Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity to dielectric properties of the target. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other parameters like surface roughness, crop cover and soil texture. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited for resolving these effects and incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisition, the gap period between the two acquisitions should be minimum. However, for RADARSAT-1 the gap is typically of the order of 3 days. To overcome this difficulty, simultaneously acquired ENVISAT-1 ASAR HH/VV and VV/VH data was studied for operational soil moisture estimation. Cross-polarised SAR data has been exploited for its sensitivity to vegetation for crop-covered fields where as co-pol ratio has been used to incorporate surface roughness for the case of bare soil. Although there has not been any multi-frequency SAR system onboard a satellite platform, efforts have also been made to understand soil moisture sensitivity and penetration capability at different frequencies using SIR-C/X-SAR and multi-parametric Airborne SAR data. This paper describes multi-incidence angle, multi-polarised and multi-frequency SAR approaches for soil moisture retrieval over large agricultural area.

This paper presents experimental results obtained with ENVISAT-ASAR space borne data of VV, VH and HH polarizations over the parts of Karnataka in the Western Ghats, India. The aim is to quantify various levels of above ground forest Biomass, Volume and Basal area with the help of empirical relationship of the backscattering coefficients with the ground inventory. Extensive field data were collected to characterize forest vegetation parameters in the plots. Ground inventory data such as GBH, tree height were collected. The above ground tree biomass (ABG) is estimated from the collected ground data using the existing allometric equations at stand level in study area. Dual polarized ENVISAT C-band Advanced Synthetic Aperture Radar (SAR) data of IS2 beam mode i.e., incidence angle ranges from 18.8°-26.1° were analyzed. The DN values of the ENVISAT-ASAR data are converted to backscattering coefficients. The forest in the study area holds 129-203 Mg ha^-1 (1Mg=10³ kg) of Biomass. Scatter plots were drawn between backscattering coefficients and Volume, Basal Area and Biomass for VV, VH and HV polarizations. Results show that with increase in the biomass levels, backscattering coefficient also increases. The backscattering coefficient of HH has significant correlation with the biophysical parameters whereas VH and VV are not well correlated. This relationship can be utilized to estimate the forest biophysical parameters of the study area.

Conventional imaging radars operating with a single polarization antenna measures only the amplitude of the returned signal. Therefore, accurate discrimination between similar scattering returns is difficult and, depending on the system's polarization configuration, many features go undetected. Recent developments in radar technology have led to the development of imaging radar polarimeters, that is, radars that are capable of imaging the Earth's surface at any and all possible polarizations through antenna synthesis techniques. The capability enables the complete measurement of a target's polarization properties, thus permitting a much more detailed understanding of the electromagnetic scattering process. The work presented in this paper describes the concept of polarimetric signatures, polarimetric scattering matrix and simple theoretical signatures from various models. The Stokes' matrix for individual class of pixels was generated using the amplitude and relative phase of the scattered wave. Based on the Stokes' matrices of the full polarimetric Lband airborne SAR data, polarization signatures were extracted and analyzed for four land cover classes: urban area, forest, agriculture fallow and water body. These signatures were compared with the theoretical polarization signatures and the scattering mechanisms were studied. The scattering mechanism of these land cover classes was also analysed based on the images generated by Pauli as well as Freeman-Durden target decomposition.

