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Books in Computers in geosciences

1-10 of 26 results in All results

Computational Methods for Time-Series Analysis in Earth Sciences

  • 1st Edition
  • January 1, 2025
  • Silvio José Gumiere + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 3 6 3 1 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 3 6 3 2 - 4
Computational Methods for Time-Series Analysis in Earth Sciences bridges the gap between theoretical knowledge and practical application, offering a deep dive into the utilization of R programming for managing, analyzing, and forecasting time-series data within the Earth sciences. The book systematically unfolds the layers of data manipulation, graphical representation, and sampling to prepare the reader for complex analyses and predictive modeling, from the basics of signal processing to the nuances of machine learning. It presents cutting-edge techniques, such as neural networks, kernel-based methods, and evolutionary algorithms, specifically tailored to tackle challenges, and provides practical case studies to aid readers.This is a valuable resource for scientists, researchers, and students delving into the intricacies of Earth's environmental patterns and cycles through the lens of computational analysis. It guides readers through various computational approaches for deciphering spatial and temporal data.

Data Analytics and Artificial Intelligence for Earth Resource Management

  • 1st Edition
  • November 1, 2024
  • Deepak Kumar + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 3 5 9 5 - 5
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 3 5 9 6 - 2
Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity.Resource monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources.

Intelligence Systems for Earth, Environmental and Planetary Sciences

  • 1st Edition
  • July 30, 2024
  • Hossein Bonakdari + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 2 9 3 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 2 9 2 - 6
Intelligence Systems for Earth, Environmental and Planetary Sciences: Methods, Models and Applications provides cutting-edge theory and applications of modern-day artificial intelligence and data science in the Earth, environment, and planetary science fields. The book is divided into three sections: (i) Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets; (ii) Models, detailing model development, data assimilation, and techniques in each field; and (iii) Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives.Intelligence Systems for Earth, Environmental and Planetary Sciences will be of interest to students, academics, and postgraduate professionals in the field of applied sciences, Earth, environmental, and planetary sciences and would also serve as an excellent companion resource to courses studying artificial intelligence applications for theoretical and practical studies in Earth, environmental, and planetary sciences.

Advances in Machine Learning and Image Analysis for GeoAI

  • 1st Edition
  • April 3, 2024
  • Saurabh Prasad + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 9 0 7 7 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 9 0 7 8 - 0
Advances in Machine Learning and Image Analysis for GeoAI presents recent advances in applications and algorithms that are at the intersection of Geospatial imaging and Artificial Intelligence (GeoAI). The book covers algorithmic advances in geospatial image analysis, sensor fusion across modalities, few-shot open-set recognition, explainable AI for Earth Observations, self-supervised learning, image superresolution, Visual Question Answering, and spectral unmixing, among other topics. This book offers a comprehensive resource for graduate students, researchers, and practitioners in the area of geospatial image analysis. It provides detailed descriptions of the latest techniques, best practices, and insights essential for implementing deep learning strategies in GeoAI research and applications.

Machine Learning in Earth, Environmental and Planetary Sciences

  • 1st Edition
  • June 27, 2023
  • Hossein Bonakdari + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 2 8 4 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 2 8 5 - 6
Machine Learning in Earth, Environmental and Planetary Sciences: Theoretical and Practical Applications is a practical guide on implementing different variety of extreme learning machine algorithms to Earth and environmental data. The book provides guided examples using real-world data for numerous novel and mathematically detailed machine learning techniques that can be applied in Earth, environmental, and planetary sciences, including detailed MATLAB coding coupled with line-by-line descriptions of the advantages and limitations of each method. The book also presents common postprocessing techniques required for correct data interpretation. This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results.

Geoinformatics for Geosciences

  • 1st Edition
  • May 26, 2023
  • Nikolaos Stathopoulos + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 8 9 8 3 - 1
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 5 7 8 2 - 3
Geoinformatics for Geosciences: Advanced Geospatial Analysis using RS, GIS and Soft Computing is a comprehensive guide to the methodologies and techniques that can be used in Earth observation data assessments, geospatial analysis, and soft computing in the geosciences. The book covers a variety of spatiotemporal problems and topics in the areas of the environment, geohazards, urban analysis, health, pollution, climate change, resources and geomorphology, among others. Sections cover environmental and climate issues, analysis of geomorphological data, hazard and disaster impacts, natural and human resources, the influence of environmental conditions, geohazards, climate change, geomorphological changes, etc., and socioeconomic challenges. Detailing up-to-date techniques in geoinformatics, this book offers in-depth, up-to-date methodologies for researchers and academics to understand how contemporary data can be combined with innovative techniques and tools in order to address challenges in the geosciences.

Case Studies in Geospatial Applications to Groundwater Resources

  • 1st Edition
  • October 21, 2022
  • Pravat Kumar Shit + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 9 9 6 3 - 2
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 9 9 6 4 - 9
Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner.

Advances in Subsurface Data Analytics

  • 1st Edition
  • May 18, 2022
  • Shuvajit Bhattacharya + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 2 9 5 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 2 3 0 8 - 6
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume.

Computers in Earth and Environmental Sciences

  • 1st Edition
  • September 22, 2021
  • Hamid Reza Pourghasemi
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 8 9 8 6 1 - 4
  • eBook
    9 7 8 - 0 - 3 2 3 - 8 8 6 1 5 - 4
Computers in Earth and Environmental Sciences: Artificial Intelligence and Advanced Technologies in Hazards and Risk Management addresses the need for a comprehensive book that focuses on multi-hazard assessments, natural and manmade hazards, and risk management using new methods and technologies that employ GIS, artificial intelligence, spatial modeling, machine learning tools and meta-heuristic techniques. The book is clearly organized into four parts that cover natural hazards, environmental hazards, advanced tools and technologies in risk management, and future challenges in computer applications to hazards and risk management. Researchers and professionals in Earth and Environmental Science who require the latest technologies and advances in hazards, remote sensing, geosciences, spatial modeling and machine learning will find this book to be an invaluable source of information on the latest tools and technologies available.

Knowledge Discovery in Big Data from Astronomy and Earth Observation

  • 1st Edition
  • April 9, 2020
  • Petr Skoda + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 9 1 5 4 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 9 1 5 5 - 2
Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.