Название: Remote Sensing: Theory and Applications
Автор: P.K. Garg
Издательство: Mercury Learning and Information
Год: 2024
Страниц: 671
Язык: английский
Формат: epub (true)
Размер: 49.4 MB
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. Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object. It deals with the data collection of natural and man-made objects on the Earth to show their geographic locations as well as characteristics on the maps. Addressing the need for updated information in remote sensing, this book consists of two major divisions: theory covering principal topics and different applications. The book discusses the basic concept of remote sensing, remote sensing systems, processing, classification, and applications of data. In addition, it provides the latest techniques of satellite image classification, such as Artificial Neural Networks, Convolution Neural Networks, k-NN, Object-based Image Analysis, Fuzzy C-Means, Artificial Intelligence, Machine Learning, Deep Learning, Support Vector Machine, Random Forest, Decision Tree, etc., which are not only useful in accurate classification of an extraction of specific objects from images, but also developing innovative solutions.