Angular and polarization response of vegetation,bare soil and water from ADEOS POLDER data over India

In this letter, the angular variations of total and polarized reflectances of vegetation, bare soil and water with respect to different Sun-target-view angles, obtained from ADEOS (Advanced Earth Observation Satellite) POLDER (Polarisation and Directionality of Earth Reflectances) measurements acquired over the Indian sub-continent during 7 November 1996, are analysed at three wavelengths, namely, 443, 670 and 865 nm. The POLDER measured reflectances are approximately corrected for molecular and aerosol effects due to path radiance assuming a single layer, horizontally homogeneous atmosphere. The variation of total and polarized reflectances of three targets as a function of view zenith and relative azimuth angles are presented. The corrected target polarized reflectances show a monotonic decrease with relative azimuth and view zenith angles. A semi-empirical model was fitted to the corrected total reflectances for the three targets at three wavelengths. Statistical analysis of regression coefficients show that the coefficient corresponding to normalized reflectance, k₀, is physically significant.     

The use of a microwave backscatter model for retrieving soil moisture over bare soil

Abstract

Most attempts at predicting soil moisture from C-band microwave backscattering coefficients for bare soil are made by fitting experimental calibration relations obtained for limited ranges of incidence angle and soil surface roughness. In this paper, a more general approach is discussed using an inversion procedure to extend the use of a single experimental calibration relation to a wider range of incidence angle and surface roughness. A correcting function is proposed to normalize the backscattering coefficients to the conditions (incidence angle and surface roughness) of the calibration relation. This correcting function was derived from simulated data using the physical optics or KirchhofTs scatter model using the scalar approximation. Before discussing the inversion procedure, the backscattering coefficients calculated by the model have been compared with experimental data measured in the C-band, HH polarization and three incidence angles (Θ= 15°, 23°, 50°) under a wide range of surface soil moisture conditions (0.02H_v  0.35cm³ cm^-3) and for a single quite smooth soil surface roughness (0–011 _s  OOI4/n)m. The model was found to be experimentally validated from 15° to 23° of incidence and for surface soil moistures higher than 0-I0cm³cm^-3. For the inversion procedure, it is assumed to have a wider range of validity (15°  Θ 35° ) for ihc incidence angle. A sensitivity analysis of the model to errors on roughness parameter and incidence angle was performed in order to assess the feasability and suitability of the described inversion procedure.     

Appropriate scale of soil moisture retrieval from high resolution radar imagery for bare and minimally vegetated soils

This research investigates the appropriate scale for watershed averaged and site specific soil moisture retrieval from high resolution radar imagery. The first approach involved filtering backscatter for input to a retrieval model that was compared against field measures of soil moisture. The second approach involved spatially averaging raw and filtered imagery in an image-based statistical technique to determine the best scale for site-specific soil moisture retrieval. Field soil moisture was measured at 1225 m² sites in three watersheds commensurate with 7 m resolution Radarsat image acquisition. Analysis of speckle reducing block median filters indicated that 5 × 5 filter level was the optimum for watershed averaged estimates of soil moisture. However, median filtering alone did not provide acceptable accuracy for soil moisture retrieval on a site-specific basis. Therefore, spatial averaging of unfiltered and median filtered power values was used to generate backscatter estimates with known confidence for soil moisture retrieval. This combined approach of filtering and averaging was demonstrated at watersheds located in Arizona (AZ), Oklahoma (OK) and Georgia (GA). The optimum ground resolution for AZ, OK and GA study areas was 162 m, 310 m, and 1131 m respectively obtained with unfiltered imagery. This statistical approach does not rely on ground verification of soil moisture for validation and only requires a satellite image and average roughness parameters of the site. When applied at other locations, the resulting optimum ground resolution will depend on the spatial distribution of land surface features that affect radar backscatter. This work offers insight into the accuracy of soil moisture retrieval, and an operational approach to determine the optimal spatial resolution for the required application accuracy.     

Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands

The study of radar backscattering signatures of wheat fields was investigated, using data collected on the Orgeval agricultural watershed (France) by the airborne scatterometer ERASME in C and X bands, HH and VV polarizations, at incidence angles from 15° to 45°, during two years for different soil moisture conditions with simultaneous ground-based measurements. A simple parameterization as water-cloud model with two driving parameters (the surface soil moisture and the plant water content) gives satisfactory results to estimate radar cross sections of wheat for a wide range of frequencies (C and X bands) and incidence angles (20° and 40°) within 1 dB in CHH and XHH and 2 dB in CVV and XVV. At the lower frequency (C band) the attenuated soil backscattering by the vegetation is dominant. It is shown that simple linear relations in C band between radar cross section and soil moisture are insufficient. A correction term for the vegetation attenuation is needed and is determined. Low contrast between the backscattering of dry and wet soil (around 6 dB) for a given vegetation density leads to a relatively high error in the estimation of soil moisture by radar (0.06 cm³ / cm³). At the higher frequency (X band), the radar backscattering is negatively correlated to the vegetation water content with a saturation of the radar cross section as the plant grows (about 6 dB of dynamic range between low and fully grown canopy) with no dependence on the soil signal. The achievable accuracy in the estimation of crop water content is the same at 20° and 40° and higher in XHH (about 0.5 kg/m²) than in XVV.     

