Radar observations of basaltic lava flows,Craters of the Moon,Idaho

Abstract

Radar images were assessed to determine the backscatter characteristics of basaltic lava flows of predominantly pahoehoe textures and the ability to detect fissure vents. The images were obtained from synthetic aperture side-looking airborne radar systems—X-band HH, X-band HV, L-band HH and L-band H V. Smooth, collapsed blisters of shelly pahoehoe have weak returns in all four radar images. These returns are identical to those from pahoehoe surfaces covered with smooth mantles of windblown sediments. Hummocky pahoehoe flows have strong backscatter in all four images, most likely due to the large range in surface roughness causing multiple scattering at both radar wavelengths. Aa lava flows show the greatest variation in backscatter intensities—strong XHH, weak XHV, strong LHH and very strong LHV returns. This variation is due to an increase in multiple scattering at the L-band scale. Although smooth and rough surface textures can be differentiated in the radar images, there are constraints in tracing textural changes back to a particular fissure vent, in part because near-vent flows do not have unique radar signatures. Eruptive fissures are detectable in the radar images by virtue of associated parallel spatter ramparts which have diagnostic, strong backscatter in the X-band images that are in contrast to the weak backscatter of the surrounding shelly pahoehoe lava. However, spatter ramparts are not delineated in the L-band images. The centimetre-scale relief of the agglutinate spatter may cause scattering of the X-band energy more than the L-band energy. Although the structures are several metres high, the look directions for both imaging systems are approximately parallel to the trend of the ramparts. The rampart walls do not serve as reflectors. Such findings emphasize the importance of look direction in the use of radar images to characterize terrains.     

Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data

The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by solving the IEM with two unknowns is a classic example of under-determination and is at the core of the problems associated with the use of radar imagery coupled with IEM-like models. This study offers a solution strategy to this problem by the use of multi-angle radar images, and thus provides estimates of roughness and soil moisture without the use of ancillary field data. Results showed that radar images can provide estimates of surface soil moisture at the watershed scale with good accuracy. Results at the field scale were less accurate, likely due to the influence of image speckle. Results also showed that subsurface roughness caused by rock fragments in the study sites caused error in conventional applications of IEM based on field measurements, but was minimized by using the multi-angle approach.     

Radar and infrared measurements of a cold eddy in the Tyrrhenian Sea

Simultaneous airborne measurements of sea surface temperature (SST) by an infrared (IR) radiometer and radar backscatter from a scattcromcter operating at the same C band as on ERS-1, were made over the Tyrrhenian Sea. The aircraft SST field showed part of the cold and warm eddy system characteristic of the region and compared well with ship-based measurements. The radar backscatter data were examined to investigate whether any dependence on SST could be discerned. It was found that the radar backscatter data gave a more intermittent view of the eddy and that view appeared to change from day to day. A change in the radar view of the eddy could occur due to changing wind fields or atmospheric stability patterns over the thermal front and this hypothesis was discussed with regard to two periods with different atmospheric conditions. For two days of very light winds and calm sea conditions the radar signature followed the main thermal gradient features and a positive, significant correlation was obtained between the SST and radar spatial patterns. For a further three days with moderate winds from the north to east quarter, a negative and generally weakening correlation was obtained with SST, with the radar view not identifying the major thermal gradients associated with the eddy.     

The field row direction relative to the radar azimuth considered as an apparent surface roughness for smooth bare soils

The row direction of fields relative to the radar view direction, as well as the natural random roughness of soil, both influence the backscattering coefficient of bare soils. On radar images, row directions are random and generally unknown, making the use of two-scale roughness radar models difficult or impossible. However it is shown here that, in given conditions, a cultivated field with eroded rows behaves like an isotropical surface. One-scale models therefore apply, and the periodic roughness of the soil can be considered together with the natural random roughness as an ‘equivalent’ roughness variable dependent on the row direction. If this observation can be generalized, variations of apparent roughness values can therefore be surveyed on temporal series of radar images without a priori knowledge of the field rows.     

