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Radar data has been historically expensive and complex to process. However, in this milieu of cloud-computing platforms and open-source datasets, radar data analysis has become convenient and can now be performed for more exploratory researches. This study aims to perform multi-temporal analysis of radar backscatter to characterize dense and sparse forest from Sentinel-1 images. The area of study are reforested sites under the National Greening Program (NGP) of the Philippines. Ground data were collected: (1) in 2019, from a 1.35 ha -site in Brgy. Calula, Ipil, Zamboanga Sibugay, (2) in 2019, from a 1.10 ha- site in Brgy. Cabatuanan, Basay, Negros Oriental, and (3) from PhilLiDAR 2 – Project 3: FRExLS’ 2.4 ha -validated site in Ubay, Bohol. SAR intensity values were derived from Sentinel-1 from Google Earth Engine, which is a cloud-based platform with a repository of satellite images and functionalities for data extraction and processing. The temporal variation in C-band radar backscatter from 2014 to 2018 were analyzed. The results show, for the whole period of analysis, that: in VH polarization, dense forest samples backscatter range from −11 to −18 dB in VH and −2 to -13 dB in VV; sparse forest samples range from −12 to -21 dB in VH and −7 to −14 dB in VV; ground samples range from −12 to −24 dB in VH and −6 to −15 dB in VV; and water samples range from −21 to −30 dB in VH and −11 to −26 dB in VV. Forest backscatter are expected to saturate over time, especially in dense forests. These variations are due to differences in forest species, landscape, environmental and climatic drivers, and phenomenon or interventions on the site.

Despite decades of research confirming the benefits, most farms do not incorporate soil moisture sensing into their irrigation practices. Soil moisture sensing can be broken into two broad approaches, both of which have drawbacks. In situ sensors are installed in the ground, tend to be difficult to deploy and maintain, and have high costs. Remote-sensing based approaches use radars to infer soil moisture from surface reflection properties. While completely wireless, remote sensing suffers from lower resolution and accuracy compared to in situ sensing. We propose a hybrid approach that combines the advantages of both. This paper introduces the idea of using inexpensive in situ backscatter tags with above-ground radars, which enables completely wireless soil moisture measurements with high-accuracy and high-resolution. Our key idea is introducing a simple, power efficient modulation scheme that enables commodity radars to easily detect and range the underground tag. We have benchmarked our approach against oven-based, industry-standard ground-truth measurements and demonstrated that, at a realistic depth and across several types of soil, we achieve a 90th percentile error of 3.4%, which is the same accuracy as state-of-the-art in situ sensors. We also demonstrate that our approach works with similar accuracy at a real farm.

Sentinel-1 backscatter observations were assimilated into the Global Land Evaporation Amsterdam Model (GLEAM) using an ensemble Kalman filter. As a forward operator, which is required to simulate backscatter from soil moisture and leaf area index (LAI), we evaluated both the traditional water cloud model (WCM) and the support vector regression (SVR). With SVR, a closer fit between backscatter observations and simulations was achieved. The impact on the correlation between modeled and in situ soil moisture measurements was similar when assimilating the Sentinel data using WCM (Delta R = +0.037) or SVR (Delta R = +0.025).

The Chinese HY-2D satellite was launched on 19 May 2021, carrying a Ku-band scatterometer. Together with the operating scatterometers onboard the HY-2B and HY-2C satellites, the HY-2 series scatterometer constellation was built, constituting different satellite orbits and hence opportunity for mutual intercomparison and intercalibration. To achieve intercalibration of backscatter measurements for these scatterometers, this study presents and performs three methods including: (1) direct comparison using collocated measurements, in which the nonlinear calibrations can also be derived; (2) intercalibration over the Amazon rainforest; (3) and the double-difference technique based on backscatter simulations over the global oceans, in which a geophysical model function and numerical weather prediction (NWP) model winds are needed. The results obtained using the three methods are comparable, i.e., the differences among them are within 0.1 dB. The intercalibration results are validated by comparing the HY-2 series scatterometer wind speeds with NWP model wind speeds. The curves of wind speed bias for the HY-2 series scatterometers are quite similar, particularly in wind speeds ranging from 4 to 20 m/s. Based on the well-intercalibrated backscatter measurements, consistent sea surface wind products from HY-2 series scatterometers can be produced, and greatly benefit data applications.

