2024
Permanent URI for this collectionhttps://dl.bhu.ac.in/bhuir/handle/123456789/36736
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PublicationArticle Fusion of Optical and SAR Data Using Three Approaches for the Estimation of LAI With Modified Integral Equation Model(Institute of Electrical and Electronics Engineers Inc., 2024) Shubham Kumar Singh; Rajendra Prasad; Suraj A. Yadav; Prashant K. Srivastava; Gulab Singh; Hari Shanker SrivastavaThis research article presents a comprehensive investigation of leaf area index (LAI) estimation using Sentinel- 1 synthetic aperture radar (SAR) and Sentinel-2 Optical L2A datasets for the wheat crop. The water cloud model (WCM) and PROSAIL radiative transfer models (RTMs) are used to estimate LAI from SAR and optical data, respectively. To model the surface backscattering in WCM, the integral equation model (IEM) at VV and VH polarizations is used with the Gaussian correlation function. The results demonstrate that LAI derived from SAR at VH polarization (R2 = 0.72, RMSE = 0.60 m2m?2) exhibits superior accuracy compared with optical LAI (R2 = 0.70, RMSE = 0.82 m2m?2). A fusion approach incorporating deep learning, principal component analysis (PCA), and nonlinear regression techniques is applied to fuse the SAR and optical datasets to further enhance LAI estimation accuracy. The accuracy of these estimations is tested against the ground-truth LAI taken at different locations. Among the fusion methods tested, deep learning emerges as the most effective and accurate approach (R2 = 0.91, RMSE = 0.38 m2m?2). This study provides valuable insights into the estimation of LAI using multisource remote sensing data and highlights the potential of deep learning for improved accuracy in fusion applicationss. © 2024 IEEE.PublicationBook Chapter Exploring aquatic environments through geographical information science: A comprehensive review and applications(Elsevier, 2024) Smrutisikha Mohanty; Md Wasim; Prem C. Pandey; Prashant K. SrivastavaIn recent years, environmental monitoring become a topic of discussion due to the rapid increase in anthropogenic activities and natural calamities. Monitoring is important to assess the environmental condition and maintains the ecological balance at regional and global levels. The present study focuses on the role of geographical information system (GIS) in water resource and coastal environment monitoring. GIS techniques have proved to be an effective tool for monitoring, analyzing, and mapping the various aspects related to environmental issues such as ground water potential mapping, flood risk assessment, water quality assessment, shoreline changes, coastal geomorphological and habitat mapping. GIS-based fuzzy, analytical hierarchy process (AHP), frequency ratio (FR), weighted overly (WO), spatial interpolation methods, machine learning, and artificial neural network (ANN) are widely used by researchers to prepare a decision system for environmental management. In future, the integration of GIS software with statistical methods may help to analyze the spatiotemporal data at broader level, thus enabling the researchers to produce more precise outcome. © 2024 Elsevier Inc. All rights reserved.PublicationBook Chapter Exploring the effect of the first lockdown due to covid-19 to atmospheric NO2 using Sentinel 5P satellite data, Google Earth Engine and Geographic Information Systems(Elsevier, 2024) Georgios Gkatzios; George P. Petropoulos; Spyridon E. Detsikas; Prashant K. SrivastavaAir pollution is a phenomenon that plagues modern societies, causing serious impacts on both the natural and man-made environment. Air pollution is linked to specific substances which, when their concentration exceeds certain limits, become harmful and are called pollutants. Such pollutants include carbon monoxide (CO) and carbon dioxide (CO2), particulate matter (PM10), nitrogen oxides (NOX), ozone (O3), and sulfur dioxide (SO2). Fluctuations in pollutant emissions are affected by various events. An example is the first lockdown implemented on March 23, 2020 as a result of the Covid-19 disease in an effort to protect citizens. The period of lockdown was characterized by the complete suspension of various types of activities, the reduction in transport means, as well as the decrease in industrial operations, activities that significantly contribute to increased emissions. The aim of the present study is to determine the distribution and changes in the concentration specifically of nitrogen dioxide (NO2) in the prefecture of Thessaloniki, Greece. The study period is defined as the corresponding time period 04 May–04 April 2019/2020, that is, one year before and during the first lockdown. More specifically, the correlation between the lockdown and atmospheric NO2 is investigated. As part of the analysis, area characteristics such as population density and land uses are also correlated with the distribution of NO2 concentrations. To satisfy the study objectives, the technologies of satellite remote sensing and Geographic