Remote Sensing

Theory and Applications

P. K. Garg, P. Garg

• Publisher: Mercury Learning and Information
• Year: 2024
• ISBN:
  9781501522819
• Topic: Technology & Engineering
• Subtopic: Mechanical Engineering
• Index: Technology & Engineering

This book explores the world of remote sensing technology, offering comprehensive insights into its principles, data acquisition methods, advanced processing techniques, and diverse applications. It covers the basics of remote sensingsuch as the foundational principles and data acquisition techniques, image pre-processing, such as noise removal, radiometric corrections, and image fusion, and advanced classification techniques like machine learning algorithms including neural networks and support vector machines. Finally, it discusses disaster management and agriculture, demonstrating how remote sensing methods are revolutionizing fields such as disaster response and agricultural monitoring. Professionals, researchers, and students involved in environmental sciences, geography, urban planning, and disaster management will benefit from these topics. FEATURES:

• Explores cutting-edge advanced classification techniques like machine learning algorithms including neural networks and support vector machines
• Covers both the theoretical principles and also practical data acquisition techniques, image pre-processing, noise removal, radiometric corrections, and image fusion
• Demonstrates how remote sensing methods are revolutionizing fields such as disaster response and agricultural monitoring
• Includes companion files for downloading with full color images from the text

Table of contents

• Cover page
• Half-Title page
• License and Disclaimer
• Title page
• Copyright
• Dedication
• Contents
• Preface
• Abbreviations
• Chapter 1 Basics of Remote Sensing
• Chapter 2 Electromagnetic Radiations and Interaction with Atmosphere
• Chapter 3 Various Remote Sensing Sensors and Data Characteristics
• Chapter 4 Various Remote Sensing Platforms
• Chapter 5 Image Preprocessing Approaches
• Chapter 6 Image Classification
• Chapter 7 State-of-Art Classification Techniques
• Chapter 8 Applications of Remote Sensing
• Chapter 9 Land Use and Land Cover Mapping and Modeling
• Chapter 10 Remote Sensing Platforms for Agricultural Applications
• Chapter 11 Disaster Monitoring and Management Using Remote Sensing Technology
• Chapter 12 Remote Sensing of Snow Cover
• Chapter 13 Feature/Object Extraction From Remote Sensing Algorithms
• Chapter 14 Applying Remote Sensing for Smart Cities
• Chapter 15 The Future of Remote Sensing
• Index