Prem Chandra Pandey

Bio: Prem Chandra Pandey is an academic researcher from Shiv Nadar University. The author has contributed to research in topics: Cyclic voltammetry & Ormosil. The author has an hindex of 24, co-authored 81 publications receiving 1462 citations. Previous affiliations of Prem Chandra Pandey include Birla Institute of Technology, Mesra & Tel Aviv University.

Spatial distribution of mangrove forest species and biomass assessment using field inventory and earth observation hyperspectral data

Abstract: The objective of this research is to identify species, provide spatial distribution of the species and estimate the biomass in the mangrove Forest, Bhitarkanika India. Mangrove ecosystems play an important role in regulating carbon cycling, thus having a significant impact on global environmental change. Extensive studies have been conducted for the estimation of mangrove species identification and biomass estimation. However, estimation at a regional level with species-wise biomass distribution has been insufficiently investigated in the past because either research focuses on the species distribution or biomass assessment. Study shows that good relationship has been achieved between stem volume (field measured data) and Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from satellite image and further these two indices are employed to estimate the biomass in the study site. Three models- linear, logarithmic and polynomial (second degree) are used to estimate biomass derived from EVI and NDVI. The hyperspectral data (spatial resolution ~ 30 m) is utilised to identify ten mangrove plant species. We have prepared the spatial distribution map of these species using spectral angle mapper. We have also generated mangrove species-wise biomass distribution map of the study site along with areal coverage of each species. The results indicate that the Sonneratia apetala Buch.-Ham. and Cynometra iripa Kostel has the highest biomass among all ten identified species, 643.12 Mg ha−1 and 652.14 Mg ha−1. Our study provided a positive relationship between NDVI, EVI, and the estimated biomass of Bhitarkanika Forest Reserve Odisha India. The study finds a similar results for both NDVI and EVI derived biomass, while linear regression has more significant results than the polynomial (second degree) and logarithmic regression derived biomass. The polynomial is found slightly better than the logarithmic when using the EVI as compared to NDVI derived biomass. The spatial distribution of species-wise biomass map obtained in this study using both, EVI and NDVI could be used to provide useful information for biodiversity assessment along with the sustainable solutions to different problems associated with the mangrove forest biodiversity. Thus, biomass assessment of larger regions can be achieved by utilization of remote sensing based indices as concluded in the present study.

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment.

Abstract: This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.

Geospatial Strategy for Tropical Forest-Wildlife Reserve Biomass Estimation

Abstract: This study focus on the biomass estimation of Sariska Wildlife Reserve using forest inventory and geospatial approaches to develop a model based on the statistical correlation between biomass measured at plot level and the associated spectral characteristics. The multistage statistical technique with incorporated the satellite data of IRS P-6 LISS III gives a precise estimation of biomass. Forest cover, forest stratum, and biomass maps were generated in the study. Spectral signatures along with tonal and textural variations were used to classify different forest types validated with GPS and ground truth data. Altitude dependent vegetation and contour information from toposheets were also considered while classifying imagery during interpretation. Sample plots were laid in study area with 0.1 ha area at intersect of the diagonals of the plots. DBH and height of all the trees inside the plot were measured and converted to biomass using volumetric equations depending upon specific gravity. The specific gravity of each tree species differ from each other and sometimes unique in different regions and varies from forest type of different regions. Estimation of tree biomass can serve as useful benchmark for future studies in related areas. Linear equation obtained was used as the model to generate final biomass map where predicted and estimated biomass were compared for each band of the satellite imageries. Linear, logarithm and power exponential models were compared to each other for correlation coefficient. Correlation between estimated and predicted AGB is 0.835 and coefficient of determination (r2) value is 0.698.

A novel ferrocene encapsulated palladium-linked ormosil-based electrocatalytic dopamine biosensor

Abstract: A novel finding on the development of electrocatalytic biosensor for dopamine is reported. The new electrocatalytic dopamine biosensor is developed using ferrocene encapsulated palladium (Pd)-linked organically-modified sol–gel glass (ormosil). The alkoxy precursors used for the preparation of new ormosil-based electrocatalytic biosensor are palladium-linked glycidoxypropyltrimethoxysilane and trimethoxysilane. The optimum concentrations of these precursors are added in aqueous solution of ferrocene monocarboxylic acid and HCl followed by gelation for 30 h at 25°C to form ormosil. The ferrocene encapsulated ormosil is characterized based on cyclic voltammetric measurements. The CV results shows peak separation of 57–59 mV and a linear relation between peak current and square root of scan rate suggesting well behaved reversible electrochemistry of ormosil encapsulated ferrocene. The CV results and the detection of ferrocene in working medium shows that ferrocene is not leached out of ormosil matrix. The tyrosinase is immobilized within polyvinyl alcohol over the ferrocene encapsulated new ormosil and finally mounted using nucleopore membrane. The electrocatalytic response of immobilized tyrosinase over new ormosil is observed and the results are reported. The performance, stability, and reproducibility of new ormosil-based dopamine biosensor are reported.

Gold nanoparticles in chemical and biological sensing.

Abstract: Detection of chemical and biological agents plays a fundamental role in biomedical, forensic and environmental sciences1–4 as well as in anti bioterrorism applications.5–7 The development of highly sensitive, cost effective, miniature sensors is therefore in high demand which requires advanced technology coupled with fundamental knowledge in chemistry, biology and material sciences.8–13 In general, sensors feature two functional components: a recognition element to provide selective/specific binding with the target analytes and a transducer component for signaling the binding event. An efficient sensor relies heavily on these two essential components for the recognition process in terms of response time, signal to noise (S/N) ratio, selectivity and limits of detection (LOD).14,15 Therefore, designing sensors with higher efficacy depends on the development of novel materials to improve both the recognition and transduction processes. Nanomaterials feature unique physicochemical properties that can be of great utility in creating new recognition and transduction processes for chemical and biological sensors15–27 as well as improving the S/N ratio by miniaturization of the sensor elements.28 Gold nanoparticles (AuNPs) possess distinct physical and chemical attributes that make them excellent scaffolds for the fabrication of novel chemical and biological sensors (Figure 1).29–36 First, AuNPs can be synthesized in a straightforward manner and can be made highly stable. Second, they possess unique optoelectronic properties. Third, they provide high surface-to-volume ratio with excellent biocompatibility using appropriate ligands.30 Fourth, these properties of AuNPs can be readily tuned varying their size, shape and the surrounding chemical environment. For example, the binding event between recognition element and the analyte can alter physicochemical properties of transducer AuNPs, such as plasmon resonance absorption, conductivity, redox behavior, etc. that in turn can generate a detectable response signal. Finally, AuNPs offer a suitable platform for multi-functionalization with a wide range of organic or biological ligands for the selective binding and detection of small molecules and biological targets.30–32,36 Each of these attributes of AuNPs has allowed researchers to develop novel sensing strategies with improved sensitivity, stability and selectivity. In the last decade of research, the advent of AuNP as a sensory element provided us a broad spectrum of innovative approaches for the detection of metal ions, small molecules, proteins, nucleic acids, malignant cells, etc. in a rapid and efficient manner.37 Figure 1 Physical properties of AuNPs and schematic illustration of an AuNP-based detection system. In this current review, we have highlighted the several synthetic routes and properties of AuNPs that make them excellent probes for different sensing strategies. Furthermore, we will discuss various sensing strategies and major advances in the last two decades of research utilizing AuNPs in the detection of variety of target analytes including metal ions, organic molecules, proteins, nucleic acids, and microorganisms.

Remote Sensing And Image Interpretation

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