C. V. Rao

Expansion of LISS III swath using AWiFS wider swath data and contourlet coefficients learning

Spaceborne sensors have limited capability to acquire images with wider swath at high spatial and high temporal resolutions simultaneously. This study reports a ground processing technique that combines images from two sensors onboard Resourcesat-2 (RS2) Linear Imaging and Self-Scanning Sensor (LISS III) and an Advanced Wide-Field Sensor (AWiFS) to overcome this limitation. The spatial resolution of LISS III is 23.5 × 23.5m and that of AWiFS is 56 × 56m. The temporal resolution of LISS III is 24 days and that of AWiFS is 5 days. The 140-km swath of the LISS III overlaps at center portion of 740-km swath of AWiFS in simultaneous acquisition. Assume that the nonoverlapping region of the AWiFS contains similar Earth’s surface features of the LISS III overlapping region; then, it is possible to enhance the spatial resolution of AWiFS to the spatial resolution of LISS III in the nonoverlapping region. With this assumption, we propose a novel technique to enhance the spatial resolution of the nonoverlapping region through a single-image super-resolution technique using nonsubsampled contourlet transform (NSCT) and evaluated it on RS2 data-sets. The proposed method can create a synthetic image with 740-km swath at 23.5 × 23.5m spatial and 5-day temporal resolutions. Experimental results demonstrated that it outperforms the support vector regression (SVR)-based methods in prediction accuracy and computational time.

Restoration of high frequency details while constructing the high resolution image

Indian Remote Sensing (IRS) Resourcesat satellites have AWiFS, LISS-III, LISS-IV sensors of 56m, 23.2m, 5.8m spatial resolutions respectively and of having identical spectral and temporal (simultaneous acquisition) resolutions but they are different in spatial and radiometric resolutions. In this work, we are trying to create high resolution (HR) image from coarser resolution AWiFS image called as emulated LISS-III like HR image. It will have HR (original LISS-III) image characteristics and minimal Mean Squared Error (MSE), ideally zero difference with LISS-III image as refernce, which inturn processed for identical spatial resolution of LISS - III. Ground sampling distance (GSD) of AWiFS is equivalent to 2.4 pixels of LISS-III. Radiance values are compared for normalization purpose, after weighted averaging of LISS-III to create AWiFS equivalent spatial resolution. Spatial resolution can be enhanced by improving the spatial sampling density of the signal. Nyquist-Shannon sampling theorem directs the sampling rate for exact reconstruction of the signal. The Resourcesat images are pre-processed to match this condition. Papoulis-Gerchberg algorithm is suitably improved for constructing the HR image from AWiFS. The results are compared with the classical interpolation techniques such as nearest neighbor, bilinear, spline, cubic convolution Papoulis-Gerchberg and modified Papoulis-Gerchberg [1].

Fast spatiotemporal data fusion: merging LISS III with AWiFS sensor data

The high resolution of remote sensors has evolved to capture the fine details of the Earth’s surface features in remote-sensing (RS) data. There is a trade-off between this fine spatial resolution and the temporal resolution of global space-borne sensors. Global space-borne sensors are not good enough to acquire an image at fine spatial and high temporal (FSHT) resolutions simultaneously. In this article, we propose a computationally efficient technique to create a FSHT resolution image using a ground-based data processing system. Resourcesat-2, part of the Indian Space Research Organization’s (ISRO’s) mission, carries linear imaging self-scanners (LISS III and LISS IV) and an advanced wide-field sensor (AWiFS) on board. The spatial and temporal resolutions of LISS III are 23.5 m and 24 days and those of AWiFS are 56 m and 5 days, respectively. The proposed method creates a synthetic FSHT resolution image with 23.5 m spatial and 5 day temporal resolution. This method is referred to as ‘LISS III spatial and AWiFS temporal’ (LSAT) data fusion. The LSAT data fusion method is based on a sub-pixel relationship between the images of a single AWiFS–LISS III image pair, which was acquired before or after the ‘prediction date’: a synthetic LISS III image for the time is ‘predicted’ (synthesized) using an AWiFS image at time and a single AWiFS–LISS III image pair at time , where . The LSAT model was tested on simulated and real data sets acquired by the LISS III and AWiFS sensors. The proposed method was compared with the recently developed spatiotemporal data fusion methods. The experimental results demonstrate that the method is computationally efficient and shows consistent prediction accuracy in retrieving surface reflectance changes.

Degradation and Metabolite Profiling of Benz (a) Anthracene, Dibenz (a, h) Anthracene and Indeno [1, 2, 3-cd] Pyrene by Aspergillus terricola

ABSTRACT Mycoremediation of low molecular weight polycyclic aromatic hydrocarbons (PAH) is well studied. This study highlights the degradation of high molecular weight PAH (HMW-PAHs): Benz (a) anthracene (BAA), Dibenz (a, h) anthracene (DBA), and Indeno pyrene (IND) by Aspergillus terricola var americanus. The metabolism of the HMW-PAHs by this fungus was investigated in liquid submerged culture added with 60 mg/L of each compound. Depletion of BAA, DBA, and IND was 94.80, 90.16, and 93.80%, respectively, after 10 days of culture. Fungal broth solvent extracts were analyzed for the presence of metabolites by gas chromatography mass spectrometry and the extracellular enzymes produced were also assayed. The coexistence of two metabolic pathways, cytochrome P450 monooxygenase and ligninolytic pathway were identified. A high laccase activity was observed in BAA cultures on day 4 when compared to other PAHs studied. In conclusion, A. terricola might be a promising fungus for bioremediation of HMW-PAH mixtures co-metabolically.