A derivation of roughness correlation length for parameterizing radar backscatter models

Surface roughness is a key parameter of radar backscatter models designed to retrieve surface soil moisture (θ_S) information from radar images. This work offers a theory‐based approach for estimating a key roughness parameter, termed the roughness correlation length (L _c). The L _c is the length in centimetres from a point on the ground to a short distance for which the heights of a rough surface are correlated with each other. The approach is based on the relation between L _c and h _RMS as theorized by the Integral Equation Model (IEM). The h _RMS is another roughness parameter, which is the root mean squared height variation of a rough surface. The relation is calibrated for a given site based on the radar backscatter of the site under dry soil conditions. When this relation is supplemented with the site specific measurements of h _RMS, it is possible to produce estimates of L _c. The approach was validated with several radar images of the Walnut Gulch Experimental Watershed in southeast Arizona, USA. Results showed that the IEM performed well in reproducing satellite‐based radar backscatter when this new derivation of L _c was used as input. This was a substantial improvement over the use of field measurements of L _c. This new approach also has advantages over empirical formulations for the estimation of L _c because it does not require field measurements of θ_S for iterative calibration and it accounts for the very complex relation between L _c and h _RMS found in heterogeneous landscapes. Finally, this new approach opens up the possibility of determining both roughness parameters without ancillary data based on the radar backscatter difference measured for two different incident angles.     

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.     

The effect of tidal currents on radar backscatter from the sea around Portland Bill

Low grazing angle radar data of the sea surface were collected using three different frequencies (3, 10 and 16?GHz) from a cliff‐top site on the south coast of England. A number of features were observed in the radar imagery that could be related to the tidal current flow around Portland Bill. The strongest, most obvious features occurred near the time of low water, and these features had significantly reduced backscatter levels in horizontal polarization, with reductions up to 20?dB, or more, below the clutter levels around them. In vertical polarization, the reduction in the clutter level was typically somewhat smaller (10?dB or so) than the horizontally polarized backscatter. No convincing explanation of this effect has been found. The strain rate component in the radar line of sight was estimated from measurements of the current component calculated from the radar data. A comparison of range–time intensity images of the radar backscatter and the strain rate showed a number of strongly correlated features that repeated with the semi‐diurnal tidal period. The maximum strain rate was around 0.0005?s^?1, which produced modulations in the radar backscatter of around 2–3?dB. On occasions a number of bright streaks with a separation of around 100?m were also observed, moving away from the radar at a few cm?s^?1. A satellite image from European Remote Sensing Satellite (ERS)‐2 of the Portland area suggests that the slow‐moving streaks may be internal waves generated by tidal flow over raised bathymetry.     

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.     

Laboratory and field measurements of the modification of radar backscatter by sand

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.     

The effect of artificial rain on wave spectra and multi-polarisation X band radar backscatter

We have carried out wind-wave tank measurements using wave-height and wave-slope gauges and a coherent 9.8 GHz (X band) scatterometer, when the water surface was agitated by heavy rain (160 mm h- 1 to 300 mm h -1 ) and by wind (2 ms- 1 to 12 ms -1 ). The upwind-looking scatterometer was operating at co- (VV- and HH-) and cross- (HV-) polarisation at a steep incidence angle of 28°. In the presence of rain, the power spectral density of the wind-wave spectra is enhanced at frequencies above about 5 Hz and it is reduced at lower frequencies. This is the net effect of surface roughness production by the rain-induced splash products and of wave damping by the rain-induced turbulence. We measured isotropic (rain-dominated) wave spectra at low wind speeds and anisotropic (wind-dominated) wave spectra at high wind speeds, with a transition wind speed that increases with rain rate. The radar backscattering at co-polarisation at low wind speeds is mainly caused by rain-induced ring waves, whereas at cross-polarisation, at all wind speeds, other rain-induced splash products, like crowns, stalks, and cavities, are the dominant scatterers. We have found a rain-induced increase of the radar backscatter at co-polarisation at wind speeds of up to 9 ms- 1 and at cross-polarisation at all wind speeds. At cross-polarisation the radar backscatter slightly depends on rain rate. Using our results an analysis of spaceborne synthetic aperture radar (SAR) images of tropical rain cells was performed.     

