A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

Solar X-ray Monitor (XSM) on-board Chandrayaan-2 orbiter

The remote X-ray fluorescence spectroscopy is a powerful technique to investigate the elemental abundances in the atmosphere-less planetary bodies. The experiment involves measuring spectra of fluorescent X-rays from lunar surface using a low energy X-ray detector onboard an orbiting satellite. Since the flux of fluorescent X-ray lines critically depend on the flux and spectrum of the incident solar X-rays, it is essential to have simultaneous and accurate measurement of X-ray from both Moon and Sun. In the context of Moon, this technique has been employed since early days of space exploration to determine elemental composition of lunar surface. However, so far it has not been possible to exploit it to its full potential due to various reasons. Therefore it is planned to continue the remote X-ray fluorescence spectroscopy experiment on-board Chandrayaan-2 which includes both lunar X-ray observations and solar X-ray observations as two separate payloads. The lunar X-ray observations will be carried out by Chandra Large Area Soft x-ray Spectrometer (CLASS) experiment; whereas the solar X-ray observations will be carried out by a separate payload, Solar X-ray Monitor (XSM). Here we present the overall design of the XSM instrument, the present development status as well as preliminary results of the laboratory model testing. XSM instrument will have two packages namely – XSM sensor package and XSM electronics package. XSM will accurately measure spectrum of Solar X-rays in the energy range of 1–15 keV with energy resolution ∼200 eV @ 5.9 keV. This will be achieved by using state-of-the-art Silicon Drift Detector (SDD), which has a unique capability of maintaining high energy resolution at very high incident count rate expected from Solar X-rays. XSM onboard Chandrayaan-2 will be the first experiment to use such detector for Solar X-ray monitoring.     

Novel method for reconstruction of hyperspectral resolution images from multispectral data for complex coastal and inland waters

Hyperspectral resolution image products of a synthetic sensor featuring the high spatial resolution of the space-borne sensor can offer cost-effective means for enhancing our current capabilities in terms of providing an array of images in lieu of designing an expensive system for image acquisition, which can serve the expanding needs of the scientific and user communities for various critical water color applications. Despite several studies on enhancing the capability of land remote sensing sensors, full spectrum reconstruction of water color images with varying spectral bands is hampered by the lack of methods and accurate atmospheric correction procedures. In the present work, a novel method is developed for reconstruction of hyperspectral resolution images from high spatial-resolution Sentinel 2 Multispectral Instrument (MSI) data representative of many complex waters in coastal and inland zones. This method uses a deep neural network (DNN) with multiple blocks of deconvolution and dense layers. The spectral reconstruction of hyperspectral resolution images from multispectral data was based on rigorous training data from the atmospherically-corrected and validated HICO normalized water-leaving radiance products (with spectral resolution 438-868 nm sampled at 5.7 nm) of diverse water types. The generalizability and versatility of the DNN method was tested and evaluated systematically by means of various qualitative and quantitative analyses using concurrent space-borne (MSI and HICO) and in-situ measurements from different regional waters. Reconstructed hyperspectral resolution radiances obtained from the MSI images closely matched with independent HICO and MSI measurements within the desired accuracy. Successful reconstruction and validation of the hyperspectral radiances indicate that the proposed state-of-the-art method provides possible future directions for enhancing our current capabilities of space-borne sensors for various research purposes and societal applications at local, regional and global scales.     

Alpha Particle X-Ray Spectrometer (APXS) on-board Chandrayaan-2 rover

Alpha Particle X-ray Spectrometer (APXS) payload configuration for Chandrayaan-2 rover has been completed recently and fabrication of mechanical assembly, PCB layout design and fabrication are in progress. Here we present the design and performance evaluation of various subsystems developed for APXS payload. The low energy threshold of <1 keV and the energy resolution of ∼150 eV at 5.9 keV, for the Silicon Drift Detector (SDD), as measured from the developed APXS electronics is comparable to the standard spectrometers available off-the-shelf. We have also carried out experiments for measuring fluorescent X-ray spectrum from various standard samples from the USGS catalog irradiated by the laboratory X-ray source ²⁴¹Am with 1 mCi activity. It is shown that intensities of various characteristic X-ray lines are well correlated with the respective elemental concentrations.     

Estimation of sediment settling velocity in estuarine and coastal waters using optical remote sensing data

A robust method has been developed for estimating sediment settling velocity (w_s) from high resolution optical remote sensing data in estuarine, coastal and harbor waters. This method estimates settling velocity as a function of the drag coefficient (C_d), Reynolds number (Re), grain size (D₅₀), specific gravity (Δ_SG) and grain shape (in terms of the Corey Shape Factor – CSF). These parameters were derived from the particulate inherent optical properties such as backscattering (b_bp), beam attenuation (c_p), suspended sediment concentration and turbidity using Landsat 8 OLI and HICO data. Preliminary results for the Gulf of Cambay in the eastern Arabian Sea and Yangtze river estuary in the East China Sea, showed that satellite-retrieved settling velocities (m?s^?1) varied from very low values in clear oceanic waters, intermediate values in coastal waters, to very high values in river plumes and sediment-laden coastal waters. The remote sensing retrievals of sediment properties and their settling velocities were generally consistent with the field and laboratory results, which indicate that the proposed methodology will have important implications in various coastal engineering, environmental and management studies.     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.     

Hard X-ray continuum from lunar surface: Results from High Energy X-ray spectrometer (HEX) onboard Chandrayaan-1

The High Energy X-ray spectrometer (HEX) on Chandrayaan-1 was designed to study the photon emission in the range of 30–270 keV from naturally occurring radioactive decay of ²³⁸U and ²³²Th series nuclides from the lunar surface. The primary objective of HEX was to study the transport of volatiles on the lunar surface using radon as a tracer and mapping the 46.5 keV line from ²¹⁰Pb, a decay product of ²²²Rn. HEX was tested for two days during the commissioning phase of Chandrayaan-1 and performance of all sub systems was found to be as expected. HEX started collecting science data during the first non-prime imaging season (February–April, 2009) of Chandrayaan-1. Certain anomalies persisted in this data set and the early curtailment of Chandrayaan-1 mission in August, 2009, did not allow any further operation of HEX. Despite these issues, HEX provided the first data set for 30–270 keV continuum emission, averaged over a significant portion of the lunar surface, including the polar region.