Use of multitemporal ERS-2 SAR images for identification of burned scars in south-east Asian tropical rainforest

Evaluation of an area severely affected by fires in 1998 using a multitemporal series of ERS-2 Synthetic Aperture Radar (SAR) images showed that fire induced changes of the vegetation cover strongly affected C-band radar backscatter. We investigated the changes in radar backscatter over a period of ten months in areas of interest that represented different land-cover types at a study site in East Kalimantan, Indonesia. The impact of fire was found to cause a strong decrease in backscatter (2-5 dB) for all land-cover classes while areas not affected by fire showed only slight variations in backscatter (maximum 0.5 dB). Ground and aerial evidence suggests that the marked decrease in backscatter can be attributed to the removal of the vegetation cover and subsequently higher contribution of backscatter from dry soil. After the onset of rain the radar backscatter increased to 5.5 dB in areas severely affected by fire while in unburned forests it returned to values similar to those before the drought. Burned scars could be identified visually in multitemporal principal component analysis-enhanced ERS SAR colour composites.     

Sensitivity of SAR data to post-fire forest regrowth in Mediterranean and boreal forests

Disturbed forests may need decades to reach a mature stage and optically-based vegetation indices are usually poorly suited for monitoring purposes due to the rapid saturation of the signal with increasing canopy cover. Spaceborne synthetic aperture radar (SAR) data provide an alternate monitoring approach since the backscattered microwave energy is sensitive to the vegetation structure. Images from two regions in Spain and Alaska were used to analyze SAR metrics (cross-polarized backscatter and co-polarized interferometric coherence) from regrowing forests previously affected by fire. TerraSAR-X X-band backscatter showed the lowest sensitivity to forest regrowth, with the average backscatter increasing by 1-2 dB between the most recent fire scar and the unburned forest. Increased sensitivity (around 3-4 dB) was observed for C-band Envisat Advanced Synthetic Aperture (ASAR) backscatter. The Advanced Land Observing Satellite (ALOS) Phased Array-type L-band Synthetic Aperture Radar (PALSAR) L-band backscatter presented the highest dynamic range from unburned to recently burned forests (approximately 8 dB). The interferometric coherence showed low sensitivity to forest regrowth at all SAR frequencies. For Mediterranean forests, five phases of forest regrowth were discerned whereas for boreal forest, up to four different regrowth phases could be discerned with L-band SAR data. In comparison, the Normalized Difference Vegetation Index (NDVI) provided reliable differentiation only for the most recent development stages. The results obtained were consistent in both environments.     

Geocoding of fast-delivery ERS-l SAR image mode product using DEM data

An algorithm for geocoding and radiometric correction of ERS–1 Synthetic Aperture Radar images by using Digital Elevation Model data is described a.nd applied to images over a mountainous area in Norway. Several images covering the same area are calibrated and geocoded into a UTM map projection and the results are evaluated against map and i/1 situ measurements. The map to SAR geometric precision is given by a rms value of 54m in the casting direction and 45m in the northing direction. The SAR to SAR geometric precision is given by a rms value of 43m in the casting direction and 44m in the northing direction. Estimates of the radar backscatter coefficient are extracted from the geocoded SAR backscatter images. Obtained values for wet snow–13dB and for dry snow–7dB which agrees favourably with earlier radar measurements and theory.     

Analysis of ERS-1 Synthetic Aperture Radar data from Nordaustlandet,Svalbard

Study of the Earth's terrestrial ice masses (glaciers, ice caps and ice sheets), especially the seasonal variation of different surface conditions such as dry snow, wet snow and bare ice, is of particular importance in relation to possible climatic change. Synoptic monitoring techniques using visible and near-infrared satellite imagery are severely limited by the prevalence of cloud cover in the polar regions, and winter observations are impossible as a result of the absence of solar radiation. Consequently, considerable attention is now being focused on the use of imaging radar in the study of large ice masses. In this paper, we present and interpret a time-series of C-band synthetic aperture radar images acquired using the ERS-1 satellite from the Austfonna ice cap in eastern Svalbard. Winter imagery shows little variability, most of the ice cap having a uniform and high (approximately – 3dB) backscatter attributed to ice lenses or to a large effective grain size. Summer imagery shows considerable topographically-related detail, and backscatter values typically 5 to l0 dB less than in winter, which can be explained on the basis of surface scattering from wet snow. However, the marginal areas of the ice cap show a clearly defined zone of high ( –5dB) backscatter in mid- to late-August. It is proposed that this corresponds to the bare ice zone, the high backscatter values being due to scattering from crevasses and meltwater channels, and that the inner boundary of the zone of enhanced backscatter indicates the position of the transient snow line.     