Dynamic change of CO2 flux over bare soil field and its relationship with remotely sensed surface temperature

This study investigated the potential of thermal remote sensing for estimating ecosystem surface CO₂ flux. Ecosystem surface CO₂ flux was measured by an eddy covariance method for more than 3 years, in conjunction with thermal and optical remote sensing measurements as well as micrometeorological, soil and plant measurements. The soil was Andisol (Hydric Hapludands), a humic volcanic ash soil, which is the major cultivated soil for upland crops in Japan. The soil surface CO₂ flux under bare soil conditions was best correlated with the remotely sensed surface temperature, while air temperature was less well correlated and soil temperature and soil water content were poorly correlated. The relationship was well expressed by an exponential Q ₁₀ function (r ²=0.66, RMSE=0.098). The value of Q ₁₀ and the threshold temperature at which the CO₂ flux approached zero were estimated to be 1.47 and 10.0°C, respectively. Results suggested that the soil surface temperature had the dominant effect on the microbial respiration as well as on the physical processes determining the CO₂ gas transfer at the soil–atmosphere interface. Remotely sensed surface temperature will provide useful information for investigation of CO₂ transfer processes near the soil surface, as well as for quantitative assessment of ecosystem surface CO₂ flux.     

Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields

The sensitivity of TerraSAR-X radar signals to surface soil parameters has been examined over agricultural fields, using HH polarization and various incidence angles (26°, 28°, 50°, 52°). The results show that the radar signal is slightly more sensitive to surface roughness at high incidence (50°–52°) than at low incidence (26°–28°). The difference observed in the X-band, between radar signals reflected by the roughest and smoothest areas, reaches a maximum of the order of 5.5 dB at 50°–52°, and 4 dB at 26°–28°. This sensitivity increases in the L-band with PALSAR/ALOS data, for which the dynamics of the return radar signal as a function of soil roughness reach 8 dB at HH38°. In the C-band, ASAR/ENVISAT data (HH and VV polarizations at an incidence angle of 23°) are characterised by a difference of about 4 dB between the signals backscattered by smooth and rough areas.Our results also show that the sensitivity of TerraSAR-X signal to surface roughness decreases in very wet and frozen soil conditions. Moreover, the difference in backscattered signal between smooth and rough fields is greater at high incidence angles. The low-to-high incidence signal ratio (Δσ° = σ_26°–28°/σ_50°–52°) decreases with surface roughness, and has a dynamic range, as a function of surface roughness, smaller than that of the backscattering coefficients at low and high incidences alone. Under very wet soil conditions (for soil moistures between 32% and 41%), the radar signal decreases by about 4 dB. This decrease appears to be independent of incidence angle, and the ratio Δσ° is found to be independent of soil moisture.     

Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust

Soils play a key role in shaping the environment and in risk assessment. We characterized the soils of bare agricultural plots using TerraSAR-X (9.5 GHz) data acquired in 2009 and 2010. We analyzed the behavior of the TerraSAR-X signal for two configurations, HH-25° and HH-50°, with regard to several soil conditions: moisture content, surface roughness, soil composition and soil-surface structure (slaking crust).The TerraSAR-X signal was more sensitive to soil moisture at a low (25°) incidence angle than at a high incidence angle (50°). For high soil moisture (> 25%), the TerraSAR-X signal was more sensitive to soil roughness at a high incidence angle (50°) than at a low incidence angle (25°).The high spatial resolution of the TerraSAR-X data (1 m) enabled the soil composition and slaking crust to be analyzed at the within-plot scale based on the radar signal. The two loamy-soil categories that composed our training plots did not differ sufficiently in their percentages of sand and clay to be discriminated by the X-band radar signal.However, the spatial distribution of slaking crust could be detected when soil moisture variation is observed between soil crusted and soil without crust. Indeed, areas covered by slaking crust could have greater soil moisture and consequently a greater backscattering signal than soils without crust.     