This study describes the use of SAR interferometric technique, coherence technique and backscattering coefficient data for the estimation of canopy height in forest area. The study area is Tundi Reserved Forest falling in Dhanbad district of Jharkhand state in India. Most predominant species is Shorea robusta (Sal) constituting the top storey of the forest with maximum height up to 20 m. For the purpose of validation, Ground Truth locations were taken on the basis of variability in the area. At ground truth location, sample plots were selected for the measurement of stand heights for the forest stands of different age and height categories. Interferometric SAR technique was used to generate Digital Elevation Model (DEM) in terms of Top of the Canopy Digital Surface Model (TCDSM). For this, Radarsat SAR interferometric data pair of 12 February and 7 March, 2004 were selected. The baseline for this pair was 643 m. The TCDSM at ground truth location was subtracted from the DEM obtained at clear-cut areas. The value of tree height was 8.1 m as against the measured value of 9m. The two date SLC data set (17 April and 22 May, 2004) of Envisat- ASAR were also used for the study of coherence pattern and its relation to forest height. Averages of coherence values for each of the GT sites with stand heights as well as ground height were derived using 5×5 pixel windows. The coherence values with the ground measured stand heights showed a high correlation. Coherence has been shown to be efficient for establishment of forest stand height in a forest environment. Thus, this paper demonstrates that SAR derived TCDSM and coherence can be used as a useful tool along with intensity data for the measurement of tree parameters.

Multi-frequency SAR observation over forested areas has been the subject of research owing to the frequency dependence on the contribution of radar backscatter from different parts of the vegetation canopy. The multi-frequency SAR data at P-, L-, C- and X-band was acquired over Rajpipla site (Gujarat). All the channels were in quad-pole mode except X-SAR, which was in HH and VV-polarization mode. The study area comprises of the dry and moist deciduous forest. The moist deciduous forest is not evergreen and shed their leaves during March-April. Teak (Tectona grandis) is the dominant species in the moist deciduous forest area. Dry deciduous trees are mainly khakhar (Butea monosperma). Multifrequency SAR data was processed to get geo-referenced images and all the images were co-registered. Images were converted to the backscattering image using the calibration function. For the purpose of ground verification, ground data was obtained at different locations. Ground data consisted of measurements on tree height, diameter at breast height, basal girth, crown diameter etc. for each location; measurements were done in 10m by 10 m area. The analysis of the data was carried out in relation to comparison of backscattering coefficient in different frequencies and polarizations. In general, forest type was better seen in X-band image as compared to other classes. However, X- and C-band could be comparable in terms of forest classes. Further, backscattering coefficient increases with frequency except in P-band. However, P-band showed best correlation with biomass as compared to other channels.

A comparative study of ENVISAT ASAR data and corresponding wave rider buoy data has been attempted. An algorithm has been developed to retrieve Ocean Wave Spectrum from SAR data. The resulting spectrum is compared with the wave rider buoy measured wave spectrum. To compute the 2-D image spectrum from multi-look SAR data, various corrections to the original SAR data has been applied. Thereafter, Modulation Transfer Function has been computed and utilized to convert image spectrum to the Ocean Wave Spectrum. This final ocean wave height spectrum is used to estimate the ocean wave spectral parameters and has been compared with the in-situ measurements and model derived wave spectrum. An attempt has also been made to process the Single Look Complex (SLC) data to reduce the speckle noise in the SAR data using Fast Fourier Transform (FFT).

Snow cover area (SCA) mapping is very important parameter for snowmelt runoff modeling and forecasting. Snow cover information is also useful for managing transportation and avalanche forecasting. For SCA mapping, we selected Gangotri area and ENVISAT ASAR swath-2 data sets acquired during 2003-2004. The ASAR SLC data are converted into backscattering coefficient. The backscattering coefficient images are co-registered, multi-looked and geocoded using freely available DORIS InSAR software package. Out of available images during 2 years, Nov. 2003 image was taken as a reference image to form a ratio image with respect to others. Snow covered and non-snow areas are classified using threshold value (less than -3 dB is considered as snow) based on change detection method as given by Nagler and Rott. This value is shifted to -2dB to match with the classified snow cover area from optical data of IRS-1D. With five pairs of ratio images we could observe seasonal change of snow. The problem with the technique is that it can not be used with different ASAR mode data. The threshold value also depends on the location of the area.