Cover photograph Image from GOES-E spacecraft

Azimuthally travelling ocean waves are seldom well imaged by microwave real aperture radar (RAR) operating with conventional HH or VV polarizations. Attenuation of image intensity modulation in the azimuthal direction implies that ocean wave spectra derived from such images also will not be accurate. Real aperture radar cross-section modulation by long ocean waves is normally attributed to two principal sources, tilt modulation and hydrodynamic modulation. In ocean radar images both of these modulation sources are significantly attenuated in the azimuthal direction. Therefore, complete two-dimensional k-space wave spectra derived from microwave data often are quite different than physical ocean spectra. This paper uses fully-polarimetric radar measurements of ocean backscatter to identify a new source of backscatter modulation that is strongest in the azimuthal direction. This modulation source has potential for augmenting tilt and hydrodynamic modulation sources in the azimuthal direction where their weakness causes poor wave visibility. The predicted improvement in the measurement of ocean wave spectra using an optimized polarization is investigated by means of a RAR ocean imaging model. Fully-polarimetric, and conventional, radar spectrometers are proposed which are specifically optimized to sense wave-tilts in the azimuthal direction.     

Classification of sea ice types in the Ross Sea,Antarctica from SAR and AVHRR imagery

ERS-2 synthetic aperture radar (SAR) and Advanced Very High Resolution Radiometer (AVHRR) imagery are used to examine spectral characteristics of late winter/early spring ice in the Ross Sea, Antarctica. The combined spectral signatures are used to distinguish six ice types: fast ice, new ice, smooth first year ice, rough first year ice, thin new ice/wind roughened open water and glacial ice. The procedure firstly involves 'picking' class boundaries from SAR imagery based on the morphology of a speckle reduced backscatter spectrum. These class boundaries are then used as input to an iterative segmentation procedure that involves the repeated application of a speckle reduction filter to the image. For an image from late September 1996 the segmentation procedure enabled separation of five general ice categories each with a characteristic backscatter range. However because of the combined contributions of ice thickness, surface roughness, salinity and water content to the SAR backscatter, further decision criteria are required to separate some physical ice types unable to be resolved individually using this method. Coincident and co-registered infrared data from the AVHRR sensor are used to extract spectral characteristics for the final ice classes. Using this procedure we were able to distinguish floating glacier ice from thin new ice/wind roughened open water and new ice from nearshore fast ice. These ice types were unable to be separated using SAR backscatter intensity alone. In addition image subtraction was also able to clearly delineate areas of shore fast ice.     

The validity of the composite surface model and its applications to the modulation of radar backscatter

Abstract

The composite surface model is compared with the Kirchoff method and shown to be equivalent for radar backscatter at moderate incidence angles in most commonly occurring sea states. Based on this comparison, limits are determined for the validity of the composite surface model. The model is then utilized to study the modulation of the radar cross-section of the ocean surface by long surface waves and internal waves. It is shown that apart from the well understood tilt modulation and the direct hydrodynamic modulation of the short waves, there is also an additional indirect modulation of the radar cross-section due to the hydrodynamic modulation of the intermediate waves by the long waves. Computer simulations are used to investigae these modulation mechanisms for different sea states, incidence angles and radar frequencies. It is shown that this modulation is strongest at small incidence angles and high radar frequencies. The simulations show that internal waves may be observed by X-band and Ka-band radars due to the indirect modulation through the intermediate waves. It is also shown that, contrary to previous predictions, the indirect modulation process results in modulation of radar backscatter by surface waves that travel normal to the radar look direction.     

Statistical properties of soil moisture images derived from Radarsat-1 SAR data

In this article, we report on the assessment of the spatial variability of soil moisture using synthetic aperture radar (SAR) data. The imagery was acquired during five different periods over the Roseau River watershed in southern Manitoba, Canada. For validation purposes, ground measurements were carried out at 62 locations simultaneous with the satellite data acquisitions. The first step in this analysis was to assess the performance of the Integral Equation Model (IEM) in simulating backscatter coefficients for selected bare soils. In order to reduce the surface roughness effect on radar backscatter, a semi-empirical calibration technique was implemented. This calibrated model was then implemented in a simplex inversion routine in order to estimate and map soil moisture. Derived spatial patterns of near-surface moisture content were then examined using scale analyses. It has been confirmed that the variance of radar-based soil moisture images follows power law decay versus the observation scale. Also, more explicit analysis of the same soil moisture maps shows a ln–ln linear spatial scale with statistical moments. Concave shape dependency of the corresponding slopes with the moment order was observed during all radar acquisition periods. The latter indicates the presence of multifractal effects.     