Prescribed burning is a common strategy for minimizing forest fire risk. Fire is introduced under specific environmental conditions, with explicit duration, intensity, and rate of spread. Such conditions deviate from those encountered during the fire season. Prescribed burns mostly affect surface fuels and understory vegetation, an outcome markedly different when compared to wildfires. Data on prescribed burning are crucial for evaluating whether land management targets have been reached. This research developed a methodology to quantify the effects of prescribed burns using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery in the forests of southeastern Australia. C-band SAR datasets were specifically used to statistically explore changes in radar backscatter coefficients with the intensity of prescribed burns. Two modeling approaches based on pre- and post-fire ratios were applied for evaluating prescribed burn impacts. The effects of prescribed burns were documented with an overall accuracy of 82.3% using cross-polarized backscatter (VH) SAR data under dry conditions. The VV polarization indicated some potential to detect burned areas under wet conditions. The findings in this study indicate that the C-band SAR backscatter coefficient has the potential to evaluate the effectiveness of prescribed burns due to its sensitivity to changes in vegetation structure.

For most land and ice surfaces, the measured radar backscatter at the spatial resolution of a wind scatterometer is insensitive to the azimuth angle. However, for regions of East Antarctica, the backscatter strongly depends on the azimuth angle. This relationship between backscatter and azimuth angle is often modeled with a Fourier series. Although previous work has separately examined the data from QuikSCAT, a Ku-band scatterometer, and the Advanced Scatterometer (ASCAT), a C-band scatterometer, this letter compares the two on the same high-resolution grid. We find that, although QuikSCAT has superior azimuth angle coverage (due to its measurement geometry) compared to ASCAT, both are suitable to estimate the radar backscatter azimuth angle modulation of East Antarctica. The ASCAT data exhibit a much larger azimuth modulation than the QuikSCAT data. This is attributed to the different wavelengths of the microwave signal: At C-band (5.7 cm), East Antarctica has features that show radar backscatter to be more dependent on azimuth angle than at Ku-band (2.2 cm). This letter also examines the ASCAT and QuikSCAT azimuth modulation over previously identified regions of wind glaze. Although azimuth modulation is expected to be minimal over wind glaze, we find the wind-glaze regions to contain more structure than previously suggested.

Recently, one of the authors (A. V. G.) developed a theory of low-frequency plasma irregularities which are created as a consequence of neutral turbulence in the D and lower E regions. In the following this theory will be applied to coherent backscatter experiments with radars in a frequency range between 5 and 150 MHz. We discuss the dependence of the backscatter cross-section on ionospheric as well as on turbulence parameters. The backscatter increases strongly with decreasing radar frequency. Above 15 MHz the effects discussed here can probably only be detected by very powerful radars with large antenna arrays.

This paper summarizes the results of an extensive study to model the statistics of the polarimetric backscatter response of vehicles at 222 GHz. Radars operating at high millimeterwave frequencies provide the necessary high azimuth resolution envisioned for many advanced applications of automotive radars, including autonomous vehicles. The data of many polarimetric measurements of vehicles are used here to extract the statistical behavior of radar scattering from vehicles. It is found that the radar statistics for a given vehicle are different as the percentage of the illuminated area of the vehicle is changed. The Weibull distribution is found to be the best fit to all measured data, with its shape parameter adjusted for different types of vehicles, radar polarization, and percentage illumination area. The results reported in this paper should provide valuable information for developers of such radars to optimize the performance of their detection and classification algorithms.

This paper describes some of the extensive measurements taken at 77 GHz of various surfaces relevant to driverless cars. Targets of particular interest are those that will be indicative of a car's position on the road as well as those that occur during inclement weather, when visibility is limited. Results are compared to similar measurements at different frequencies when available.

Radar backscatter measurements under various road conditions are presented in this paper. With the aid of a millimeter-wave automotive radar, backscatter measurements of an asphalt road surface were obtained for a stationary and moving radar platform and under dry, rainy, snowy, and slushy conditions. The effect of the conditions on the radar's backscatter are examined, and the feasibility of a road-condition identification scheme is demonstrated.

