Search

Four global mosaics of Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) HH and HV polarization data were generated at 25 m spatial resolution using data acquired annually from 2007 to 2010. Variability in L-band HH and HV gamma-naught (γ 0 ) for forests was observed between regions, with this attributed to differences in forest structure and vegetation/surface moisture conditions. Region-specific backscatter thresholds were therefore applied to produce from each annual mosaic, a global map of forest and non-forest cover from which maps of forest losses and gain were generated. The overall agreement with forest/non-forest assessments using the Degree Confluence Project, the Forest Resource Assessment and Google Earth images was 85%, 91% and 95% respectively. Using 2007 as a baseline, decreases of 0.040 and 0.028 dB (with a 0.006 dB 99% confidence level) were observed in the HH and HV γ 0 respectively over the same areas suggesting a decrease in forest area and/or increased smoothing of the global surface at the L-band radar observation over the four-year period. The maps provide a new global resource for documenting the changing extent of forests and offer opportunities for quantifying historical and future dynamics through comparison with historical (1992–1998) Japanese Earth Resources Satellite (JERS-1) SAR and the forthcoming (from 2014) ALOS-2 PALSAR-2 data. Four year PALSAR mosaics and the forest/non-forest data, which were generated and analyzed in this paper, are opened to the public for free downloading albeit with coarser resolutions (WWW1). Future distribution of the higher (original) resolution datasets from PALSAR as well as the ALOS-2/PALSAR-2 is planned. [ABSTRACT FROM AUTHOR]

Backscatter measured by scatterometers and Synthetic Aperture Radars is sensitive to the dielectric properties of the soil and normally increases with increasing soil moisture content. However, when the soil is dry, the radar waves penetrate deeper into the soil, potentially sensing subsurface scatterers such as near-surface rocks and stones. In this paper we propose an exponential model to describe the impact of such subsurface scatterers on C-Band backscatter measurements acquired by the Advanced Scatterometer (ASCAT) on board of the METOP satellites. The model predicts an increase of the subsurface scattering contributions with decreasing soil wetness that may counteract the signal from the soil surface. This may cause anomalous backscatter signals that deteriorate soil moisture retrievals from ASCAT. We test whether this new model is able to explain ASCAT observations better than a bare soil backscatter model without a subsurface scattering term, using k-fold cross validation and the Bayesian Information Criterion for model selection. We find that arid landscapes with Leptosols and Arenosols represent ideal environmental conditions for the occurrence of subsurface scattering. Nonetheless, subsurface scattering may also become important in more humid environments during dry spells. We conclude that subsurface scattering is a widespread phenomenon that (i) needs to be accounted for in active microwave soil moisture retrievals and (ii) has a potential for soil mapping, particularly in arid and semi-arid environments. • ASCAT soil moisture retrievals are of poor quality in arid environments. • The physical reasons for this phenomenon have for long not been understood. • We show that this is due to backscatter signals from subsurface rocks and stones. • An exponential model to describe subsurface scattering effects is introduced. • This physical effect may be exploited for mapping soil properties in arid regions. [ABSTRACT FROM AUTHOR]

• This study presents an integrated approach for monitoring GLOF susceptibility. • Radar backscatter for glaciers and basins are seasonal and periodic. • Radar backscatter for lakes are seasonal but not periodic. • Radar backscatter changes can be attributed to ice and snow melt and lake ice. • Persistent Scatterer Interferometry allows the dictation of surface instabilities. Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer lake area change using a time-series radar backscatter intensity data such as the rapid expansion of Bechung Tsho. The PSI analysis showed that all the terminal moraines were stable except Drukchung Tsho. Its terminal moraine showed subsidence at the rate of –5.18 mm/yr. Sidewalls of lakes were also stable with the exception of Lugge Tsho at site 4. Due to the free availability of S-1 SAR data, the efficiency of processing a large amount of imagery within GEE, and the PSI technique, we were able to understand the outburst susceptibility of glacial lakes in the region at great detail. The regular acquisition of S-1 SAR data enables continuous monitoring of glacial lakes. A similar approach and concept can be transferred to any geographic region on earth that shares similar challenges in glacial lake monitoring. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