Integration of radar and Landsat-derived foliage projected cover for woody regrowth mapping, Queensland, Australia

In Queensland, Australia, forest areas are discriminated from non-forest by applying a threshold (∼ 12%) to Landsat-derived Foliage Projected Cover (FPC) layers (equating to ∼ 20% canopy cover), which are produced routinely for the State. However, separation of woody regrowth following agricultural clearing cannot be undertaken with confidence, and is therefore not mapped routinely by State Agencies. Using fully polarimetric C-, L- and P-band NASA AIRSAR and Landsat FPC data for forests and agricultural land near Injune, central Queensland, we corroborate that woody regrowth dominated by Brigalow (Acacia harpophylla) cannot be discriminated using either FPC or indeed C-band data alone, because the rapid attainment of a canopy cover leads to similarities in both reflectance and backscatter with remnant forest. We also show that regrowth cannot be discriminated from non-forest areas using either L-band or P-band data alone. However, mapping can be achieved by thresholding and intersecting these layers, as regrowth is unique in supporting both a high FPC (> ∼ 12%) and C-band SAR backscatter (> ~ − 18 dB at HV polarisation) and low L-band and P-band SAR backscatter (e.g. < =∼ 14 dB at L-band HH polarisation). To provide a theoretical explanation, a wave scattering model based on that of Durden et al. [Durden, S.L., Van Zyl, J.J. & Zebker, H.A. (1989). Modelling and observation of radar polarization signature of forested areas. IEEE Trans. Geoscience and Remote Sensing, 27, 290-301.] was used to demonstrate that volume scattering from leaves and small branches in the upper canopy leads to increases in C-band backscattering (particularly HV polarisations) from regrowth, which increases proportionally with FPC. By contrast, low L-band and P-band backscatter occurs because of the lack of double bounce interactions at co-polarisations (particularly HH) and volume scattering at HV polarisation from the stems and branches, respectively, when their dimensions are smaller than the wavelength. Regrowth maps generated by applying simple thresholds to both FPC and AIRSAR L-band data showed a very close correspondence with those mapped using same-date 2.5 m Hymap data and an average 73.7% overlap with those mapped through time-series comparison of Landsat-derived land cover classifications. Regrowth mapped using Landsat-derived FPC from 1995 and JER-1 SAR data from 1994-1995 also corresponded with areas identified within the time-series classification and true colour stereo photographs for the same period. The integration of Landsat FPC and L-band SAR data is therefore expected to facilitate regrowth mapping across Queensland and other regions of Australia, particularly as Japan's Advanced Land Observing System (ALOS) Phase Arrayed L-band SAR (PALSAR), to be launched in 2006, will observe at both L-band HH and HV polarisations.     

Monitoring leaf area of sugar beet using ERS-1 SAR data

This paper presents the results of field testing a radar model which relates leaf area index to radar backscatter for ERS-1 C-band VV polarization SAR data. Ground truth measurements of leaf area index and soil moisture content were made in selected sugar beet fields, with simultaneous acquisition of ERS-1 SAR image data. Radar backscatter coefficients were derived from the calibrated ERS-1 SAR data. The Leeuwen and Clevers expression of the water cloud model was fitted to determine the in situ relationship between radar back-scatter and leaf area index. The model can be inverted analytically to calculate leaf area index from radar backscatter. The results show considerable potential for the operational application of ERS-1 SAR data in crop monitoring.     

Decomposition of polarimetric synthetic aperture radar backscatter from upland and flooded forests

The goal of this research was to decompose polarimetric Synthetic Aperture Radar (SAR) imagery of upland and flooded forests into three backscatter types: single reflection, double reflection, and cross-polarized backscatter. We used a decomposition method that exploits the covariance matrix of backscatter terms. First we applied this method to SAR imagery of dihedral and trihedral corner reflectors positioned on a smooth, dry lake bed, and verified that it accurately isolated the different backscatter types. We then applied the method to decompose multi-frequency Jet Propulsion Laboratory (JPL) airborne SAR (AIRSAR) backscatter from upland and flooded forests to explain scattering components in SAR imagery from forested surfaces. For upland ponderosa pine forest in California, as SAR wavelength increased from C-band to P-band, scattering with an odd number of reflections decreased and scattering with an even number of reflections increased. There was no obvious trend with wavelength for cross-polarized scattering. For a bald cypress-tupelo floodplain forest in Georgia, scattering with an odd number of reflections dominated at C-band. Scattering power with an even number of reflections from the flooded forest was strong at L-band and strongest at P-band. Cross-polarized scattering may not be a major component of total backscatter at all three wavelengths. Various forest structural classes and land cover types were readily distinguishable in the imagery derived by the decomposition method. More importantly, the decomposition method provided a means of unraveling complex interactions between radar signals and vegetated surfaces in terms of scattering mechanisms from targets. The decomposed scattering components were additions to the traditional HH and V V backscatter. One cautionary note: the method was not well suited to targets with low backscatter and a low signal-to-noise ratio.     

