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Tectonic deformation along the Delhi-Haridwar Ridge revealed by InSAR observations: Preliminary results

Pasari, Sumanta (IEEE, 2021)

Ridges and fractures along the interplate boundaries influence arc morphology and earthquake rupture propagation. The space-based interferometric synthetic aperture radar (InSAR) approach has been used to investigate ...

Iterative Empirical Orthogonal Function in Gap Filling of GPS and InSAR Data

Pasari, Sumanta (IEEE, 2021)

Missing values or gaps in observational datasets are a common problem. Data gaps may lead to inaccurate inference about the underlying process. In Synthetic Aperture Radar (SAR) images, the reason could be interference ...

Application of Empirical Orthogonal Function on Geodetic Time-Series Data

Pasari, Sumanta (IEEE, 2021)

Growing amount of geodetic data through sophisticated data collection techniques in recent times has led to substantial challenges in data analysis and interpretation. The empirical orthogonal function (EOF), commonly known ...

Use of Shannon Information Entropy in Earthquake Nowcasting

Pasari, Sumanta (IEEE, 2021)

Earthquake nowcasting uses cumulative counts of interevent small earthquakes (say, 3.0≤M<6.0) between successive large earthquakes (M≥6.0) to estimate the current dynamic state of a geological fault system. As Shannon ...

Hyperspectral Image Clustering Using Nearest Neighbor

Pasari, Sumanta (IEEE, 2021)

Clustering of hyperspectral images is a challenging task due to the high spectral resolution and the presence of elaborate spatial structures in the data. In this study, a new clustering framework for hyperspectral imagery ...

Wind Speed Prediction with Spatio Temporal Correlation using Convolutional and Spiking Neural Networks

Pasari, Sumanta (IEEE, 2022)

Due to inherent intermittency, reliable wind speed prediction with space-time correlation is a crucial task for several practical applications, including grid operation and energy trading. This paper aims to address this ...

Hierarchical Classification using Neighbourhood Exploration for Sparse Text Tweets

Pasari, Sumanta; Tiwari, Kamlesh (IEEE, 2022)

Twitter has grown into a vast network of small informal text, and navigating it often becomes difficult for us. Here, we explore Natural Language Processing (NLP) approaches to make the topic classification of tweets easier. ...

Synthetic Aperture Radar Interferometry to Measure Earthquake-Related Deformation: A Case Study from Nepal

Pasari, Sumanta (Springer, 2022-02)

The Himalayan syntax is located at the collision boundary of the Indian and the Eurasian plates form an arc that extends ~2400 km across the continent, starting from the Kashmir Himalaya to Northeast India. Due to this ...

Estimation of Current Earthquake Hazard Through Nowcasting Method

Pasari, Sumanta (Springer, 2022)

In several tectonically active regions of the world, large magnitude earthquakes on fault systems are observed to occur in near-repetitive cycles as a consequence of stress accumulation and moment release. Since absolute ...

Earthquake Forecasting in the Himalayas Artificial Neural Networks

Pasari, Sumanta (Springer, 2022)

Earthquake is a natural phenomenon that causes huge loss in both life and property. Improvement of seismic hazard assessment requires integrated techniques such as geodetic, stochastic, and machine learning models. Forecasting ...

Effectiveness of PNL technique in disaster damage assessment: evidence from selective case studies

Pasari, Sumanta (IOP, 2022-06)

Natural disasters often cause large scale infrastructural damage and disruption of services. In such cases, a rapid damage assessment technique might prove beneficial to assist the disaster management efforts. Percent of ...

InSAR Data Analysis using Deep Neural Networks

Pasari, Sumanta (IOP, 2022-06)

Among all natural disasters, earthquakes cause the most severe devastation to both infrastructure as well as human lives. The pattern of surface deformation from satellite-based measures, such as interferometric synthetic ...

Impact of directional effect of strong ground motion on scenario-based earthquake hazards: preliminary results

Pasari, Sumanta (IOP, 2022)

Scenario-based earthquake hazards are useful for social planning and disaster mitigation. In this study, general attenuation properties of earthquake events are analysed empirically with respect to the direction of seismic ...

Earthquake Prediction Using Deep Neural Networks

Pasari, Sumanta (IEEE, 2022)

Reliable prediction of earthquakes has numerous societal and engineering benefits. In recent years, the exponentially rising volume of seismic data has led to the development of several automatic earthquake detection ...

Use of Spatio-temporal Features for Earthquake Forecasting of imbalanced Data

Pasari, Sumanta (IEEE, 2022)

With improvement in instrumentation to precisely record seismic activities, the quality of seismic data is improving day by day, leading to more informative data sets. These data sets possess temporal and geospatial patterns ...

Statistical Analysis and Forecasting of Wind Speed

Pasari, Sumanta (IEEE, 2022)

Energy plays a vital role in urbanization and industrialization. Wind energy is highly valuable and accurate forecasts can help determine the best locations to set up windmills. Using a dataset comprising wind speeds from ...

Earthquake Magnitude Prediction in Chile Using Neural Network

Pasari, Sumanta (IEEE, 2022)

In this study, we implement an earthquake magnitude prediction model using a neural network for a test region in Chile. For this, the epicenter of earthquake is located on a mesh with dimensions of 1°×1°. We adopt a zonation ...

Prediction of Solar Energy using Time Series Methods

Pasari, Sumanta (IEEE, 2022)

The utilization of solar energy as a source of electricity is increasing day by day, raising interest in prediction of solar irradiation. A successful integration of solar energy sources with existing grid system is the ...

Application of Window Sliding ARIMA in Wind Speed and Solar Irradiance Forecasting

Pasari, Sumanta (IEEE, 2022)

For better management and integration of renewable energy to the existing grid system, its accurate prediction is an inevitable requirement. For such a purpose, in literature, the statistical ARIMA model is often suggested ...

Wind Speed Prediction Using Sentinel-1 OCN Products

Pasari, Sumanta (IEEE, 2023)

Assessment of wind speed is inevitable for new offshore wind farm development. The location identification of offshore wind energy plant requires careful planning and analysis of various factors, such as the distance from ...

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