Over the last two decades, the use of synthetic aperture radar (SAR) to address geologic problems has expanded as new applications for radar have been developed. One of the earliest and perhaps most surprising results from orbital SAR images of the Sahara was that, under certain conditions, radar signals penetrated up to several meters of sand to reveal subsurface features such as ancient river channels. Subsequent studies of radar penetration of arid sand deposits have dealt with factors that govern the ability of radar to penetrate a sand cover. This paper presents results from a laboratory experiment in which radar backscatter from a surface of rocks was measured under controlled conditions as a function of frequency, polarization, incidence angle, and sand cover thickness. The sand used in the experiment had a moisture content of 0.28 vol.% and caused calculated average attenuations of 4.2±1 dB/m for C-band and ∼11±2 dB/m for X-band. Results from the experiment were compared to field measurements of sand thickness during acquisition of airborne radar images. In AIRSAR images, the extent of dry sand in a dune field appears best in C-band because longer wavelength L- and P-band signals penetrate thinner sand deposits. Images of wet sand (4.9 vol.%) suggest that L-band was able to penetrate thin sand even though that sand was wet. Together, these laboratory and field measurements contribute towards a better understanding of how a sand cover modifies the radar backscatter of a surface. [Copyright &y& Elsevier]

L-band (1.25 GHz) radar measurements of a soybean canopy indicate that the emergence of seed pods is a significant contributor to the backscatter during the late stages of the growing season. In order to validate the measured data, a realistic scattering model of the soybean canopy is developed. The parameters of the soybean canopy and underlying soil used in the model vary over the growing season based on in situ measurements. Scattering amplitudes for soybean leaves are modeled analytically by using a thin disk approximation; stem and pods are jointly modeled using a numerical electromagnetic field solver. These scattering amplitudes are together incorporated into a coherent scattering model to obtain the backscattering coefficient for VV- and HH-polarizations. The modeling results show good agreement with the radar field measurements, having RMSEs of 0.51 dB for VV-pol and 1.1 dB for HH-pol. Both measured data and modeled results show that the change of soil moisture can be accurately monitored by L-band backscatter. It is also found that the difference between HH- and VV-polarized backscatter increases as the size of the soybean pods becomes larger. A method is developed here to estimate the number of pods in a soybean canopy based on polarimetric radar backscatter at L-band. • L-band radar measurements are made for a soybean canopy over the growing season. • A Coherent backscattering model is developed for the soybean canopy at L-band. • Soybean pods are the main contributor to backscatter at reproductive stage. • Difference between the HH- and VV-pol backscatters is related to pod size/density. • Radar data has good agreement with modeling results. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) amplitude measurements from spaceborne sensors are sensitive to surface roughness conditions near their radar wavelength. These backscatter signals are often exploited to assess the roughness of plowed agricultural fields and water surfaces, and less so to complex, heterogeneous geological surfaces. The bedload of mixed sand- and gravel-bed rivers can be considered a mixture of smooth (compacted sand) and rough (gravel) surfaces. Here, we assess backscatter gradients over a large high-mountain alluvial river in the eastern Central Andes with aerially exposed sand and gravel bedload using X-band TerraSAR-X/TanDEM-X, C-band Sentinel-1, and L-band ALOS-2 PALSAR-2 radar scenes. In a first step, we present theory and hypotheses regarding radar response to an alluvial channel bed. We test our hypotheses by comparing backscatter responses over vegetation-free endmember surfaces from inside and outside of the active channel-bed area. We then develop methods to extract smoothed backscatter gradients downstream along the channel using kernel density estimates. In a final step, the local variability of sand-dominated patches is analyzed using Fourier frequency analysis, by fitting stretched-exponential and power-law regression models to the 2-D power spectrum of backscatter amplitude. We find a large range in backscatter depending on the heterogeneity of contiguous smooth- and rough-patches of bedload material. The SAR amplitude signal responds primarily to the fraction of smooth-sand bedload, but is further modified by gravel elements. The sensitivity to gravel is more apparent in longer wavelength L-band radar, whereas C- and X-band is sensitive only to sand variability. Because the spatial extent of smooth sand patches in our study area is typically <50 m, only higher resolution sensors (e.g., TerraSAR-X/TanDEM-X) are useful for power spectrum analysis. Our results show the potential for mapping sand-gravel transitions and local geomorphic complexity in alluvial rivers with aerially exposed bedload using SAR amplitude. • SAR amplitude data are used to measure alluvial channel-bed roughness. • Backscatter gradients are mostly due to changes in smooth sand-surface contribution. • L-band SAR has a more dynamic backscatter signal, modified by gravel size. • 5-m resolution SAR can assess localized spatial extents of sand-gravel patchiness. [ABSTRACT FROM AUTHOR]