The flood hazards in the southwest coastal region of India in 2018 and 2020 resulted in numerous casualties and the displacement of over a million people from their homes. In order to mitigate the loss of life and resources caused by recurrent major and minor flood events, it is imperative to develop a comprehensive spatial flood zonation map of the entire area. Therefore, the main aim of the p…
Utilization of subsurface resources is essential to achieve energy sustainability including large-scale CO sequestration, H storage, geothermal energy extraction, and hydrocarbon recovery. In-situ visualization of fluid flow in geological media is essential to understand complex, coupled, physical and chemical processes underlying fluid injection, storage, extraction. X-ray Computed Tomogra…
Land subsidence is a worldwide threat that may cause irreversible damage to the environment and the infrastructures. Thus, identifying and mapping areas prone to land subsidence with accurate methods such as Land Subsidence Susceptibility Index (LSSI) mapping is crucial for mitigating the adverse impacts of this geohazard. Also, Machine Learning (ML) is now becoming a powerful tool to analyze v…
High-resolution digital rock micro-CT images captured from a wide field of view are essential for various geosystem engineering and geoscience applications. However, the resolution of these images is often constrained by the capabilities of scanners. To overcome this limitation and achieve superior image quality, advanced deep learning techniques have been used. This study compares four differe…
The accumulation of crustal strain towards the western part of India, especially in the Kachchh Rift basin, is making one of the most seismically active parts of the Indian plate. Several strong to major earthquakes, including the recent 2001 (M7.7) Bhuj earthquake, were triggered in the Kachchh rift basin during the last two centuries. Therefore, in the present study, we have attempted to quan…
This study addresses the challenge of oil spill detection using Synthetic Aperture Radar (SAR) satellite imagery, employing deep learning techniques to improve accuracy and efficiency. We investigated the effectiveness of various neural network architectures and encoders for this task, focusing on scenarios with limited training data. The research problem centered on enhancing feature extractio…
Terrestrial Radar Interferometry (TRI) is widely adopted in geomonitoring applications due to its capability to precisely observe surface displacements along the line of sight, among other key characteristics. As its deployment grows, TRI is also increasingly used to monitor smaller and more dispersed geological phenomena, where the challenge is their precise localization in 3d space if the pos…
This paper presents Pol-InSAR-Island, the first publicly available multi-frequency Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR) dataset labeled with detailed land cover classes, which serves as a challenging benchmark dataset for land cover classification. In recent years, machine learning has become a powerful tool for remote sensing image analysis. While there are numerou…
The increased availability of satellite SAR data coupled with improved InSAR processing algorithms has led to higher accuracy of InSAR-derived displacements. However, obtaining millimeter-level accuracy still remains a challenge due to the inability to accurately model the tropospheric delay, which is sometimes larger than the actual deformation. We propose to estimate the relative daily SAR tr…
Buku ini berisi tentang teknik pemasaran digital yang mudah dan tidak membutuhkan pemahaman teknis yang tinggi dalam menerapkan strategi pemasaran digital 360 derajat. Aplikasi berbasis android yang dihasilkan juga dapat dikembangkan sendiri tanpa harus menjadi seorang programmer atau belajar pemrograman terlebih dahulu. Dengan langkah-langkah yang sistematis dan dilengkapi dengan gambar. Buk…