A Study on the Delineation of Coral Reefs in Andaman and Lakshadweep Islands Using RISAT-1 Data

Coral reefs are one of the most diverse of all marine ecosystems and are often referred to as the “rainforests of the sea”. Though they cover less than one per cent of Earth’s surface, they are home to one quarter of all ocean species by providing food and shelter to them. Optical remote sensing has been widely employed for mapping and monitoring coral reefs. But the application of microwave remote sensing has been an alternate domain in this area. This study explores the possibility of utilizing synthetic aperture radar (SAR) data of Radar Imaging Satellite-I, India’s first indigenous microwave satellite to delineate the coral reefs in Andaman and Lakshadweep Islands in the Indian Ocean. The dual polarized data, after reducing the speckle has been classified to delineate the coral reefs in the vicinity of both islands. SAR has a performance comparable with passive optical sensors under favourable conditions of imaging, viz. optimum tidal current and surface winds. The study results are compared with the international coral reef reference map and are found to be highly promising, with an overall accuracy of 98.3% and a Kappa coefficient of 0.944 for fringing reefs in Andaman region. For the atolls in Lakshadweep region, the overall accuracy is found to be 92.99% and the Kappa coefficient is estimated at 0.7377. This study tries to explore a different horizon for microwave remote sensing in coral reef studies. It is seen that, optical and microwave remote sensing can provide a mutually supporting platform in coral reef delineation, in terms of imaging depth as well as climatic conditions.

High Spatial and Spectral Details Retention Fusion and Evaluation

To retain spatial and spectral details simultaneously from source images is a trade-off in image sharpening. Fourier and wavelet transform based image fusion methods retain better spectral quality but represent less spatial details as in source images. Wavelets and Laplacian pyramid perform well only at linear discontinuities because they do not consider the geometric properties of structures and do not exploit the regularity of edges. In this paper we proposed a novel image fusion method to preserve high spatial and spectral details based on the curvelet transforms. Curvelet transforms overcome the difficulty to identify the critical transient features. To retain high spatial details, finer and detailed scale coefficients of High Resolution (HR) PAN image are substituted in Low Resolution (LR) multispectral (MS) bands in the Fast Discrete Curvelet Transforms (FDCT) domain. Spectral details in the fused image are preserved by following the shape of the spectral reflectance curve of each pixel in the resample MS image. Spectral profile of the each pixel in spatially fused image is parallel to the spectral profile of the corresponding pixel in the resampled MS image. For experimental study of this method, Indian Remote Sensing (IRS) Resourcesat-1 LISS IV images are used as LR MS image and Cartosat-1 images are used as HR PAN Image. Proposed fusion method is evaluated against state of the art fusion techniques and quality measures.

Spatiotemporal Data Fusion Using Temporal High-Pass Modulation and Edge Primitives

Most spaceborne sensors have a tradeoff between high spatial and high temporal resolutions. This tradeoff limits the use of remote sensing data in various applications that require images in both the high spatial and high temporal resolutions. In this paper, we propose a novel technique to create a fine spatial and high temporal resolution images at a ground-based data processing system. Resourcesat-2 is one of the Indian Space Research Organization missions, and it carries the Linear Imaging Self-Scanning sensors (LISS III and LISS IV) and an Advanced Wide-Field Sensor (AWiFS) onboard. The spatial resolution of LISS III is 23.5 m, and that of AWiFS is 56 m. The temporal resolution of LISS III is 24 days, and that of AWiFS is five days. The proposed method creates a synthetic LISS-III image at 23.5-m spatial and five-day temporal resolutions. It is based on the subpixel relationship between a single AWiFS-LISS-III image pair, which is acquired before or after the prediction date. In temporal data composition, spurious spatial discontinuities are inevitable for land-cover type changes. These discontinuities were identified with temporal edge primitives and were smoothed with a spatial-profile-averaging method. A synthetic LISS-III image for time tk is predicted from an AWiFS image at time tk and a single AWiFS-LISS-III image pair at time t0, where t0 ∦ tk. Experimental results demonstrated that the proposed method is superior in terms of the computational efficiency and prediction accuracy with the other existing methods.

In-flight MTF measurement for ResourceSat-2 LISS-III sensor

In-flight sensor Modulation Transfer Function (MTF) can be measured using ground based targets (natural/artificial) which satisfy the basic criteria. Meeting the specific conditions all the time is practically difficult. In this paper, we have explored Bi-resolution method to measure ResourceSat (RS)-2 Linear Imaging Self Scanner (LISS)-III sensor MTF. LISS-III sensor MTF was measured for three spectral bands (B2, B3 & B4) with corresponding LISS-IV bands as reference. MTF values determined for all three data sets found to meet the specifications and their variation were within 6.1% over the mean.