The snow wetness in the Himalayan snow covered region is an important parameter, for the snow melt runoff modeling and forecasting. The main objective of the study is to estimate snow wetness in parts of Himalayan snow covered regions. Snow surface backscattering can expressed as function of permittivity of snow. Reflectivity at the air snow interface increases greatly with wetness and volume scattering decreases abruptly. ENIVISAT-ASAR dual polarization (HH and VV) data have been used to investigate permittivity and snow wetness in sub Himalayan region. Raw data have been processed for backscattering coefficient (BSC) image generation for HH and VV polarization. BSC image is georeferenced and topographically corrected using high precision digital elevation model (DEM). The BSC images are despeckled using adaptive filter technique. For this study Physical optics Model (POM) for surface scattering based inversion model has been used. Physical Optics Model based inversion model gives the permittivity which can be further related for estimating snow wetness. A comparison was done between inversion model estimated snow wetness and field values of snow wetness in the study region. Comparison with field measurement showed that the correlation coefficient for snow wetness estimated from ASAR data was 0.8 at 95% confidence interval. The snow wetness ranges from 0-15% by volume.

In this paper an attempt to model wheat yield is made by exploiting characteristic interaction of cross-polarised SAR with wheat crop. SAR backscatter from a crop field is affected by the density, structure, volume and the moisture content of various components of plant (viz. head, stem, leaf) alongwith soil moisture. Hence, to effectively handle the influence of each of these components of the plant on SAR backscatter, a plant parameter, termed as Interaction Factor (IF) is conceptualised by combining volume, moisture, height for each of the component and density of plant. For this purpose, detailed experiment over farmers' fields was carried out in synchrony with SAR acquisition involving in-depth measurements on volume, moisture content and height of various components of wheat plant, number of grains, plant density and soil moisture. Stepwise regression analysis revealed that IF_Head significantly affects the shallow incidence angle, cross-polarised C-band SAR backscatter. IF_Head is also highly correlated to the number of grains. This is attributed to the fact that parameters of the wheat head from which IF_Head is calculated, namely moisture, volume and height, determine eventual number of grains. The study offers an approach for estimating wheat yield by retrieving number of grains from shallow incidence angle cross-polarised SAR data.

The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) is a conically scanning, dual-polarization, total power microwave radiometer flying on NASA's Aqua satellite. It has been taking global observations for more than four years. The instrument was provided by the Japan Aerospace Exploration Agency, JAXA, and it was built by Mitsubishi Electric Company. AMSR-E data provide information on the state of various hydrologic parameters in the atmosphere and on the Earth's surface. AMSR-E measures dual linearly polarized radiation (horizontal and vertical polarizations) at frequencies of 6.9, 10.7, 18.7, 36.5, and 89 GHz. These frequencies have diverse amounts of influence from a wide variety of lower atmospheric and surface variables. Examples of environmental results obtained from AMSR-E data are included. One of the most important new capabilities is global SST observations through clouds, including observations of the cold wakes behind hurricanes. The cold wake behind hurricane Katrina will be shown. A monthly, global soil moisture percentage map was developed from the AMSR-E retrievals, and as an additional benefit maps showing large RFI sources have been compiled. Maps of the snow water equivalent (SWE) and detailed maps of the Arctic sea ice will be shown.

Precipitation radar (PR) on Tropical Rainfall Measuring Mission (TRMM) satellite offers three-dimensional downwardlooking observations of tropical storms. Such observations are very useful to study the structure of tropical storms. This work presents a systematic study of vertical profile of reflectivity (VPR) of hurricanes over North Atlantic, typhoons over North Western Pacific and cyclones over South Indian Ocean. Due to a large number of VPR observation, it is possible to classify them into characteristic profiles so that it can be useful in comparing different structures. In this study, Self Organizing Map (SOM) is used to classify VPR of hurricanes, typhoons and cyclones observed in the years 2000, 2002 and 2003. We have not included the 2001 data because of the orbit transition during that year. More than 100 storms are studied in this work. VPR of the storms are classified into characteristic profiles. Percentages of contribution of each characteristics profile are determined. In addition the microphysical structure including drop size and its concentration is also derived. Comparative study on yearly basis of hurricanes, typhoons and cyclones reveals similarities and systematic differences among them, and those results are presented.

