Browsing by Author "Smrutisikha Mohanty"

Now showing 1 - 8 of 8

Appraisal of radiative transfer model 6SV for atmospheric correction of multispectral satellite image towards land surface temperature retrieval
(Elsevier, 2022) Prashant K. Srivastava; Nishita Jaiswal; Swati Suman; Smrutisikha Mohanty; Sharma Mona
Land surface temperature (LST) is very important parameter for broad range of applications related to weather and climate, hydrology, etc. For LST, satellite could be a very promising solution, but need to be corrected especially for atmospheric noises present in bands such as in red and near-infrared (NIR) windows. The atmospheric noises occurred due to ozone, water vapor, and aerosols cause reduction in reflectance values of red and the NIR bands which makes the normalized difference vegetation index (NDVI) values smaller than their true value. NDVI considered as an important variable for emissivity estimation and any loss in reflectance causes error in LST retrieval. In this study, for atmospheric correction of satellite image, radiative transfer model 6SV (second simulation of satellite signal in the solar spectrum-vector) was used and then the corrected image was utilized for the LST retrieval using Landsat 8 satellite thermal and visible bands. Changes in the values are found in the atmospherically corrected images of NDVI, plant fraction, emissivity, and LST as compared to the atmospherically uncorrected images. Hence, the reported approach could be a better choice for retrieval of LST due to its robust nature. © 2023 Elsevier Ltd. All rights reserved.
Aquatic Vegetation Species Identification and Mapping Using Multisource Data-Review
(CRC Press, 2024) Smrutisikha Mohanty; Prem C. Pandey; Prashant K. Srivastava
The 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.
Challenges and Future Implications in Monitoring and Assessment of Aquatic Ecosystems
(CRC Press, 2024) Smrutisikha Mohanty; Prem C. Pandey; Prashant K. Srivastava; Sanjeev Kumar Srivastava
Aquatic 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.
Earth observation applications for urban mapping and monitoring: research prospects, opportunities and challenges
(Elsevier, 2023) Aashri Chauhan; Md. Wasim; Smrutisikha Mohanty; Prem C. Pandey; Manish Pandey; Neeraj K. Maurya; Shalini Rankavat; Surya Bhushan Dubey
The significant loss of urban green spaces led to increasing Urban Heat Island (UHI) effects, environmental pollution, and other factors that have made it more difficult for societies to create healthier living conditions. The first-generation Earth Observation (EO) data like MODIS500 and GlobCover300 had less to moderate spectral and spatial resolution having limitations in the precise mapping of urban environmental variables. Monitoring and evaluating the urban environment have improved with the advancement of EO like GlobeCover30 and the Global Human Settlement Layer, which are connected to a multisensor approach, Unmanned Aerial Vehicles (UAVs) - LIDAR for 3D mapping, as well as microwave SAR applications. The present chapter offers an overview of interesting facets of urban area research that uses EO datasets directly or indirectly to address the complexity present in the urban environment for mapping and monitoring. It also offers potential future directions for creating a sustainable urban environment. It also included some case studies that demonstrate the potential of EO in mapping and monitoring urban areas, land use/land cover changes, air pollution, site suitability, road safety, urban flood monitoring, and UHI effects. © 2024 Elsevier Ltd. All rights reserved.
Exploring aquatic environments through geographical information science: A comprehensive review and applications
(Elsevier, 2024) Smrutisikha Mohanty; Md Wasim; Prem C. Pandey; Prashant K. Srivastava
In 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.
Vegetation discrimination based on chlorophyll prediction in Marshy wetland using Unmanned Aerial Vehicles
(John Wiley and Sons Ltd, 2024) Smrutisikha Mohanty; Prem C. Pandey; Prachi Singh; Vikas Dugesar; Prashant K. Srivastava
Wetlands are an integral part of our global ecosystems and play crucial roles in ecological functions such as carbon sequestration, flood mitigation, water purification, and recreational activities. The Ramsar Convention is the most significant wetland protection pact and is doing tremendous work in conserving wetlands worldwide. However, the wetlands area is still under threat due to anthropogenic activity. The current study utilized drone images, chlorophyll measurements and machine leaning to discriminate and map vegetation at marsh wetland area—the Ramsar site. The high-resolution, multispectral imagery is acquired using a drone-mounted MICAsense sensor. Eight spectral indices such as Normalized Difference Water Index (NDWI), Two-Band Algorithm (2BDA), Normalized Difference Chlorophyll Index (NDCI), Normalized Difference Vegetation Index (NDVI) Enhanced Normalized Difference Vegetation Index (ENDVI), Green Normalized Difference Vegetation Index (GNDVI), and Normalised Difference RedEdge (NDRE) were calculated on the acquired imagery in order to discriminate the different vegetation covers such as floating aquatic vegetation (FAV), open water, and other vegetations types. These include the following: Eichhornia, Nymphea, Oleracea, Paspalam, and Oryza from agriculture land at the study site. Two models (viz., the Taylor plot and the Lek Profile methods) were employed to assess the sensitivity of the spectral indices for prediction of chlorophyll and vegetation discrimination. It is inferred from both methods that NDCI was most sensitive for chlorophyll prediction of vegetation followed by NGRDI/ ENDVI/ 2BDA and NDVI for chlorophyll prediction in wetland ecosystems. Further, three machine learning algorithms, support vector machine (SVM), random forest (RF), and gradient tree boost (GTB), were utilized for classification, and the performance accuracy of GTB was found to be the highest (0.893), followed by RF (0.851) and SVM (0.723). The GTB algorithm was applied over NDCI for vegetation discrimination. The study revealed that Eichhronia sp. is abundantly present at the study site; hence, strategic management plans should be carried out for the eradication of invasive species and proper management of wetland vegetation. © 2024 John Wiley & Sons Ltd.