Assessment of an analytical model for sea surface wind speed retrieval from spaceborne SAR

An analytical model based on radar backscatter theory was utilized to retrieve sea surface wind speeds from C-band satellite synthetic aperture radar (SAR) data at either vertical (VV) or horizontal (HH) polarization in transmission and reception. The wind speeds were estimated from several ENVISAT Advanced SAR (ASAR) images in Hong Kong coastal waters and from Radarsat-1 SAR images along the west coast of North America. To evaluate the accuracy of the analytical model, the estimated wind speeds were compared to coincident buoy measurements, as well as winds retrieved by C-band empirical algorithms (CMOD4, CMOD_IRF2 and CMOD5). The comparison shows that the accuracy of the analytical model is comparable to that of the C-band empirical algorithms. The results indicate the capability of the analytical model for sea surface wind speed retrieval from SAR images at both VV and HH polarization.     

Radar backscatter coefficients and snow detectability for upland terrain in Scotland

This paper presents a quantitative investigation of the relative importance of variations in incidence angle, land cover type, month of the year, and the presence or otherwise of a wet snow cover, in modulating the C-band VV backscattering coefficient from upland terrain in Scotland. We show that, provided the contributions from incidence angle and land cover are modelled, the uncertainty in a backscatter measurement can be reduced to approximately 1 dB. At this level of precision, a difference can be observed from a snow-covered area in the case of heather and rough grass, the two dominant upland vegetation types. Over heather-covered areas, a wet snow cover typically reduces the backscatter by 2 dB whereas over rough grass it is increased by about 1 dB. Densely forested areas exhibit no significant change in backscattering coefficient as a result of a wet snow cover, a result in accordance with previous research.     

A ground-based radar backscatter investigation in the percolation zone of the Greenland ice sheet

Satellite radar altimeters and scatterometers deployed over ice sheets experience backscatter from the surface and from within the snowpack, termed surface and volume backscatter respectively. In order to assess the errors in satellite altimeter measurements it is vital to know where the return is originating from in the snowpack. This return can vary spatially and temporally. Seasonal variations in the volume backscatter can be a major complicating factor in the radar return from the percolation zone. Ground-based step-frequency radar was deployed in the percolation zone of the Greenland Ice Sheet at ∼ 1945 m elevation (69 51N, 47 15W). Previous measurements in this area made by scientists from the Byrd Polar Research Centre and the University of Kansas, undertaken prior to summer melt events, have shown the strongest backscatter from ice features at around 1 m depth buried beneath the previous end-of-summer surface. In autumn 2004, radar measurements in the Ku band with bandwidths of 1 and 8 GHz were made alongside detailed stratigraphic observations within a 1 km² site. The radar results revealed no continuous reflecting horizons in the upper 3.5 m of the firn. Shallow cores and snowpits also indicated that there were no spatially continuous stratigraphic horizons across the study site. An average electromagnetic wave velocity of 2.11 ± 0.05 × 10⁸ m s^− 1 was determined for the upper metre of the firn. Surface and volume backscatter at vertical incidence were calculated using a standard model. The contribution of the surface backscatter to the total backscatter was on average 6 dB higher than that of the volume backscatter. However, at the higher 8 GHz bandwidth the strongest return frequently originated not from the surface but from within the upper 30 cm of the snowpack, most probably from thin ice layers. At 1 GHz bandwidth these ice layers were not always resolved; their return merged with the surface return, causing it to broaden, with the peak and leading edge moving down. Modelling using density and thickness measurements from shallow cores and snowpits showed that the backscatter from these shallow, thin ice layers could be stronger than the surface return owing to constructive interference from the top and base of the layers.     