Retrieval of bare soil and vegetation parameters from wind scatterometer measurements over three different climatic regions

Medium to low resolution (1-50 km) active microwave sensors such as spaceborne scatterometers and wide-swath mode synthetic aperture radars have great potential as tools for long term monitoring over land and ice. To optimise the use of this kind of data, the heterogeneity of the target and its effects on the radar measurements need to be investigated and modelled, particularly in the view of retrieving geophysical parameters. In this paper, wind scatterometer measurements over three different test sites, the NOPEX region in Sweden, the HAPEX-Sahel site in Niger and the Niger delta area in Nigeria, are analysed. For these regions, a forward model is developed by considering the backscatter contributions of the bare surface, the seasonal and evergreen vegetation and the open water areas. Colocated high spatial resolution SAR data and ground information are used to characterise the target scene. The model is then inverted to retrieve monthly soil roughness, dielectric properties and vegetation parameters. It is shown that the measurements contain enough information to characterise these three different regions and to monitor their temporal evolution. The retrieved values obtained for the bare surface and the vegetation parameters are consistent with ground measurements collected in these areas. Further improvements are achieved by incorporating the time scale variability of the variables investigated into the retrieval scheme.     

Simple,efficient allocation of modelling runs on heterogeneous clusters with MPI

In scientific modelling and computation, the choice of an appropriate method for allocating tasks for parallel processing depends on the computational setting and on the nature of the computation. The allocation of independent but similar computational tasks, such as modelling runs or Monte Carlo trials, among the nodes of a heterogeneous computational cluster is a special case that has not been specifically evaluated previously. A simulation study shows that a method of on-demand (that is, worker-initiated) pulling from a bag of tasks in this case leads to reliably short makespans for computational jobs despite heterogeneity both within and between cluster nodes. A simple reference implementation in the C programming language with the Message Passing Interface (MPI) is provided.     

Review article Synthetic aperture radar (SAR) frequency and polarization requirements for applications in ecology,geology, hydrology,and oceanography: A tabular status quo after SIR-C/X-SAR

The Spaceborne Imaging Radar-C, X-Band Synthetic Aperture Radar (SIR-C/X-SAR) was the first multi-frequency and multi-polarization SAR system to be launched into space. SIR-C/X-SAR imaged over 300 sites around the Earth returning 143 terabits of data. There has been a tremendous advancement of knowledge in the field of radar remote sensing accomplished in the last two years, as well as verification of earlier findings since the two successful SIR-C/X-SAR missions. This review article presents the current status of optimal SAR parameters for various key issues within the disciplines of ecology, geology, hydrology, and oceanography. A polarimetric X- and L-band radar is suggested as a result of our review for future SAR sensors. The design of a single frequency, albeit polarimetric, SAR satellite, limits applications, as can be deduced from the tables.     

Monitoring insect migration with radar: the ventral‐aspect polarization pattern and its potential for target identification

Automated vertical‐beam radars employing linear polarization and incorporating a narrow‐angle conical scan provide an effective means for season‐long monitoring of insect migratory activity at altitudes up to about 1 km. As well as detecting and quantifying migration events, these radars provide information about the identity of the targets they detect; such information may provide a means for excluding unwanted taxa from the radar‐observation summaries that are produced for pest managers and other potential users. The copolar‐linear polarization pattern (CLPP), a property of individual targets that is retrieved from the IMR data during routine processing, provides an indication of the shape of the target when viewed from below (i.e. ventrally). The form of the CLPP for insect targets, and the possible extent of its variation, is determined from scattering theory and symmetry considerations. CLPP parameters retrieved from a sample of echoes recorded at a site in inland Australia during a night when two different types of insect were migrating are consistent with the theory, but not all possible parameter combinations occurred. CLPP parameters are correlated with both target size and wingbeat frequency, and on this occasion all three characters discriminated reliably between the two target classes.     

Relationships between aerosol index,ozone, solar zenith angle and surface reflectivity: a case study of satellite observations over Lagos

Surface reflectivity (RFL), solar zenith angle (SZA), ozone and aerosol index (AI) daily data over Lagos (6.60° N, 3.33° E) measured by the Total Ozone Mapping Spectrometer (TOMS) were examined to determine the relationship between the parameters. We found that aerosol distribution can fully account for changes in RFL in the presence of ozone when other factors are held constant. We also showed that dust distribution over Lagos varies seasonally, reaching a maximum during the local dry season and a minimum during the local wet season whereas ozone peaks during the wet season and decreases to a minimum during the dry season. Aerosol variation was further linked to the seasonal transport of sahelian dust by the northeasterly wind that arrives at the location during the dry season and the eventual cloud washout during the wet season while the ozone distribution was attributed to the near balance between production and loss of the pollutant as a consequent of local wind transport.     

