily composite sea ice presence map at 250 m. Validation based on comparisons with photo-interpreted ground-truth show the ability of the algorithm to achieve high classification accuracy, with kappa values systematically over 90%. IceMap250 second product is a weekly clear sky map that provides a synthesis of 7 days of daily composite maps. This map, produced using a majority filter, makes the sea ice presence map even more accurate by filtering out the effects of isolated classification errors. The synthesis maps show spatial consistency through time when compared to passive microwave and national ice services maps.