Wetland Species Mapping Using Advanced Technological Measurement
(John Wiley and Sons Ltd, 2024) Smrutisikha Mohanty; Prashant K. Srivastava; Prem C. Pandey; Prachi Singh; Sanjeev Srivastava
Wetlands are pivotal in supporting the natural ecosystem and maintaining biodiversity while being susceptible to anthropogenic activities and climate change. However, monitoring wetlands over a large geographical and temporal extent is challenging. Vegetation health can be considered a good indicator of wetland conditions, and measuring chlorophyll content will provide insight into vegetation health. Linking wetland species mapping from chlorophyll spectral indices to local and regional conservation strategies could improve biodiversity conservation. Here, we apply this to Keetham Lake, India, using machine learning methods (relevance vector model) and hyperspectral measurements. From 10 chlorophyll-sensitive spectral indices, we identified four as best performing, particularly for: TVI + CCCI + NDRE for calibration and NDRE + TVI for validation data. The least performing combinations were MCARI for calibration and TVI + CCCI + NDRE + MCARI for validation. Overall, we identified that NDRE + TVI was the best-performing pair of spectral indices for chlorophyll assessment and implementation in wetland species. This approach allows for precise mapping of wetland species, providing data on their extent and the area they cover. By creating a digital database, this method enables long-term monitoring of changes in wetland species' numbers and distribution, helping to assess trends of increase or decline in freshwater ecosystems. Such strategies are vital for supporting both local and global conservation efforts, offering insights for forward-looking, data-driven preservation initiatives. © 2024 John Wiley & Sons Ltd.
Wetlands contribution and linkage to support SDGs, its indicators and targets- A critical review
(John Wiley and Sons Ltd, 2024) Smrutisikha Mohanty; Prem Chandra Pandey; Manish Pandey; Prashant K. Srivastava; Chandra Shekhar Dwivedi
This study marks one of the pioneering efforts to compile comprehensive information on Ramsar sites globally. It delves into the significance of wetlands and the designation of Ramsar sites across various countries, incorporating a concise exploration of the utilization of Unmanned Aerial Vehicles (UAVs) for wetland monitoring and assessment. Additionally, the study conducts a comparative evaluation of Ramsar sites, analyzing their percentage area and overall coverage worldwide. Incorporating a Scientometric analysis utilizing the Scopus database, the study features a co-occurrence map, thematic map, thematic evolution trend, and country collaboration map. Emphasizing the interconnection between wetlands and Sustainable Development Goals (SDGs), particularly SDG6 (Clean Water & Sanitation), SDG12 (Responsible Consumption & Production), SDG13 (Climate-Action), SDG14 (Life Below Water) and SDG15 (Life on Land), the study delves into associated targets and indicators. Targets such as 6.1, 6.2, 6.3, 6.4, 6.5, 6a, 6b of SDG-6, 12.1, 12.2, 12.4 of SDG-12, and 13.2, 13.3 of SDG-13 align with wetland management and conservation. Moreover, it affirms the role of wetlands in supporting targets 14.1, 14.2, 14.3, 14.4, 14.5, 14.6, 14a-c of SDG-14, and 15.1, 15.5, 15.6, 15.7, 15.8, and 15.8 of SDG-15. Policies, regulations and management plans of different countries relevant for supporting and establishing relationship with SDGs are discussed in details. The study offers a detailed exploration of these targets, elucidating indicator types associated with each SDG target. By doing so, it provides valuable insights for future researchers and policymakers, underlining the indispensable contribution of wetlands to the direct and indirect fulfillment of SDGs 6,12,13,14,15 and 17. © 2024 ERP Environment and John Wiley & Sons Ltd.