Possible methods for improving the way in which the emissivity of sea ice is represented in numerical weather prediction (NWP) assimilation schemes, and hence allowing increased exploitation of satellite data in these traditionally data sparse regions, are investigated by comparing emissivities retrieved from in-situ, airborne observations in the arctic and those derived from two different models. Further information is provided by sea ice type and concentration products derived from Special Sensor Microwave Imager (SSM/I) observations. Analysis of the aircraft derived emissivities shows a definite relationship between the emissivities at 157 GHz and 183 GHz irrespective of the ice type (R² = 0.97), and while this is not the case for the window channel at 89 GHz and the two higher frequencies (R² = 0.55), it will be shown that by sub setting the emissivities according to ice type results in a stronger relationship between these frequencies for first year ice (R² = 0.66 between 89 and 183 GHz) while the relationships for multi year ice are weaker. The retrieved emissivities are also compared with two emissivity models, the fast emissivity model (FASTEM) which assigns an emissivity to a prescribed ice type and a model from the NOAA (National Oceanographic and Atmospheric Administration) which uses an empirical approach based on retrievals from Advanced Microwave Sounding Unit (AMSU) brightness temperatures. The NOAA model performed better than FASTEM, although FASTEM performance was improved by weighting the emissivity spectra by the sea ice type and concentration information given by the SSM/I derived products.

The NASA RADSTAR instrument is a compact scatterometer-radiometer system designed for airborne and space remote sensing of Earth surface properties such as soil moisture and sea surface salinity. In this paper we describe the active portion of RADSTAR, the L-band Imaging Scatterometer (LIS). The system employs electronic steering and digital beamforming techniques to generate multiple, low-sidelobe beams over a scan range of +/-50 degrees below an aircraft. We discuss the design and testing of LIS, and the planned merging of the scatterometer with the radiometric components of the final instrument. In its final configuration, RadSTAR will employ a single broadband antenna to efficiently support simultaneous scatterometer (LIS) and radiometer measurements in airborne and spaceborne applications. LIS is currently being flown along with the ESTAR synthetic aperture radiometer aboard the NASA P-3 aircraft in order to prove the concept of coregistered data, setting the path for future spaceborne, single aperture, electronically scanned, radar/radiometer systems.

The National Oceanic and Atmospheric Administration (NOAA) have been flying microwave sounders since 1975 on Polar Operational Environmental Satellites (POES). Microwave observations have made significant contributions to the understanding of the atmosphere and earth surface. This has helped in improving weather and storm tracking forecasts. However, NOAA's Geostationary Operational Environmental Satellites (GOES) have microwave requirements that can not be met due to the unavailability of proven technologies. Several studies of a Geostationary Microwave Sounder (GMS) have been conducted. Among those, are the Geostationary Microwave Sounder (GEM) that uses a mechanically steered solid dish antenna and the Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) that utilizes a sparse aperture array. Both designs take advantage of the latest developments in sensor technology. NASA/Jet Propulsion Lab (JPL) has recently successfully built and tested a prototype ground-based GeoSTAR at 50 GHz frequency with promising test results. Current GOES IR Sounders are limited to cloud top observations. Therefore, a sounding suite of IR and Microwave should be able to provide observations under clear as well as cloudy conditions all the time. This paper presents the results of the Geostationary Microwave Sounder studies, user requirements, frequencies, technologies, limitations, and implementation strategies.

Recent developments in millimeter-wave receiver have enabled new remote sensing capabilities. MMIC circuits operating at frequencies as high as 200 GHz have enabled low-cost mass producible integrated receivers suitable for array applications. We will describe several ground-based demonstrations of this technology including development of integrated spectral line receivers for atmospheric remote sensing, a synthetic thinned aperture radiometer for atmospheric sounding and imaging and polarimetric array radiometers for astrophysics applications.