Analysis of large aeolian (wind-blown) bedforms using the Shuttle Radar Topography Mission (SRTM) digital elevation data

Dry land areas cover large parts of the land masses of Earth. Of these a large portion is mantled by aeolian (wind-blown) deposits and subjected to aeolian process, i.e., the transport of sand or dust by wind. One of the most prominent morphologies created by wind-driven deposits are dunes and in their larger form draas or mega dunes. These mega dunes tend to be widely spaced; very large; often forming a base on which smaller dunes form, producing a compound dune pattern.In February 2000 the Shuttle Radar Topography Mission, onboard the space shuttle Endeavour flew an interferometric radar system whose objective was to create a DEM of nearly all Earth land masses. In this paper DEM data from the C-band 90 m data set and the X-band 30 m data set were used to map and characterize the height and spacing of the large sand seas (Ergs) on Earth. Only the larger forms of dunes could be mapped reliably. The dune spacing and heights extracted from the SRTM DEMs tended to be in overall agreement with those reported in the literature. In a comparison between the X-band and the C-band data it was found that the X-band data are more sensitive to the smaller scale undulations on the compound dunes and better revealed the full height of the dunes.     

Investigation of the effect of the incidence angle on land cover classification using fully polarimetric SAR images

Incidence angle is one of the most important imaging parameters that affect polarimetric SAR (PolSAR) image classification. Several studies have examined the land cover classification capability of PolSAR images with different incidence angles. However, most of these studies provide limited physical insights into the mechanism how the variation of incidence angle affects PolSAR image classification. In the present study, land cover classification was conducted by using RADARSAT-2 Wide Fine Quad-Pol (FQ) images acquired at different incidence angles, namely, FQ8 (27.75°), FQ14 (34.20°), and FQ20 (39.95°). Land cover classification capability was examined for each single-incidence angle image and a multi-incidence angle image (i.e., the combination of single-incidence angle images). The multi-incidence angle image produced better classification results than any of the single-incidence angle images, and the different incidence angles exhibited different superiorities in land cover classification. The effect mechanisms of incidence angle variation on land cover classification were investigated by using the polarimetric decomposition theorem that decomposes radar backscatter into single-bounce scattering, double-bounce scattering and volume scattering. Impinging SAR easily penetrated crops to interact with the soil at a small incidence angle. Therefore, the difference in single-bounce scattering between trees and crops was evident in the FQ8 image, which was determined to be suitable for distinguishing between croplands and forests. The single-bounce scattering from bare lands increased with the decrease in incidence angles, whereas that from water changed slightly with the incidence angle variation. Consequently, the FQ8 image exhibited the largest difference in single-bounce scattering between bare lands and water and produced the fewest confusion between them among all the images. The single- and double-bounce scattering from urban areas and forests increased with the decrease in incidence angles. The increase in single- and double-bounce scattering from urban areas was more significant than that from forests because C-band SAR could not easily penetrate the crown layer of forests to interact with the trunks and ground. Therefore, the FQ8 image showed a slightly better performance than the other images in discriminating between urban areas and forests. Compared with other crops and trees, banana trees caused stronger single- and double-bounce scattering because of their large leaves. As a large incidence angle resulted in a long penetration path of radar waves in the crown layer of vegetation, the FQ20 image enhanced the single- and double-bounce scattering differences between banana trees and other vegetation. Thus, the FQ20 image outperformed the other images in identifying banana trees.     

Assessment of polarimetric SAR data for discrimination between wet versus dry soil moisture conditions

Radarsat-2 imagery from extreme dry versus wet conditions are compared in an effort to determine the value of using polarimetric synthetic aperture radar (SAR) data for improving estimation of fuel moisture in a chronosequence of Alaskan boreal black spruce ecosystems (recent burns, regenerating forests dominated by shrubs, open canopied forests, moderately dense forest cover). Results show strong distinction between wet and dry conditions for C-HH and C-LR polarized backscatter, and Freeman–Durden and van Zyl surface bounce decomposition parameters (35–65% change for all but the dense spruce site). These four SAR variables have high potential for evaluation of within site surface soil moisture, as well as for relative distinction between wet and dry conditions across sites for lower biomass and sparse canopy forested sites. However, for any given test site except the shrubby regrowth site, van Zyl volume, surface, and double bounce scattering all result in similar percentage increases from dry to wet soil condition. This indicates that for most of these test sites/cases moisture enhances the magnitude of the return for all scattering mechanisms evaluated. Thus, differences in scattering from the interaction of biomass, surface roughness, and moisture condition across sites remains an issue and backscatter due to surface roughness or biomass cannot be uniquely estimated. In contrast, the Cloude–Pottier C-band decomposition variables appear invariant to soil moisture, but may instead account for variations in ecosystem structure and biomass. Further investigation is needed, as results warrant future research focused on evaluation of multiple polarimetric parameters in algorithm development.     