The research aims at differentiating dominant crop cultures in two test sites of Baden-Wuert- temberg, Southern Germany by creating crop signatures from radar backscatter values. It seeks to establish whether the crop signatures collected in one test site are comparable or transferable to another test site. The two test sites are located in different agro-ecological zones as described in the climate maps of the “Klimaatlas Baden-Wuerttemberg”. TerraSAR-X images (VV polarization) for the months of July and August 2010 were overlaid with crop fields’ ground truth data. As pre-processing steps, radiometric correction was carried out on the images in order to normalize the topographical effects. Classification of the crops was performed on a field scale, according to the mean and standard deviation of their backscatter values. From the results, potatoes could be uniquely differentiated from the cereals in the two different test sites for both the months of July and August 2010. Cereals (rapes, maize, barley, wheat and oats) had comparable backscatter values and their differentiation varied from one test site to another. The results’ accuracy obtained with a maximum kappa coefficient of 0.82 agrees with results of a similar research carried out in North East Germany.

Time-dependent properties of coherent range-resolved backscatter from a sea surface with simple floating targets are studied using two-dimensional (2-D) direct numerical simulations based on a first-principles boundary integral equation technique. The deterministic sea surface is generated according to a wind-driven wave spectrum. Target motion is modeled in a simplified way as that of a massless object heaved by orbital currents. Calculations can be performed at a broad range of grazing angles and at both HH and VV polarizations. The paper gives examples of range-time records of the X-band backscatter and then focuses on the Doppler characteristics of the simulated echoes. Differences between the responses of floating targets and sea surface are rather conspicuous, and appear to be caused primarily by dissimilarities in cross-section modulation behavior.

This paper reports on a set of radar experiments conducted at 222 GHz in support of envisioned application of radars to autonomous vehicles. The measured radar backscatter data of road surfaces at incident angles between 80 and 88o are presented. The polarimetric radar response level from different surfaces encountered in roads and highway environments and the angular dependency are discussed. The results are helpful in developing models for different surfaces and in the design process and assessment of autonomous vehicles sensors.

The paper reports on an extensive set of outdoor measurements aimed at characterizing the polarimetric radar backscatter response of vehicles at 222 GHz. This effort supports the future application of high frequency radars operating around 230 GHz in autonomous vehicle navigation and collision avoidance. It is observed that radar backscatter is primarily from the outer surfaces of the vehicle and that few strong scattering centers dominate the radar return. Derived radar statistics from reported data may be used by researchers in optimizing detection.

The contribution of electromagnetic wave scattering on density irregularities in the volume component of radar backscatter was analyzed for a thick snow pack containing internal hoar/ice layers. To evaluate the efiect of this scattering, Density Deviation Factor (DDF), a statistical parameter, was introduced into the backscattering coe-cient using the \slice" approach. DDF is proportional to the intensity of the density ∞uctuation and inverse to the mean density. The inverse dependence of backscatter with accumulation rate was discussed based on the DDF parameterization of snow inhomogeneities.

Approaches exploiting the complementary information on forest above-ground biomass (AGB) contained in multi-temporal and multi-frequency radar backscatter have hardly been explored in the tropics. Having available a multi-seasonal stack of air- and spaceborne X-, C-, L-, and P-band imagery for forest sites in Lope and Mondah, Gabon, we analyzed the sensitivity of backscatter at different frequencies to AGB under varying environmental imaging conditions, and the performance of an AGB retrieval when combining multi-temporal and multi-frequency backscatter observations. For the tropical forest sites in Gabon, which differ significantly with respect to forest composition and climatic conditions, we find that i) P-band allows for estimating AGB with the highest accuracy, ii) multi-temporal L-band backscatter may achieve accuracies close to what can be achieved with few P-band observations, iii) the use of multi-temporal observations is beneficial/crucial at all frequencies, in particular when the imaging conditions are persistently moist and the sensitivity of individual images to AGB reduced, and iv) combining P- and L-band backscatter allows for improving the AGB retrieval primarily when few P-band observations are complemented by a larger number of L-band observations. While the results of this study reemphasize that P-band is the most suitable frequency for mapping AGB in the tropics, they also advise consideration of the growing archives of spaceborne backscatter observations acquired at higher frequencies when mapping AGB in the tropics.

