Fundamentals and Advances in Remote Sensing

From Principles to AI Applications

Häftad, Engelska, 2027

1 776 kr

Kommande

Beskrivning

Fundamentals and Advances in Remote Sensing: From Principles to AI Applications is an essential scientific reference for researchers, students, and professionals in geospatial sciences. It addresses the need to combine traditional remote sensing principles with modern AI-driven methods. Covering sensor technologies, image calibration, classification, semantic segmentation, InSAR, and data fusion, the book offers both theoretical insights and practical workflows. It features open-source code, real-world case studies, and visual aids like flow diagrams and comparison tables to enhance understanding. The structured chapters facilitate easy navigation and application, empowering users to deploy advanced techniques confidently in environmental monitoring, urban planning, and hazard assessment. By bridging fundamental concepts with cutting-edge tools, this volume supports innovative research and operational solutions to pressing societal and environmental challenges, making it a vital resource for advancing remote sensing science and applications.

Offers open-source workflows using Python and Google Earth Engine for practical remote sensing applications
Demonstrates real-world case studies across diverse sensors including optical, SAR, and UAV data
Utilizes a modular, template-based chapter structure to enhance learning and cross-referencing
Bridges traditional remote sensing techniques with cutting-edge AI-driven methods like semantic segmentation and InSAR
Integrates visual elements such as flow diagrams, step-by-step boxes, comparison tables, and high-resolution figures for clarity

Produktinformation

Utgivningsdatum:2027-08-30
Mått:152 x 229 x undefined mm
Format:Häftad
Språk:Engelska
Antal sidor:300
Förlag:Elsevier Science
ISBN:9780443490217

Utforska kategorier

Geografi inom Naturvetenskap och teknik

Mer om författaren

Dr. Alireza Sharifi is Associate Professor of Remote Sensing within Shahid Beheshti University’s Department of Surveying Engineering, Iran. He obtained his BSc in Surveying Engineering from Azad University and his MSc and PhD in Remote Sensing Engineering from the University of Tehran, Iran. He brings more than 15 years of experience in the applications of remote sensing and artificial intelligence to landscape biomass and ecological health monitoring. Since 2016, he has operated a consulting business delivering remote sensing and AI solutions for mapping, image processing, data analysis, visualization, and data management. He is a member of several scientific communities and editorial boards, including the International Committee of Space Research, the Iranian Society of Geoinformatics Artificial Intelligence, and the following journals: Spatial Information Research, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Big Data Research, Environmental Earth Sciences, and Information Science and Engineering.

Innehållsförteckning

Part I: Foundations of Remote Sensing 1. Introduction to Remote Sensing 2. Electromagnetic Spectrum and Sensor Technology 3. Image Preprocessing and Calibration Part II: Core Analytical Methods 4. Classification Techniques in Remote Sensing 5. Change Detection and Time-Series Analysis Part III: AI and Deep Learning for Remote Sensing 6. Semantic Segmentation for Land Cover and Object Detection 7. Data Labeling, Augmentation, and Transfer Learning Part IV: InSAR and 3D Earth Observation 8. Introduction to Interferometric SAR (InSAR) 9. Advanced InSAR Applications Part V: Multi-Sensor Fusion and Emerging Trends 10. Sensor Fusion Techniques 11. Cloud Platforms and Big Data Tools 12. Ethical, Legal, and Societal Impacts