Information Systems (GIS), which are a major pillar of geoinformatics, are used. More specifically, data recording NO2 concentrations are used, which have been collected via the Sentinel 5P satellite. Based on the results obtained, it is found that the month of 2020 during which the lockdown was applied showed a very small decrease in NO2 values (4.03%) compared to the corresponding month of 2019. © 2024 Elsevier Inc. All rights reserved.PublicationBook Chapter Techniques and tools for monitoring agriculture drought: A review(Elsevier, 2024) Varsha Pandey; Prashant K. Srivastava; Anjali Kumari Singh; Swati Suman; Swati MauryaDrought is a global phenomenon that silently spreads and creates an insidious hazard by destabilizing the hydrological cycle over a large region. Due to increased frequency, severity, and negative impact on climate conditions, droughts have drawn worldwide attention. Real-time drought monitoring and quantification is a prerequisite to ensure the well-being of inhabitants and appropriate management of water, food, and social resources. This chapter provides a comprehensive overview of the agricultural drought and its association with other drought types and monitoring using satellite remote sensing images and various hydrological model-simulated datasets. Furthermore, a few widely used and essential indices for agricultural drought were discussed along with their importance and limitations. Usage of an advanced drought assessment platform and related case studies were also discussed. The chapter concludes with the challenges in agriculture drought monitoring and provides the roadmap for future research. © 2024 Elsevier Inc. All rights reserved.PublicationArticle Ensemble of machine learning and global circulation models coupled with geospatial databases for niche mapping of Bell Rhododendron under climate change(Taylor and Francis Ltd., 2024) K.V. Satish; Prashant K. Srivastava; Mukund Dev Behera; Mohammed Latif Khan; Srishti Gwal; Sanjeev Kumar SrivastavaHimalayan species conservation faces major challenges due to unprecedented climate change. Alpine Rhododendrons are crucial components of Himalaya, yet their vulnerability to climate change remains poorly understood. This study examines niche shifting of Rhododendron campanulatum, a keystone species of alpine treeline, under different climate change scenarios using ensemble models. The study presents extensive use of four machine learning models and three global circulation models for niche modelling. Models achieved True Skill Statistic ≥0.8, Area Under Curve ≥0.9, Cohen’s Kappa ≥0.7, and overall accuracy of ≥0.9. Results showed distribution of R. campanulatum is governed by annual temperature range, minimum temperature of coldest month and precipitation of warmest quarter. Analyses revealed niche contraction and expansion of a 3–5%. Contractions are particularly evident at lower treeline boundaries. Both upward and downward shifts are anticipated under future climatic scenarios. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.PublicationBook Chapter Challenges and Future Implications in Monitoring and Assessment of Aquatic Ecosystems(CRC Press, 2024) Smrutisikha Mohanty; Prem C. Pandey; Prashant K. Srivastava; Sanjeev Kumar SrivastavaAquatic ecosystems, encompassing freshwater and marine environments, are vital for global ecological balance and human well-being. This concluding chapter delves into the diverse classifications of aquatic ecosystems and their ecological significance, emphasizing their pivotal role in supporting biodiversity, regulating climate, and providing economic services. It discusses traditional and advanced monitoring techniques, including molecular-level monitoring with environmental DNA (eDNA), traditional in situ or lab-based experiments, and regional and global monitoring using geospatial technology consisting of remote sensing, GIS, and GNSS for providing data input and processing platform. Remote sensing, in particular, is highlighted for its ability to provide comprehensive and timely information over large spatial extents, enabling robust monitoring and assessment of aquatic ecosystems. The chapter also explores the importance of remote sensing in understanding various water quality parameters, detecting environmental changes, and assessing the impacts of climate change. Challenges associated with conventional and technological approaches to studying aquatic ecosystems are discussed, alongside recent advancements in geospatial data collection and analytics. Overall, this chapter underscores the indispensable role of remote sensing in aquatic ecosystem monitoring using derived parameters and Trophic Status Index for assessing health conditions of aquatic ecosystems. Thus, it isoffering powerful tools and techniques for sustainable management and conservation efforts. © 2025 selection and editorial matter, Prem Chandra Pandey, Prashant K. Srivastava, Sanjeev Kumar Srivastava; individual chapters, the contributors.PublicationBook Chapter Introduction to Aquatic