This letter deals with the development of geophysical model functions (GMFs) specific to Oceansat-2 Scatterometer (OSCAT) for the operational retrieval of global ocean surface vector winds from OSCAT. It makes use of OSCAT-measured radar backscatter and the surface analysis winds at 10-m neutral-stability height from the European Centre for Medium-Range Weather Forecasts (ECMWF) model for the period from November 2009 to April 2010. The OSCAT-specific GMF has been used for retrieving the vector solutions from backscatter data as well as for the directional ambiguity removal. The procedures and the conditions incorporated for the same are presented in this letter.

This paper evaluates the rain effects on Ku-band radar backscatter at low incidence angles. The data used consisted of the sea surface backscatter and averaged rain rates from Tropical Rainfall Mapping Mission precipitation radar (TRMM PR) measurements and the collocated 10-m height numerical prediction wind speeds from the European Centre for Medium-Range Weather Forecasts (ECMWF). The wind-induced backscatter was estimated by the Ku-band low incidence backscatter model (KuLMOD) and possible bias due to different wind speed inputs was considered. The rain effect was analysed by comparing the TRMM PR-measured surface backscatter for the rain-affected sea surface with the collocated wind-induced backscatter. We found that the surface backscatter decreases with increases in the averaged rain rate. The rain-induced backscatter was clearly dependent of the wind speed and was slightly dependent of the incidence angle. Results show that it is necessary to develop a wind and rain backscatter model instead of single wind backscatter model.

The paper aimed to investigate interaction between electromagnetic wave and cereal parameters at column and row directions. S-band (center frequency 3.2GHz) and wheat had been selected as the research targets. During an entire wheat growth cycle, a series of data related to the interaction were collected for the analyses. Backscatter at row and column directions were analyzed as the function of the wheat temporal variations parameters. The research results show the dominated contribution determined the influence of wheat at row and column directions on radar backscatter. Moreover, a simple model has been presented to minimize the influence of column and row directions on radar backscatter. The research can be helpful to modeling and cereal monitoring by microwave remote sensing technology.

Advanced Land Observing Satellite (ALOS) Phased Array L-band type Synthetic Aperture Radar (PALSAR) backscatter images with 50 m pixel size (strip images) at HV-polarization were used to map clear-cuts at a regional and national level in Sweden. For a set of 31 clear-cuts, on average 59.9% of the pixels within each clear-cut were correctly detected. When compared with a one-pixel edge-eroded version of the reference dataset, the accuracy increased to 88.9%. With respect to statistics from the Swedish Forest Agency, county-wise clear-felled areas were underestimated by the ALOS PALSAR dataset (between 25% and 60%) due to the coarse resolution. When compared with statistics from the Swedish National Forest Inventory, the discrepancies were larger, partly due to the estimation errors from the plot-wise forest inventory data. In Sweden, for the time frame of 2008–2010, the total area felled was estimated to be 140,618 ha, 172,532 ha and 194,586 ha using data from ALOS PALSAR, the Swedish Forest Agency and the Swedish National Forest Inventory, respectively. ALOS PALSAR strip images at HV-polarization appear suitable for detection of clear-felled areas at a national level; nonetheless, the pixel size of 50 m is a limiting factor for accurate delineation of clear-felled areas.

The water cloud model is used to account for the effect of vegetation water content on radar backscatter data. The model generally comprises two parameters that characterize the vegetated terrain, A and B, and two bare soil parameters, C and D. In the present study, parameters A and B were estimated using a genetic algorithm (GA) optimization technique and compared with estimates obtained by the sequential unconstrained minimization technique (SUMT) from measured backscatter data. The parameter estimation was formulated as a least squares optimization problem by minimizing the deviations between the backscatter coefficients retrieved from the ENVISAT ASAR image and those predicted by the water cloud model. The bias induced by three different objective functions was statistically analysed by generating synthetic backscatter data. It was observed that, when the backscatter coefficient data contain no errors, the objective functions do not induce any bias in the parameter estimation and the true par...

