Manajemen Proyek

Edisi

-

ISBN/ISSN

9786230274442

Deskripsi Fisik

viii, 86 hlm.; 23 cm.

Judul Seri

-

No. Panggil

690.2 ROS m

Mapping the Deep

Edisi

-

ISBN/ISSN

9781589487888

Deskripsi Fisik

ix, 175 hlm.; 23 cm.

Judul Seri

-

No. Panggil

551.46 WRI m

Pemrosesan Interferometric Synthetic Aperture Radar (InSAR) untuk Eksplorasi …

Edisi

-

ISBN/ISSN

9786232972636

Deskripsi Fisik

xvi, 82 hlm; 25 cm.

Judul Seri

-

No. Panggil

621.3678 ASE p

Microstructural Investigation of Variscan Late-Collisional Granitoids (Asinar…

In the framework of the geological mapping of sheet “n. 425—Asinara Island” (NW Sardinia, Italy) of the Italian National Geological Mapping Project (CARG Project), three late- to post-collisional Variscan intrusive units are recognized: (i) Castellaccio Unit; (ii) Punta Sabina Unit; and (iii) sheeted dyke complex. Granitoid rocks from these intrusive units intruded into the medium- to hig…

Earthquake Damage Susceptibility Analysis in Barapani Shear Zone Using InSAR,…

The identification of areas that are susceptible to damage due to earthquakes is of utmost importance in tectonically active regions like Northeast India. This may provide valuable inputs for seismic hazard analysis; however, it poses significant challenges. The present study emphasized the integration of Interferometric Synthetic Aperture Radar (InSAR) deformation rates with conventional geolo…

Contribution of multispectral (optical and radar) satellite images to the cla…

The monitoring of different crops (cultivated plots) and types of surface (bare soils, etc.) is a crucial economic and environmental issue for the management of resources and human activity. In this context, the objective of this study is to evaluate the contribution of multispectral satellite imagery (optical and radar) to land use and land cover classification. Object-oriented supervised cla…

Rapid mapping of landslides using satellite SAR imagery: A progressive learni…

Rapid detection of landslides after an exceptional event is critical for planning effective disaster management. Previous works have typically used machine learning-based methods, including the recently popular deep-learning approaches, to identify characteristics surface features from satellite remote sensing data, especially from optical images. However, data acquisition from optical images i…

Integration of multi-temporal SAR data and robust machine learning models for…

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…

Enhancing prediction of fluid-saturated fracture characteristics using deep l…

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…

A machine learning approach for mapping susceptibility to land subsidence cau…

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…