Technology development related to digital, antenna and RF subsystems for Microwave Radar Sensors like Synthetic Aperture Radar, Scatterometer, Altimeter and Radiometer is one of the major activities under ISRO's microwave remote sensing programme, since 1980s. These technologies are now being gainfully utilized for building ISRO's operational Earth Observation missions involving microwave sensors like Radar Imaging Satellite, RISAT SAR, Oceansat-2 Scatterometer, Megha-Tropiques, MADRAS and Airborne SAR for Disaster Management, DMSAR. Concurrently, advanced technology developments in these fields are underway to meet the major technological challenges of building ISRO's proposed advanced microwave missions like ultra-high resolution SAR's, Synthetic Aperture Radiometer (SARAD), Milli-meter and sub-millimeter wave sounders and SAR Constellations for Disaster management as well as Interferometric, Polarmetric and polarmetric interferometry applications. Also, these hardware are being designed with core radar electronics concept, in which the same RF and digital hardware sub-units / modules will be utilized to build different microwave radar sensors. One of the major and common requirements for all these active and passive microwave sensors is the moderate to highspeed data acquisition and signal processing system. Traditionally, the Data acquisition units for all these radar sensors are implemented as stand-alone units, following the radar receivers. For ISRO's C-band airborne SAR (ASAR) and RISAT high resolution SAR, we have designed and developed High Speed 8-bit ADC based I/Q Digitisers, operating at 30.814 MHz and 250 MHz sampling rates, respectively. With the increasing demand of wide bandwidth and ultra-high resolution in imaging and non-imaging radar systems, the technology trend worldwide is towards a digital receiver, involving bandpass or IF sampling, thus eliminating the need for RF down converters and analog IQ demodulators. In order to evolve a generic configuration for all the microwave sensors, we have initiated design and development of a generic L-band digital receiver, consisting of receiver elements (LNA, digital attenuator and Bandpass filter) followed by Analog-to-Digital Converter. The digitised data can then be output in parallel or serial format. Additionally, a digital signal processor performing tasks like data compression, convolution or correlation and formatting can also be integrated with this generic digital receiver. The front end of the receiver is wide-band, catering to bandwidths of upto 2 GHz while the digitisation rates are also of the order of 1-2 GHz. It is proposed to standardize the design and use this generic receiver for front end data acquisition of all the future microwave sensors. It will meet the digitisation requirements of 500 MHz to 1 GHz for ultra-high resolution (0.25-0.5 meter) SAR as well as direct sampling of the signal around 1.4GHz for L-band Synthetic Aperture Radiometer. After initial prototyping using discrete receiver elements and ultra-high speed 8-bit ADC, it will be taken up as a custom ASIC or multi-chip module consisting of RF MMIC's and a mixed signal ADC ASIC. These designs will be fabricated using InP, GaAs or SiGe process technologies at competent foundries like GATEC, SCL, Infineon/Germany, X-Fab/Germany and Ommic-Philips/France. This novel digital receiver will offer several advantages like flexibility, stability, reduced RF hardware and miniaturisation. This paper describes the ultra-high speed design requirements, configuration details and target specifications and salient features of this generic L-band digital receiver for ISRO's future spaceborne and airborne radar missions. It also addresses the associated signal integrity, EMI/EMC and thermal issues.