The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-based measurements. A considerable improvement of point-based observations is offered by remote sensing technologies, which enables the determination of continuous spatial hydrological parameters and variables, such as surface roughness, which significantly influence runoff velocity and depth. Hydrological models commonly express the surface roughness using Manning’s roughness coefficient (n) as a key variable. The objectives were thus to determine surface roughness by exploiting a new high spatial resolution spaceborne synthetic aperture radar (SAR) technology and to examine the correlation between radar backscatter and Manning’s roughness coefficient in an arid environment. A very strong correlation (R2 = 0.97) was found between the constellation of small satellites for Mediterranean basin observation (COSMO)-SkyMed SAR backscatter and surface roughness. The results of this research demonstrate the feasibility of using an X-band spaceborne sensor with high spatial resolution for the evaluation of surface roughness in flat arid environments. The innovative method proposed to evaluate Manning’s n roughness coefficient in arid environments with sparse vegetation cover using radar backscatter may lead to improvements in the performance of hydrological models.

The aim of this study was to contribute for the flood disaster mitigation. We examined a derivation of the simple method as an integrated information processing for a prior risk analysis on the flood disaster by using change in the soil moisture content based on the periodically basic observation mode data of ALOS PALSAR, geographical information and point observed value of precipitation data. The soil moisture content is basically important for the understanding of flooding processes. The qualitative relationship between the radar backscatter and the soil moisture content was discerned.

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R-2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments.

This paper presents research accomplishments of Prof. Richard K. Moore during his “retirement” years at the University of Kansas (KU), when he led a research team that included the authors. Our collaborative research group consisted of Prof. Moore, B. Natarajakumar and V. Kurisunkal (graduate students in electrical engineering at KU), and Prof. D. Braaten (atmospheric science at KU), with the research supported by a NASA subcontract through Oregon State University (NS033A-04). Prof. Moore's interest and knowledge of scatterometry is well known, and his research efforts during the early to mid-2000's focused on correction methods for hydrometeors along the signal path from the satellite to/from the ocean surface. In this paper we focus on Prof. Moore's interest in signal propagation through the atmosphere, and his contributions toward developing correction methods for scatterometer signal attenuation and backscatter caused by hydrometeors.

Published version. Source at http://doi.org/10.5194/angeo-33-737-2015. We have compared radar observations of polar mesospheric summer echoes (PMSEs) modulated by artificial electron heating, at frequencies of 224 MHz (EISCAT VHF) and 56 MHz (MORRO). We have concentrated on 1 day of observation, lasting ~ 3.8 h. The MORRO radar, with its much wider beam, observes one or more PMSE layers all the time while the VHF radar observes PMSEs in 69% of the time. Statistically there is a clear difference between how the MORRO and the VHF radar backscatter reacts to the heater cycling (48 s heater on and 168 s heater off). While MORRO often reacts by having its backscatter level increased when the heater is switched on, as predicted by Scales and Chen (2008), the VHF radar nearly always sees the "normal" VHF overshoot behaviour with an initial rapid reduction of backscatter. However, in some heater cycles we do see a substantial recovery of the VHF backscatter after its initial reduction to levels several times above that just before the heater was switched on. For the MORRO radar a recovery during the heater-on phase is much more common. The reaction when the heater was switched off was a clear overshoot for nearly all VHF cases but less so for MORRO. A comparison of individual curves for the backscatter values as a function of time shows, at least for this particular day, that in high layers above ~ 85 km height, both radars see a reduction of the backscatter as the heater is switched on, with little recovery during the heater-on time. These variations are well described by present models. On the other hand, the backscatter in low layers at 81–82 km can be quite different, with modest or no reduction in backscatter as the heater is switched on, followed by a strong recovery for both radars to levels several times above that of the undisturbed PMSEs. This simultaneous, nearly identical behaviour at the two very different radar frequencies is not well described by present modelling.

Because of the cloudy conditions during the rice growth period, rice is one of the agricultural crops most suited to monitoring with the SAR instruments. Backscatter response measured by SAR is correlated with rice conditions, including height, density, biomass and structure, which are variable at different growing stages. In this paper, multi-date ENVISAT ASAR Alternating Polarization Mode (APMode) imageries were acquired during the rice crop growing cycle. At the same time, the rice parameters were measured in field. A continuous canopy model was used to compute the back-scattering from rice fields during the growth cycle, and the relationship between rice parameters and radar backscattering coefficients from both ASAR and modeling was analyzed. The effects of polari-zation, incidence angle and polarization on radar backscattering coefficients were analyzed. It was found that simulated radar backscatter has similar trends as ASAR data. This will be meaningful for the further research of rice parameters estimation from ASAR data. Different features show signifi-cantly different signatures in ASAR images and they follow some certain laws, so rice area can be accurately mapped by using multi-temporal SAR images, then rice yield can be estimated.

