Browsing by Author "Rishabh Singh"

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Challenges in Radar remote sensing
(Elsevier, 2022) Prashant K. Srivastava; Rajendra Prasad; Sumit Chaudhary Kumar; Suraj A. Yadav; Jyoti Sharma; Swati Suman; Varsha Pandey; Rishabh Singh; Dileep Kumar Gupta
This chapter provides different challenges that are generally faced by the radar remote sensing community. The different types of challenges of radar remote sensing in biochemical and biophysical parameter retrieval, flood detection and monitoring, soil moisture, snow, droughts, sensor development, and instrumentation are briefly provided. © 2022 Elsevier Inc. All rights reserved.
Estimation of paddy yield with AI-based model using scatterometers
(Elsevier, 2025) Monalisa Mohapatra; Abhaya Kumar Sahu; Rishabh Singh; Ayushi Gupta
Scatterometers are specified radar instruments designed to measure the reflection of microwaves received back from the Earth's surface. Paddy is recognised as the primary food crop worldwide and accounts for up to 85% of its total global production. It is consumed as a source of carbohydrates (a high source of primary energy). This chapter provides basic knowledge related to the life cycle and remote sensing properties of paddy, which also includes the operations of scatterometers in the field of modern agricultural practices, and highlights the use of different processes to estimate paddy yield. This technology helps in the identification of backscattering and clustering properties of soil moisture content and paddy phenology (biomass, leaf area index, grain length, grain width, grain thickness, leaf length, leaf width, leaf thickness, and canopy structure). This identification is done by using the backscattering coefficient (σ°) where different models are applied. Scatterometer satellite (SCATSAT-1) (known as Ku-band-based scatterometer satellite 1) is used to measure vegetative dynamics, where the σ° of rice fields was measured at horizontal transmit-horizontal receive and vertical transmit-vertical receive polarisations. It is a dual pencil beam-based scatterometer. SCATSAT-1 is used to study the paddy crop growth at different stages with measured soil moisture content. The implementation of different AI-based software to estimate paddy yield ultimately increases the potential to revolutionise the agriculture sector by improving sustainable and effective food synthesis, monitoring crop different development stages and assisting farmers and researchers to analyse data to obtain paddy yield. By accurately forecasting rice yields, this book chapter highlights the critical role that scatterometers play in promoting sustainable agricultural methods and preserving global food safety. © 2026 Elsevier Ltd. All rights reserved..
Improvement of the “Triangle Method” for Soil Moisture Retrieval Using ECOSTRESS and Sentinel-2: Results over a Heterogeneous Agricultural Field in Northern India
(MDPI, 2022) Rishabh Singh; Prashant K. Srivastava; George P. Petropoulos; Sudhakar Shukla; Rajendra Prasad
For the purpose of deriving spatiotemporal estimates of soil moisture, the triangle method is one of the most widely used approaches today utilizing remote sensing data. Generally, those techniques are based on the physical relationships that exist when a satellite-derived land surface temperature (Ts) is plotted against a spectral vegetation index (VI). The present study proposes an improvement in the triangle method in retrieving soil moisture over heterogeneous areas. In particular, it proposes a new approach in robustly identifying the extreme points required for the technique’s implementation. Those extreme points are then used in calculating fractional vegetation cover (Fr) and scaled Ts. Furthermore, the study proposes a new approach for calculating the coefficients required to develop the relationships between surface soil moisture (SSM) and Fr/Ts, which is implemented using a model and field data. As a case study, an agricultural field in the Varanasi district in India has been used, on which the triangle method is implemented using ECOSTRESS and Sentinel-2 data. The much-improved spatial resolution satellite data of ~70 m from ECOSTRESS allowed deriving more vivid results of SSM spatial variability for the study area. Comparisons between field soil moisture calculated using the proposed method returned an RMSE of 0.03 and R2 value of 0.84, which are considered very satisfactory. The methodology proposed herein and the results obtained are of significant value with regards to the triangle method, contributing to ongoing efforts at present examining its use for operational product development at a global scale. © 2022 by the authors.
Performance of novel MgS doped cellulose nanofibres for Cd(II) removal from industrial effluent – mechanism and optimization
(Nature Publishing Group, 2019) Nalini Sankararamakrishnan; Rishabh Singh; Ila Srivastava
Green environment friendly and novel nano MgS decorated cellulose nanofibres (MgS@CNF) were prepared, characterized and evaluated towards the removal of heavy metal namely, cadmium from aqueous solutions. Cellulose nanofibres acted as a template for effective dispersion of MgS nanoparticles and also aid in the complexation of cadmium ions. In depth X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Fourier transform infra red spectroscopy (FTIR) studies revealed that doped MgS on mild acidification yields insitu production of H2S which effectively complexes cadmium ion to form cadmium sulfide. The reaction followed pseudo first order kinetics with regression coefficient in the order of 0.98. A very high Langmuir adsorption capacity in the order of 333.33 mg/g was obtained for MgS@CNF. Finally, MgS@CNF was applied towards the removal of cadmium from organic and TDS rich tannery waste water. MgS@CNF was effective in bringing down the concentration from ppm to ppb levels. © 2019, The Author(s).
Rhodanine composite fluorescence probes to detect pathological hallmarks in Alzheimer's disease models
(Elsevier B.V., 2024) Himanshu Rai; Rishabh Singh; Prahalad Singh Bharti; Prabhat Kumar; Sanskriti Rai; Tanmaykumar Varma; Brijesh Singh Chauhan; Aishwarya Srikant Nilakhe; Joy Debnath; Renu Dhingra; Vijay N. Mishra; Sarika Gupta; Sairam Krishnamurthy; Jian Yang; Prabha Garg; Saripella Srikrishna; Saroj Kumar; Gyan Modi
Amyloid fibrils and hyperphosphorylated tau tangles are widely acceptable histological and biochemical pathogenic markers in Alzheimer's Disease (AD). Detecting these markers at an early stage could be beneficial for differentiating AD from other neuronal anomalies. Herein, a series of rhodanine (acceptor) based dyes in conjugation with a coumarin or carbostyril (donor) were synthesized and tested their ability to detect these biomarkers. The lead probe 19 displayed staining affinity for Aβ fibrils and tau tangles with little or no interaction with abundant plasma protein (BSA). Minimal cytotoxicity, brain accessibility, biocompatibility, and fluorescence sustainability across physiological pHs rendering it suitable for in-vivo imaging. Dual staining of histological samples validated affinity of probe 19 for Aβ plaques and tau tangles in AD brain tissue specimens via immunofluorescence, ThT (aggregated Aβ specific dye), and Tau-1 (tau filament-specific dye). Moreover, live in-vivo fluorescence imaging in mice and ocular labeling of Aβ in AD Drosophila models extend the preclinical applicability of probe 19 for screening purposes. On behalf of the following data, we assume that probe 19 can successfully detect pathological AD biomarkers in investigational studies. © 2024 Elsevier B.V.