Waterline mapping in flooded vegetation from airborne SAR imagery

Multifrequency, polarimetric airborne synthetic aperture radar (SAR) survey of a salt marsh on the east coast of the UK is used to investigate the radar backscattering properties of emergent salt marsh vegetation. Two characteristics of flooded vegetation are observed: backscatter enhanced by approximately 1.2 dB at C-band, and 180° HH-VV phase differences at L-band. Both are indicative of a double bounce backscattering mechanism between the horizontal water surface and upright emergent vegetation. The mapping of inundated vegetation is demonstrated for both these signatures, using a statistical active contour model for the C-band enhanced backscatter, and median filtering and thresholding for the L-band HH-VV phase difference. The two techniques are validated against the waterline derived from tidal elevation measured at the time of overpass intersected with an intertidal DEM derived from airborne laser altimetry. The inclusion of flooded vegetation is found to reduce errors in waterline location by a factor of approximately 2, equivalent to a reduction in waterline location error from 120 to 70 m. The DEM is also used to derive SAR waterline heights, which are observed to underpredict the tidal elevation due to the effects of vegetation. The underprediction can be corrected for vegetation effects using canopy height maps derived from the laser altimetry. This third technique is found to improve the systematic error in waterline heights from 20 to 4 cm, but little improvement in random error is evident, chiefly due to significant noise in the vegetation height map.     

基于多阶散射模型的玉米后向散射特性分析

合成孔径雷达(Synthetic Aperture Radar,SAR)由于其特有的全天时、全天候成像及对农作物的穿透探测能力,已成为农作物信息获取的重要手段。该文建立基于Matrix Doubling 算法的玉米多阶散射模型,以全极化雷达遥感数据Radarsat-2为数据源进行模型验证,在模型基础上,根据玉米关键生长期的几何参数,分析了玉米的时域散射特征;玉米不同生长期由于结构上的差异,散射特征差别很大:在玉米出苗期,小角度情况下C波段VV-HV适用于土壤湿度的提取;在玉米成熟期,大角度情况下C波段HH-HV较适合玉米叶片含水量的分析。     

Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta

Because of the importance of rice for the global food security and because of the role of inundated paddy fields in greenhouse gases emissions, monitoring the rice production world-wide has become a challenging issue for the coming years. Local rice mapping methods have been developed previously in many studies by using the temporal change of the backscatter from C-band synthetic aperture radar (SAR) co-polarized data. The studies indicated in particular the need of a high observation frequency. In the past, the operational use of these methods has been limited by the small coverage and the poor acquisition frequency of the available data (ERS-1/2, Radarsat-1). In this paper, the method is adapted for the first time to map rice at large scale, by using wide-swath images of the Advanced SAR (ASAR) instrument onboard ENVISAT. To increase the observation frequency, data from different satellite tracks are combined. The detection of rice fields is achieved by exploiting the high backscatter increase at the beginning of the growing cycle, which allows the production of rice maps early in the season (in the first 50 days). The method is tested in the Mekong delta in Vietnam. The mapping results are compared to existing rice maps in the An Giang province, with a good agreement (higher than 81%). The rice planted areas are retrieved from the maps and successfully validated with the official statistics available at each province (R² = 0.92). These results show that the method is useful for large scale early mapping of rice areas, using current and future C band wide-swath SAR data.     

A comparison of TerraSAR-X Quadpol backscattering with RapidEye multispectral vegetation indices over rice fields in the Mekong Delta,Vietnam

Satellite-based multispectral imagery and/or synthetic aperture radar (SAR) data have been widely used for vegetation characterization, plant physiological parameter estimation, crop monitoring or even yield prediction. However, the potential use of satellite-based X-band SAR data for these purposes is not fully understood. A new generation of X-band radar satellite sensors offers high spatial resolution images with different polarizations and, therefore, constitutes a valuable information source. In this study, we utilized a TerraSAR-X satellite scene recorded during a short experimental phase when the sensor was running in full polarimetric ‘Quadpol’ mode. The radar backscatter signals were compared with a RapidEye reference data set to investigate the potential relationship of TerraSAR-X backscatter signals to multispectral vegetation indices and to quantify the benefits of TerraSAR-X Quadpol data over standard dual- or single-polarization modes. The satellite scenes used cover parts of the Mekong Delta, the rice bowl of Vietnam, one of the major rice exporters in the world and one of the regions most vulnerable to climate change. The use of radar imagery is especially advantageous over optical data in tropical regions because the availability of cloudless optical data sets may be limited to only a few days per year. We found no significant correlations between radar backscatter and optical vegetation indices in pixel-based comparisons. VV and cross-polarized images showed significant correlations with combined spectral indices, the modified chlorophyll absorption ratio index/second modified triangular vegetation index (MCARI/MTVI2) and transformed chlorophyll absorption in reflectance index/optimized soil-adjusted vegetation index (TCARI/OSAVI), when compared on an object basis. No correlations between radar backscattering at any polarization and the normalized difference vegetation index (NDVI) were observed.     

