Remote Sensing: Theory and Applications

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 sensing such 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