WindSat is the first spaceborne fully polarimetric radiometer. It measures all four Stokes components; T_v (vertically polarized), T_h (horizontally), U (difference between polarizations at +45° and -45°) and V (difference right hand minus left hand circular polarized) and is primarily developed to retrieve wind speed and direction over ocean. Here we investigate the WindSat observations over Dome C, Antarctica, consisting of nearly flat terrain at about 3200 m above sea level. The seasonal cycles of T_v and T_h reflect the surface temperature cycle and the penetration depth decreasing with increasing frequency (6 to 37 GHz), while the difference T_v - T_h is nearly constant. The U and V signals are most pronounced in Austral winter (July-August). The differences between ascending and descending overpasses, corresponding to different azimuth observing directions, take values up to 1.2 K (U) and 3 K (V). Fitting the data of for and aft swath to a second order harmonic function of the azimuth angle reveals a consistent orientation of the structures at the used frequencies 10 and 37 GHz and Stokes components U and V in the direction of about 153° with respect to north, consistent with the small overall slope direction of the terrain (145°) and ERS scatterometer observations.

This article presents some ideas and issues related to the creation of a long-term upper tropospheric humidity (UTH) data set using satellite based microwave measurements. Polar orbiting satellites have been measuring UTH for more than a decade now. There are three microwave instruments which can measure UTH from Space: Special Sensor Microwave/Temperature-2 (SSM/T2), Advanced Microwave Sounding Unit-B (AMSU-B), and Microwave Humidity Sounder (MHS). These instruments have channels at 183.31±1.00GHz which are sensitive to UTH. Retrieval of UTH and cloud issues are discussed in detail. Advantage of microwave measurements of UTH over infrared measurements are demonstrated. Preliminary results on the inter-calibration of these instruments are also shown.

ScanSAR mode of SAR operation is a very important mode with which range swath can be increased multifold. This operation is based on burst mode of operation, in which raw data is collected for a fraction of the SAR aperture time, and different bursts are considered corresponding to different contiguous range-swaths, so that we can get an equivalent swath width, which is much larger than what we can get with normal strip map-mode SAR imaging. This is achieved by re-orienting the antenna beam in the elevation direction to different sub-swaths for each burst-duration. Hence, this mode is called ScanSAR mode. Of course the penalty paid in the process, is degraded resolution. This paper presents the ScanSAR operation philosophy and the development of its processing algorithm. The algorithm is tested using Radarsat-1 data in the ScanSAR narrow mode. Different parameters like variable Doppler rate and variable PRF across the sub-swaths are estimated from the data set. In the case of ScanSAR processing, estimation of Doppler Centroid is very crucial, as burst times are very limited and hence it needs a different technique to estimate this parameter from the small burst of data. The estimation algorithm is elaborated. Another important phenomenon called the "scalloping effect" is observed in the case of ScanSAR images. The genesis of this effect and its compensation are also discussed. Also due to the unique mode of imaging in bursts, mosaicing of the sub swaths in both the range as well as the azimuth direction is required in the processed image. The overall design strategy followed for processing the Radarsat-1 data is explained, and results are presented.

This paper presents an automatic ship detection system by spaceborne SAR in coast region of the East China Sea. The system has the ability of automatic ship detection in SAR imagery and can give some information about ship, such as position, ship length, beam, velocity and direction. The work region of the system is the coast region of the East China Sea. A DEM database is used to separate land from sea and a CFAR algorithm is employed to ship detection. In order to validate the performance of the system, An experiment was conducted in the region of East China Sea in 2005, where sea surface ship observation and SAR imagery were took simultaneously. The results indicate the system has a reliable ship detection performance using Radarsat-1 SAR F2 mode imagery.

The Backus-Gilbert Inversion technique is a proven method of temperature inversion in microwave radiometry with a scope of trade-off between desired resolution and tolerable noise. In this study it is used to super-resolve brightness temperature data independent of the inversion process. The BGI-method is applied on scan-mode TMI (TRMM Microwave Imager) data. The 19.35GHz TMI channel provides brightness temperature data oversampled by a factor of two and geo-collocated with the 37GHz channel data. Consequently, the enhancement of features in the 19.35GHz image after BG-resolving is validated by the identification of such features in the 37GHz image. The potential of the BGImethod as a non-degrading interpolation technique is also tested.