Effects of soil moisture and water depth on ERS SAR backscatter measurements from an Alaskan wetland complex

We conducted a preliminary investigation of the response of ERS C-band SAR backscatter to variations in soil moisture and surface inundation in wetlands of interior Alaska. Data were collected from 5 wetlands over a three-week period in 2007. Results showed a positive correlation between backscatter and soil moisture in sites dominated by herbaceous vegetation cover (r = 0.74, p < 0.04). ERS SAR backscatter was negatively correlated to water depth in all open (non-forested) wetlands when water table levels were more than 6 cm above the wetland surface (r = − 0.82, p < 0.001). There was no relationship between backscatter and soil moisture in the forested (black spruce-dominated) wetland site. Our preliminary results show that ERS SAR data can be used to monitor variations in hydrologic conditions in high northern latitude wetlands (including peatlands), particularly sites with sparse tree cover.     

Classification and snow line detection for glacial areas using the polarimetric SAR image

Snow cover and glaciers are sensitive indicators of the environment. The vast spatial coverage of remote sensing data, coupled with the tough conditions in areas of interest has made remote sensing a particularly useful tool in the field of glaciology. Compared to optical images, synthetic aperture radar (SAR) data are hardly influenced by clouds. This is important because glacial areas are usually under cloud cover.The Dongkemadi glacier in the Qinghai-Tibetan plateau was selected as the study area for this paper. We use polarimetric SAR (PolSAR) image for classification on and around the glacier. The contrast between ice and wet snow is remarkable, but it is difficult to distinguish the ice from the ground on SAR images due to similar backscatter characteristics in former research. In our study, we found that this distinction can be achieved by target decomposition. Support Vector Machines (SVMs) are performed to classify the glacier areas using the selected features. The glacial areas are classified into six parts: wet snow, ice, river outwash, soil land, rocky land and others. The PolSAR-Target decomposition-SVMs (PTS) method is proven to be efficient, with an overall classification accuracy of 91.1% and a kappa coefficient of 0.875. Moreover, 86.63% of the bare ice and 96.76% of the wet snow are correctly classified. The classification map acquired using the PTS method also helps to determine the snow line, which is an important concept in glaciology.     

Radar remote sensing of the spring thaw transition across a boreal landscape

The seasonal transition of the boreal forest between frozen and non-frozen conditions affects a number of ecosystem processes that cycle between winter dormant and summer active states. The relatively short K_u-band wavelength (2.14 cm) of the space-borne NASA scatterometer (NSCAT) is sensitive to changes in dielectric properties, associated with large-scale changes in the relative abundance and phase (frozen or thawed) of canopy and surface water. We used a temporal change detection analysis of NSCAT daily radar backscatter measurements to characterize the 1997 seasonal spring thaw transition period across the 10⁶ km² BOREAS study region of central Canada. In the spring, air temperature transitions from frozen to non-frozen conditions and surface observations of seasonal snow cover depletion were generally coincident with decreases in radar backscatter of more than 2.9 dB, regardless of regional landcover characteristics. We used a temporal classification of NSCAT daily differences from 5-day smoothed backscatter values to derive three simple indices describing the initiation, primary event and completion of the spring thaw transition period. Several factors had a negative impact on the relative accuracy of NSCAT-based results, including periodic gaps in NSCAT daily time-series information and a large (i.e., >2 cm day⁻¹) spring rainfall event. However, these results were generally successful in capturing the seasonal transition of the region from frozen to non-frozen conditions, based on comparisons with regional weather station network information. These results illustrate the potential for improved assessment of springtime phenology and associated ecosystem dynamics across high latitude regions, where field based and optical remote-sensing methods are substantially degraded by frequent cloud cover, low solar illumination and sparse surface weather station networks.