Radar backscatter knowledge is a valuable input for many remote sensing applications, which are based on synthetic aperture radar (SAR) systems. The amount of spaceborne data acquired within the TanDEM-X mission allows for the characterization of X-band backscatter on a global scale. The objective of this paper is to present a method for the characterization of radar backscatter behavior using a global statistical approach. The worldwide data set of images acquired within the TanDEM-X mission is taken into account, having the chance to exploit the unique high-quality topography information associated to it. The input measurements are differently assessed, by using a quality-based approach. A series of models can be derived, focusing on the backscatter dependence on polarization, incidence angle, ground classification, and seasonal time. The developed approach for the algorithm's verification is presented as well, together with some preliminary results obtained from TanDEM-X mission data. The generation of up-to-date backscatter models for X-band will provide a useful database for the development of a large number of scientific applications and for the optimization of future radar systems.

International audience; The goal of this study is to discuss the effect of multi-frequency radar configurations on the relationship between surface soil moisture and the nature of radar backscatter over bare soils. In an attempt to answer this question, the Advanced Integral Equation Model (AIEM) was used to simulate backscatter from soil surfaces with various moisture vertical profiles, for three frequency bands: L, C and X. In these computations, we investigated the influence of the vertical heterogeneity of soil moisture on the characteristics of the backscattered signals. The effect of radar frequency is distinctly demonstrated. A database produced from Envisat ASAR and TerraSAR-X data, acquired over bare soils with in situ measurements of moisture content and ground surface roughness, was used to validate the usefulness of taking the soil moisture heterogeneity into account in the backscattering model.

The effect of cobs on radar backscatter from a mature corn canopy is considered. In the past, a number of papers have modeled the backscattering properties of corn plants when the cobs are not present. It has been shown by O'Neill et al. [1] that the cob can constitute as much as one third of the total biomass of a mature corn plant. The position of the cob close to the stalk and the lack of knowledge of its dielectric properties make it difficult to model. These difficulties have been overcome with the aid of advanced numerical analysis tools and new biophysical measurements of the corn.

Thermodielectric interactions between free and bound soil water at different soil textures and frequencies affect radar backscatter. Simulations with a semi-empirical backscatter model show a potential for temperature corrections in inference of water content. A new thermodielectric response backscatter difference index was derived for remote mapping of surface soil texture.

Radar imaging is a valuable tool for the monitoring and management of tropical ecosystems. One of the obstacles to its successful usage is the variation of the radar backscatter with incidence angle caused by the side-looking mode of the sensor. Available research has modelled the effect of changes in incidence angle for soil, grass and scattering mechanisms in tree-covered areas. The effect varies depending on the scattering mechanism. To model the radar backscatter behaviour of a natural landscape, therefore, implies precise knowledge of the land-cover composition. A method for estimating and correcting the effect of changes in look angle on backscatter data is consequently proposed; it requires little field knowledge and encompasses the effects on most land-cover types in the study area. The method is based on the assumption that each line in azimuth direction contains a similar composition in regard to land-cover types. The backscatter frequency distribution of each azimuth line can then be employed to model and correct for the effect of variation in incidence angle. The results are evaluated using an existing land-cover classification to extract mean backscatter values for individual land-cover classes before and after the correction procedure. The correction procedure is shown to successfully adjust backscatter intensities to a nominal incidence angle for the vegetation communities in a coastal tropical savanna landscape in Australia's Northern Territory.

This paper describes measurements of the radar backscatter from rice crops at 9 GHz with a ground-based scatterometer. The measurements were conducted over the whole period of rice growth from transplanting to ripening, at three polarization combinations (HH, VV, and HV), and at incidence angles of 0-70/spl deg/.

C-band radar backscatter generally seems to be inversely related to accumulation rate across Greenland's dry snow zone. A coupled snow metamorphosis-backscatter model was constructed in order to investigate the observation. Accumulation rate and mean annual temperature were the coupled-model inputs. In a local area where accumulation rate is known very accurately the model predicts the backscatter level along several transects within the calibration uncertainties of the ERS-1 SAR data. The analysis was applied to the remainder of the dry snow zone. The model showed that both accumulation rate and temperature can modulate surface backscatter across Greenland's dry snow zone with accumulation rate being the primary influence.