This study attempts to develop an algorithm to retrieve water vapor mixing ratio profiles from satellite based microwave measurements. We use radiances measured by the five channels on the Advanced Microwave Sounding Unit-B (AMSU-B), which are sensitive to the tropospheric water vapor. The advantage of microwave remote sensing is that the data can be used even in the presence of thin clouds. The retrieval technique employed is Artificial Neural Network (ANN). A diverse set of atmospheric profiles were used to train the ANN and the algorithm has been validated with a match up data set which contains quality controlled radiosonde data and co-located AMSU-B radiances. The results show that the mixing ratio can be retrieved with an accuracy of FIXME at the surface and FIXME at the upper troposphere. It is also shown that method works well for different geographical locations using data obtained from the radiosonde.

In soil moisture retrieval by microwave remote sensing technology, vegetation effect is important, due to its emission upward as well as masking the soil surface contribution. Because of good penetration characteristics through crop at low frequencies, L-band is often used, where crop is treated as a uniform layer, and 0^th-order Brightness Temperature model is used. Higher frequencies upper than L-band, the frequencies both on NASA AQUA AMSR-E and FY-3 to be launched next year in CHINA, may be more informative in SM retrieval. The multiple-scattering effects inside crop and that between crop layer and soil surface will be increasing when frequencies go higher from L-band. In this paper, a Matrix-Doubling model that account for multiple-scattering based on ray tracing technique is used to simulate the microwave emission of vegetated-surface at C- and X-band. The orientation and size of crop element such as leaves and cylinders are accounted for in crop layer, and AIEM is used for calculation of ground surface scattering. Simulation results from this model for corn and SGP99 experiment data are in good agreement. Since complicated theoretical model as used in this paper involves too many parameters, to make SM retrieval more directly, corresponding terms from the developed model are matched with 0^th-order,so as to derive effective single scattering albedo and vegetation opacity at C- and X-band.

The forthcoming Indian satellite Oceansat-2 to be launched in 2007 will carry a microwave scatterometer and an ocean colour monitor onboard. The scatterometer, a Ku-band pencil beam sensor similar to that onboard Quikscat satellite, will provide surface vector winds over global oceans with a two days repetivity. An algorithm for retrieving wind vector from scatterometer has been developed with a solution ranking criteria of minimum normalized standard deviation (NSD) of wind speeds derived using backscatter measurements through a geophysical model function (GMF). Using Quikscat observational geometry and QSCAT-1 GMF, simulation based evaluation of algorithm performance under different noise conditions and its comparison with standard algorithm known as Maximum Likelihood Estimator (MLE) algorithm have been performed. Besides having retrieval performance closely comparable with MLE, the present algorithm has quality and rain flagging provisions. Moreover, it is computationally efficient with least subjectivity on various retrieval related parameters. These features are equally desirable for the operational implementation. Results of simulation studies related to retrieval, quality control and rain flagging along with its implementation to limited Quikscat data are presented.

Interpretation of microwave radiometric measurements over land for atmospheric studies requires representative information about surface emissivity. A simulation study has been performed to derive some of the meteorological parameters like atmospheric water vapour content over land using TRMM TMI data through assumed land surface emissivity satisfying the radiative transfer model. The process of minimization of simulated and observed radiation at TMI frequencies using a large number of simulated atmospheric and surface conditions simultaneously yields many atmospheric and surface parameters over land. Preliminary analysis of TRMM TMI data over India and adjoining land region for few days during different season has been carried out. The derived surface emissivity difference of vertical and horizontal polarization is found highly resembling with Quikscat radar backscatter of land surface over the same area corroborating the estimation of land surface emissivity parameters. The study has importance in synergic use of microwave radiometer and scatterometer for studying the surface features as well as retrieval of geophysical parameters over land in view of forthcoming Megha-Tropiques and Oceansat-2 satellites. Typical examples of TRMM-TMI and Quikscat scatterometer are presented here.