Observational study of cloud base height and its frequency over a tropical station,Thiruvananthapuram, using a ceilometer

This study aims to investigate the characteristic features of cloud base height (CBH) over Thiruvananthapuram during different seasons. CBH data were used for the present work derived from the Vaisala Laser Ceilometer, CL31 (VLC) installed at the campus of the Centre for Earth Science Studies, Akkulam (8.29° N, 76.59° E, 15 m above sea level). The VLC was in operation from the second week of July 2006 onwards. From the study, we found that CBH shows distinct diurnal and seasonal variations during all the seasons (except on rainy days). The diurnal variation for low-level clouds was different from that for the mid-level clouds. A cloud-free layer is evident in the region between 2.5 and 4 km. This cloud-free zone is more prominent during the southwest monsoon period compared to other seasons. Moreover, the monthly variations of cloud frequency and CBH were also described in addition to the different periodicities in cloud frequency. The periodicities found in the cloud frequency were 8 days and 30 days and these are significant at the 5% level. Thermodynamic parameters from the radiosonde were also related to the cloud frequency for various seasons and they were in good agreement.     

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.     

The use of biophysical indices and coefficient of variation derived from airborne synthetic aperture radar for monitoring the spread of aquatic vegetation in tropical reservoirs

This paper compares the use of biophysical indices and coefficients of variation derived from airborne synthetic aperture radar for discriminating and characterising land cover classes in the Tucurui reservoir. It assumes that the structural and dielectric properties of the land cover classes are sufficiently distinct to permit their discrimination using airborne C-band SAR data at different polarizations. Analyses of the results show that any of the proposed indices can be used effectively to discriminate among the land cover classes in the Tucurui reservoir. Certain combinations of polarizations and biophysical indices can, however, improve the saparability of the land cover classes.     

Impact of polarization and incidence of the ASAR sensor on coastline mapping: example of Gabon

Coastline mapping is of great interest in many different applications. In this Letter, we analyse the effect of the polarization and the incidence angle of the new Advanced Synthetic Aperture Radar (ASAR) sensor on coastline detection. Results indicate a marked dependence of the incidence angle and polarization on the delimitation between land and sea. At low incidence angles (<30°), delimitation is much clearer with HV polarization than with HH and VV polarizations. Delimitation is high whatever the polarization at high incidence angles (>30°). The multi‐polarization aspect of ASAR, in addition to its multi‐incidence aspect, therefore, allows coastline evolution to be monitored both more efficiently and more frequently. Consequently, the ASAR sensor is better adapted to coastline monitoring than the older ERS‐1/2 and Radarsat‐1 sensors.     

Formulation of soil angle of shearing resistance using a hybrid GP and OLS method

In the present study, a prediction model was derived for the effective angle of shearing resistance (?′) of soils using a novel hybrid method coupling genetic programming (GP) and orthogonal least squares algorithm (OLS). The proposed nonlinear model relates ?′ to the basic soil physical properties. A comprehensive experimental database of consolidated-drained triaxial tests was used to develop the model. Traditional GP and least square regression analyses were performed to benchmark the GP/OLS model against classical approaches. Validity of the model was verified using a part of laboratory data that were not involved in the calibration process. The statistical measures of correlation coefficient, root mean squared error, and mean absolute percent error were used to evaluate the performance of the models. Sensitivity and parametric analyses were conducted and discussed. The GP/OLS-based formula precisely estimates the ?′ values for a number of soil samples. The proposed model provides a better prediction performance than the traditional GP and regression models.     

Altitudinal and temporal evolution of raindrop size distribution observed over a tropical station using a K-band radar

Rain drop size distribution (DSD) measurements at different heights were made using a micro rain radar (MRR) at Thiruvananthapuram (latitude: 8.3° N, longitude: 76.9° E). Rain DSD data obtained from the MRR have been compared with a Joss–Waldvogel impact-type disdrometer (RD-80) deployed nearby and found to have good agreement. The analysis uses data collected during 16 continuous rainfall episodes during the southwest monsoon (June to September, JJAS) season. Since all the episodes behaved similarly, a single continuous rainfall episode occurring from 1610:01 to 1612:31 hours Indian Standard Time (IST) on 12 August 2006 is presented here. The fall velocity of those drops that contributed most to the rain rate was more or less constant at different altitudes and also with time during this episode, and the average value was 4.65 m s^?1. The rain rate (RR) was below 5 mm h^?1 for all the heights throughout the time. At the beginning of the rain episode, the number of drops at any given altitude was lower for larger drops. But towards the end of the episode, the number of drops in the smallest size class had reduced at almost all heights, whereas the number of drops in the larger size classes had increased. This suggests that the larger drops coming from above on colliding with smaller drops could coalesce, thus sweeping out the smaller drops as they fall. The reduction of small drops is seen with a corresponding increase in larger drops and without increase also during the course of a rainfall event. The former is an indication of coalescence while the latter is that of evaporation. All these observed phenomena in the natural rain support the observations made by Low and List in 1982.