Dipanwita Haldar

ASSESSMENT OF L-BAND SAR DATA AT DIFFERENT POLARIZATION COMBINATIONS FOR CROP AND OTHER LANDUSE CLASSIFICATION

In the present study evaluation of L-band SAR data at difierent polarization combinations in linear, circular as well as hybrid polarimetric imaging modes for crop and other landuse classiflcations has been carried out. Full-polarimetric radar data contains all the scattering information for any arbitrary polarization state, hence data of any combination of transmit and receive polarizations can be synthesized, mathematically from full-polarimetric data. Circular and various modes of hybrid polarimetric data (where the transmitter polarization is either circular or orientated at 45 - , called …=4 and the receivers are at horizontal and vertical polarizations with respect to the radar line of sight) were synthesized (simulated) from ALOS- PALSAR fullpolarimetric data of 14th December 2008 over central state farm central latitude and longitude 29 - 15 0 N/75 - 43 0 E and bounds for northwest corner is 29 - 24 0 N/75 - 37 0 E and southeast corner is 29 - 07 0 N/75 - 48 0 E in Hisar, Haryana (India) Supervised classiflcation was conducted for crops and few other landuse classes based on ground truth measurements using maximum-likelihood distance measures derived from the complex Wishart distribution of SAR data at various polarization combinations. It has been observed that linear full- polarimetric data showed maximum classiflcation accuracy (92%) followed by circular-full (89%) and circular-dual polarimetric data (87%), which was followed by hybrid polarimetric data (73{75%) and then linear dual polarimetric data (63{71%). Among the linear dual polarimetric data, co-polarization complex data showed better

Analysis of Temporal Polarization Phase Difference for Major Crops in India

A polarimetric radar system measures the complete scattering matrix of a target in the backscattered fleld that includes magnitudes of linearly polarized scattering amplitudes and the co- polarised and cross-polarised phase angles. Apart from backscattering intensity, the co-polarization phase difierence (CPD) calculated from polarimetric synthetic aperture radar (SAR) data produces important information about target physical, geometrical and dielectric properties. In the present work, the distribution of CPD in C-band polarimetric SAR data corresponding to major kharif and rabi crops (denoting the monsoon and the winter season) and other land cover features have been studied over Central State Farm, Hisar, Haryana. The probability density functions (PDF) of CPD have been compared with dominant scattering contributions from these targets as obtained from polarimetric target decompositions. The results show that crops and other land cover features show characteristic CPD distributions, which relates well with crop physical and geometrical properties. An intuition of the rate of growth and plant vigour is indicative from the temporal PDF pattern.

Time series analysis of co-polarization phase difference PPD for winter field crops using polarimetric C-band SAR data

ABSTRACT The utility of time series polarimetric C-band data for vegetation state monitoring was explored to understand the mechanism of growth and phenology for important winter crops in India. Parameters investigated were HH–VV phase difference (co-polarization phase difference, PPD), amplitude ratio, and polarization indices. Data were acquired during the entire growth phase categorized as early, mid/peak vegetative, and post-vegetative /flowering phase. The trend emerging in this study showed a shift in the phase difference distribution for agricultural areas relating to the growth rate for various crops. The time series data set revealed that the PPD is a function of frequency and was directly affected by crop type (planophile or erectophile), vigour, structure, and crop biophysical parameters, particularly biomass. The behaviour of crop biomass with PPD responded differentially across crop architectures and vigour classes. Co-polarization index was found to be a good measure for discrimination in early growth stages while cross-polarization index suited in advanced vegetative stages where geometrical orientation was uniform. The PPD captured the change in frequency distribution resulting in a peaked distribution at sowing changing to smooth, well-spread frequency distribution as the peak vegetation stage approaches. This histogram nature is observed to be gradual for high-biomass crops and peaked in case of the low-biomass crops. It is indicative of the rate of growth; a low peaked normal curve indicates faster growth rate and resulting in high biomass. The amplitude ratio in the later phase of growth as on the third date is similarly altered as in the VV returns from the crop. Intuition of the rate of growth and plant vigour is obtained from the temporal PPD pattern. The current study shows that while phase differences and amplitude ratio carry little information content on a single resolution cell basis, their spatial distribution over a wider time span can be used to derive quantitative relationships between SAR response and crop condition. The synergy of information involving the above parameters were used to derive useful information on the vegetation.