Terrestrial vegetation exhibits strong seasonal and inter-annual fluctuations, which are associated with changes in the environmental variables. The understanding of the vegetation dynamics on a long-term basis requires repetitive observations over many years at temporal and spatial scale compatible with the regional processes. Space-borne scatterometer though primarily designed for ocean study, have proved advantageous in studying vegetation dynamics at regional scale. This could be possible due to availability of high repeat cycle data in addition to availability of processed scatterometer data by SIR algorithm. In the present study, the temporal behavior of Indian tropical-moist-deciduous forests has been studied using QuikScat (Ku-band) scatterometer data of year 2000. The impact of vegetation growth and senescence was investigated by comparing σ⁰ time-series to NDVI and rainfall observations. It was observed that σ⁰ varies with different scale than the NDVI. The low correlation coefficients also indicate that, the direct relationship between σ⁰ and NDVI is either very week or absent. Therefore, inferring that NDVI, which is a measure of the vegetation greenness or vigor rather than plant water-content or height, is not important for the explanation of the backscattering behavior. Further, σ⁰ was minimum during the deciduous period with prevailing high temperature and no rainfall condition. The temporal changes in backscattering coefficient were modeled for understanding the vegetation dynamics. The study suggests the suitability of Ku-band space-borne scatterometer data for understanding the seasonal dynamics of different forest types.

The satellite propagation systems are affected by the presence of precipitation in the path of propagation to a great extent. Thus, for the optimum performance of a communication link, the system designer needs to have the knowledge about the slant path attenuation prediction for which effective rain height is an important parameter. Here we present the results of the effective rain height in statistical form for year 2004-2005.

Microwave remote sensing, due to its ability to image even during severe weather conditions is the main source for deriving flood extent for rapid mapping purpose. Most of the studies from the literature reveal that C-band SAR with HH polarization is a better option for delineation of flood extent when compared with VV polarization, which is sensitive to small ripples over flood surface. However, similar problem is observed in HH, at low incidence angles. This study focuses on the extraction of flood inundation using multi-polarized ENVISAT ASAR data acquired at both low and high incidence angles. The backscatter values for flood surface in both HH and HV polarizations were extracted. It is observed from the ASAR HH polarized data that the backscatter from floodwater is low at high incidence angles and high, in some pockets, at low incidence angles. However, with ASAR HV polarized data, the variation is marginal at both low and high incidence angles. A comparison was made between ASAR HH and HV datasets and Optical (IRS) data. The flood extents derived from both HH and HV are low when compared with the flood extent from IRS data. It is observed that the flood extent from HH is much lesser at low incidence angles (IS1). Further it is also observed that the combined flood extent from both HH and HV are more comparable with optical data, even at different incidence angles.

Passive microwave AMSR-E (Advanced Microwave Scanning Radiometer) remote sensing data has been used to monitor the seasonal snow cover variations and for the snow cover characteristics studies. In the present study the spectral and temporal variation of brightness temperature using AMSR-E has been drawn and further scattering index is calculated which filters the snow cover extent information. The derived results are compared with optical (WiFS) data for the validation. Empirical relations of snow depth were developed for different ranges using AMSR-E brightness temperature and ground observatories data from different location of the Indian Himalaya. This snow depth information works as very useful input for avalanche forecast.

A light weight, low power instrument called Multi Wavelength Dielectrometer (MWD) to measure subsurface properties of planetary surfaces is described. The MWD instrument consists of essential electronics and metallic plates acting as electrodes attached to the body of space crafts. An electric signal applied to one of the electrodes acting as a cathode sets up electric field pattern (in the soil medium) between the cathode and other electrodes acting as anodes. The electrodes are swept through multiple wavelengths (1Hz-MHz) and the electric current drawn by the electrodes or mutual capacitances between electrodes is measured at each frequency. The measured capacitances whose values depend upon electrode spacing, dielectric constant of the subsurface soil, and the frequency are then used to estimate electrical properties of the soil.