The aim of this paper is to assess the use of RADARSAT data for rice field mapping and monitoring. The specific characteristics of RADARSAT data, i.e. the radar polarization, the spatial resolution, the range of incidence angles and the repeat cycle, have been studied. Experimental data have been collected over one of the most important irrigated flood plains of Indonesia and analysed along with RADARSAT data. The radar backscatter coefficient sigma of rice fields appears to have a significant temporal variation. However, the dynamic range of RADARSAT data is found lower than that of the ERS data due to a higher backscatter at HH than at VV polarization at early stages. At a higher incidence angle (42 compared with 23), the sigma of the fine resolution F3 mode reaches a saturation level earlier compared with the standard resolution mode, which appears consequently to be most appropriate for rice field mapping. The mapping result, based on the temporal change of the radar backscatter, was found to have an ...

Multi-temporal radar backscatter characteristics of crops and their underlying soils were analysed for an agricultural area in south-western Ontario, Canada using nine dates of ERS-1 SAR imagery acquired during the 1993 growing season. From the calibrated data, SAR temporal backscatter profiles were generated for each crop type. The results indicate that small changes in incidence-angle can have strong impacts on radar backscatter. Thus, attention must be given to local incidence-angle effects when using ERS-1 SAR data,especially when comparing backscatter coefficients of the same area from different scenes or different areas within the same scene.

Compact-range radar backscatter measurements are taken of aircraft scale models. In addition, computer software is used to predict the RCS of the aircraft. Synthetic down-range profiles formed from the two sources of backscatter data are compared and visualized in an innovative manner. Similar discrimination rates between the two aircraft are obtained on data from both sources. © 1998 John Wiley & Sons, Inc. Microwave Opt Technol Lett 17: 207–213, 1998.

A full understanding of radar backscatter from urban areas is necessary in order to develop a robust methodology for monitoring and classifying urban characteristics using remotely sensed Synthetic Aperture Radar images.This paper examines the dominant backscattering mechanisms such as single bounce from roofs, double bounce from wall-ground structures and possibly triple bounce from wall-wall-ground structures, and their relative contributions to the backscatter. With the use of quad-polarized image data such as those acquired by the NASA/JPL AirSAR system, the backscatter can be decomposed into components caused by different backscattering mechanisms, offering a promise for urban monitoring and classification.

ERS-1 Windscatterometer measurements over Siberia were investigated to determine the potential of coarse resolution radar data for land cover mapping and monitoring. Two indices have been introduced: the slope index calculates the incidence angle dependence of the radar measurements, the radar backscatter index (RBSI) combines slope index and radar backscatter intensity. Using the RBSI, good correlations to canopy density were found and the freeze/thaw-transition can be determined. Promising correspondence was found with five-day interval time series of normalized radar cross sections and crop yield estimates.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; International audience; The aim of this letter is to discuss the influence of radar frequency on the relationship between surface soil moisture and the nature of radar backscatter over bare soils. In an attempt to address this issue, the advanced integral equation model was used to simulate backscatter from soil surfaces with various moisture vertical profiles, for three frequency bands, namely, L, C, and X. In these computations, we investigated the influence of the vertical heterogeneity of soil moisture on the characteristics of the backscattered signals. The influence of radar frequency is clearly demonstrated. A database produced from Envisat ASAR and TerraSAR-X data, which was acquired over bare soils with in situ measurements of moisture content and ground surface roughness, was used to validate the utility of taking the soil moisture heterogeneity into account in the backscatter model.

In this Paper presentation, compare the normal Radar backscatter coefficient between oil spill area, clean sea area, Ship, platform area and Enteromorpha area. The result display the backscatter coefficient of oil spill area is lower than clean sea and the Enteromorpha area, ship, platform area is higher than clean sea.

The principles of coherent backscatter from irregularities created by plasma instabilities in the ionospheric E-region are described in this paper. It is intended as an introduction for readers who are not familiar with this subject and not as a review article. The general principles of radar backscatter are outlined as well as the nature of plasma instabilities that cause the irregularities. In subsequent sections the occurrence of the irregularities at different geographical latitudes is addressed and the spectrum of the backscatter is discussed. Finally, some applications, particularly of auroral radars, are briefly mentioned.