Estimation of the moisture content of bare soil from RADARSAT-1 SAR using simple empirical models

Synthetic Aperture Radar (SAR) provides a remote sensing tool to estimate soil moisture. Mapping surface soil moisture from the grey level of SAR images is a demonstrated procedure, but several factors can interfere with the interpretation and must be taken into account. The most important factors are surface roughness and the radar configuration (frequency, polarization and incidence angle). This Letter evaluates the influence of these variables for estimation of bare soil moisture using RADARSAT-1 SAR data. First, the parameters of two linear backscatter models, the Ji and Champion models (Ji et al . 1995, Champion 1996), were tested and the constants recalculated. rms error based on the backscattering coefficient was reduced from 6.12 and 6.48 dB to 4.28 and 1.68 dB for the Ji and Champion models respectively. Secondly, a new model is proposed which had an rms error of only 1.21 dB. The results showed a marked increase in accuracy compared with the previous models.     

Remote sensing data of SP Mountain and SP Lava flow in North-Central Arizona

Multifrequency airborne radar image data of SP Mountain [Official name of feature (U.S. Geological Survey, 1970)] and SP flow (and vicinity) in north-central Arizona were obtained in diverse viewing directions and direct and cross-polarization, then compared with surface and aerial photography, LANDSAT multispectral scanner data, airborne thermal infrared imagery, surface geology, and surface roughness statistics. The extremely blocky, basaltic andesite of SP flow is significantly brighter on direct-polarization $\text{K-}\text{band}$ (0.9-cm wavelength) images than on cross-polarized images taken simultaneously. Conversely, for the longer wavelength (25 cm) $\text{L-}\text{band}$ radar images, the cross-polarization image returns from SP flow are brighter than the direct-polarized image. This effect is explained by multiple scattering and the strong wavelength dependence of polarization effects caused by the rectilinear basaltic andesite scatters. Two distinct types of surface relief on SP flow, one extremely blocky, the other subdued, are found to be clearly discriminated on the visible and thermal wavelength images but are separable only on the longer wavelength $\text{L-}\text{band}$ radar image data. The inability of the $\text{K-}\text{and}\text{X- (3-}\text{cm wavelength}\text{)}$ band radars to portray the differences in roughness between the two SP flow surface units is attributed to the radar frequency dependence of the surface-relief scale, which, described as the Rayleigh criterion, represents the transition between quasispecular and primarily diffuse backscatter.     

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.     

Simulated and observed L-HH radar backscatter from tropical mangrove forests

Abstract

We applied the Santa Barbara canopy backscatter model to model radar backscatter from mangrove forest stands in the Ganges delta of southern Bangladesh, and assessed the feasibility of delineating flooding boundaries within the stands. Modelled L-band (0-235 m wavelength) HH backscatter showed that canopy volume scattering dominated for stands under nonflooded ground surface. Double bounce trunk-ground term were enhanced by the presence of water under trees. For flooded mangrove forest, the trunk-ground term was dominant at small radar incidence angles; the trunk-ground term dominancy reduced as the incidence angle increased. Shuttle Imaging Radar (SIR-B) data and model results showed that for the mangrove forest, radar data with small incidence angles should be used to delineate the flooding boundaries.     

虚拟白桦纯林的雷达后向散射模拟

首先联合利用森林生长模型和分形树模型系统建立白桦纯林的空间虚拟场景并记录场景中每个散射体的方位和坐标信息,然后将此信息输入到森林植被雷达相干散射模型中进行后向散射模拟,最后分析不同的白桦结构分布对雷达后向散射的影响,以便对白桦纯林的雷达图像进行定量分析。     

基于外部风向初始信息的SAR影像海面风场反演研究

首先利用SeaWinds散射计风向作为初始信息进行SAR(Synthetic Aperture Radar)影像海面风场反演,在对SAR影像进行了噪声剔除、辐射定标、极化转换等处理后获得VV极化下各分辨单元的后向散射系数,结合地球物理模式函数获取风速并显示输出海面风场的分布情况。在此基础上,尝试利用WRF(Weather Research Forecast)数值预报模式风向作为初始场从SAR影像中反演风速信息,将结果与之前以散射计风向作为初始信息得到的反演结果进行对比,验证实验方法的正确性,高分辨率数值预报模式风向结合SAR影像将是未来业务化近岸海面风场反演的发展趋势。