Ecosystems - Editorial Message(CRC Press, 2024) Prem Chandra Pandey; Prashant K. Srivastava; Sanjeev Kumar SrivastavaThis editorial chapter provides a comprehensive view of the edited book Aquatic Ecosystems Monitoring: Conventional Assessment to Advanced Remote Sensing. In today’s dynamic world, understanding and preserving aquatic ecosystems have become more critical than ever. The health of these ecosystems directly impacts the well-being of both the environment and human societies. Therefore, it is imperative to employ effective monitoring techniques to assess the status of aquatic environments accurately. This comprehensive volume delves into the spectrum of aquatic ecosystems, and their monitoring techniques, ranging from traditional methodologies to the latest advancements in technology. Through the collaborative efforts of early career researchers to esteemed authors/experts in the field, this collection offers a profound exploration of the diverse methods used for assessing and understanding aquatic ecosystems. From the serene depths of freshwater lakes to the expansive realms of the coastal zones, aquatic environments harbor an incredible array of life forms and ecological processes. However, these fragile and delicate ecosystems face myriad threats, including pollution, habitat destruction, climate change, and invasive species. Effective monitoring serves as a cornerstone in our efforts to safeguard these invaluable resources for future generations. This chapter provides a depth of insight into different aspects of monitoring aquatic ecosystems and the methods incorporated accordingly to utilize resources in a sustainable way. © 2025 selection and editorial matter, Prem Chandra Pandey, Prashant K. Srivastava, Sanjeev Kumar Srivastava; individual chapters, the contributors.PublicationBook Aquatic Ecosystems Monitoring: Conventional Assessment to Advanced Remote Sensing(CRC Press, 2024) Prem Chandra Pandey; Prashant K. Srivastava; Sanjeev Kumar SrivastavaThis book collates traditional and modern applications of remote sensing in aquatic ecosystem monitoring. It covers conventional assessment methods like sampling, surveying, macroinvertebrates, and chlorophyll estimation for aquatic ecosystem health assessment. Advanced remote sensing technology provides timely spectral information for quantitative and qualitative assessment of water quality, shoreline changes, coral bleaching, and vegetation monitoring. The book covers different types of aquatic ecosystems like wetlands, rivers, lakes, saline, and the brackish lake. It also: Reviews the latest applications of remote sensing in the monitoring and assessment of aquatic ecosystems Includes traditional methods like cartography, sampling, surveying, phytoplankton assessment, river interlinking, and chlorophyll estimation Discusses the application of multi-source data and machine learning in monitoring aquatic ecosystems Discusses aquatic ecosystem management, services, threats, and sustainability Explores challenges, opportunities, and prospects of future Earth observation applications for aquatic ecosystem monitoring The book discusses space-borne, airborne, and drone geospatial data. The parts broadly cover aquatic ecosystem monitoring, vegetation management, advanced modeling practices, and challenges. It is meant for scientists, professionals, and policymakers working in environmental sciences, remote sensing, and geology. © 2025 selection and editorial matter, Prem Chandra Pandey, Prashant K. Srivastava, Sanjeev Kumar Srivastava; individual chapters, the contributors.PublicationEditorial Preface(CRC Press, 2024) Prem Chandra Pandey; Prashant K. Srivastava; Sanjeev Kumar Srivastava[No abstract available]PublicationBook Chapter Aquatic Vegetation Species Identification and Mapping Using Multisource Data-Review(CRC Press, 2024) Smrutisikha Mohanty; Prem C. Pandey; Prashant K. SrivastavaThe monitoring of aquatic vegetation is essential for aquatic life and the entire ecosystem’s health as it provides food, protects habitat, improves water quality, and absorbs nutrients. With the advancement of geospatial technologies, the spatio-temporal distribution of aquatic vegetation can be characterized and mapped. The present study provides a comprehensive review of different aquatic flora types, their importance, and the need to map these species. The current study gives collective information on how multisource data play a crucial role in identifying aquatic plants by using various satellite-based sensors, drones, and radar data. The scientometric analysis is also performed by searching the keywords related to the theme in the Scopus database, which includes a co-occurrence map, a thematic map, trend topic analysis, and countries’ scientific production over time. Hence, the study aims to motivate future researchers to conduct extensive analysis in this potential field. © 2025 selection and editorial matter, Prem Chandra Pandey, Prashant K. Srivastava, Sanjeev Kumar Srivastava; individual chapters, the contributors.