JUTE AND TEA DISCRIMINATION THROUGH FUSION OF SAR AND OPTICAL DATA

Remote sensing approaches based on both optical and microwave region of EM spectra have been widely adapted for large scale crop monitoring and condition assessment. Visible, infrared and microwave wavelengths are sensitive to difierent crop characteristics, thus data from optical and radar sensors are complementary. Synthetic Aperture Radar (SAR) responds to the large scale crop structure (size, shape and orientation of leaves, stalks, and fruits) and the dielectric properties of the crop canopy. Research is needed to assess the saturation efiects of SAR data and to investigate the synergy between the optical and SAR imagery for exploring various dimensions of crop growth which is not possible with any one of them singly with higher degree of accuracy. An attempt has been made to study the potential of SAR and optical data individually and by fusing them to separate various landcover classes. Two-date and three-date SAR data could distinguish jute and tea crop with 70{85% accuracy, while cloud free optical data (green, red and infrared bands) resulted in accuracy 80{ 85%. On fusing the optical and SAR single date data of May, 29 2010 using Brovey method, an accuracy of 85% was obtained. PCA and HSV with munsell based approaches resulted in similar accuracies but HSV performed the best among these. This emphasizes on the synergistic efiect of SAR and optical data. Also the fused data could be used to delineate the crop condition and age by inputs like NDVI from optical and XPR (Cross polarization ratio) from SAR data. The co- and cross polarization ratios along with various indices viz. Biomass Index (BMI), Volume Scattering Index (VSI) and canopy structural index (CSI) were used to discriminate tea from jute. Due to difierences in structural component of tea and jute at early season as manifested by the indices, there is clear separability as observed from the mean values. Among the dual polarization combinations, HV/VV performed the best (70%) followed by HV/HH (62%) and

EVALUATION OF HYBRID POLARIMETRIC DECOMPOSITION TECHNIQUES FOR WINTER CROP DISCRIMINATION

In this paper we compare, using ISRO’s RISAT-1 FRS-1 mode Compact Polarimetric (CL-Pol) data, two widely used hybrid polarimetric decomposition techniques, m − δ and m − χ decompositions, with regard to classification accuracy for various agricultural crops of north and west India. We show that the classification based on the m − χ decomposition results in better crop separability in general. But the crop stage and existence of orientating structures in the crops affects the efficacy of decomposition; a fact vividly brought out in this paper. Theoretical insights into the effectiveness of these decomposition techniques for different crop geometry are brought forth. We also compare the classification accuracy subsequent to polarimetric speckle filtering vis-a-vis spatial multilooking (downsampling). We show that usage of an appropriate polarimetric filter tends to produce comparable accuracy for most of the agricultural classes, as that of multilook case, without degrading spatial resolution. This work showcases a custom implementation of Stokes parameter based decomposition as well as POLSAR filter based on refined Lee algorithm, written in C and tailored to RISAT-1.

Cotton Crop Biophysical Parameter Study Using Hybrid/Compact Polarimetric RISAT-1 SAR Data

A hybrid-polarity architecture, consisting of transmitting circular polarisation and receiving two orthogonal linear polarisation and also their relative phase, was used to calculate four Stokes parameters. Different parameters like Degree of Polarisation, Alpha angle, Entropy, Anisotropy, Radar vegetation Index and decompositions like Raney decomposition (m-δ), Freeman-2 and 3 component decompositions were derived from these hybrid data. Crop biophysical parameters viz. plant height, plant age and plant biomass of cotton crops grown under two different environments, i.e., rainfed and irrigated in Guajrat, India were studied with respect to derived polarimetric parameters. Right circular transmitted and horizontally (RH) and vertically (RV ) received backscatter values show good relation with the plant height, age and biomass. RH backscatter −13 dB to −7 dB and RV backscatter from −13 to −10 dB were observed for crop biophysical parameters. Volume component of all decomposition showed strong response to the increase in height, age and biomass of the plant. Radar Vegetation index (RVI) values have also shown significant increase from 0.6 to 0.7 with increasing age of the crop. The rate of growth was slow in the initial phase, but fast post mid-July for both early and late sown cases. The polarimetric parameters were found significantly correlated to the above plant biophysical parameters.