Remote Sensing
Theory and Applications
- Publisher
Mercury Learning and Information - Published
22nd May - ISBN 9781683927488
- Language English
- Pages 610 pp.
- Size 7" x 9"
- Request Exam Copy
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- Publisher
Mercury Learning and Information - Published
22nd May - ISBN 9781501522819
- Language English
- Pages 610 pp.
- Size 7" x 9"
- Request E-Exam Copy
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- Publisher
Mercury Learning and Information - Published
22nd May - ISBN 9781501522840
- Language English
- Pages 610 pp.
- Size 7" x 9"
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
1: Basics of Remote Sensing
2: Electromagnetic Radiations and Interaction with the Atmosphere
3: Various Remote Sensing Sensors and Data Characteristics
4: Various Remote Sensing Platforms
5: Image Pre-processing Approaches
6: Image Classification
7: The State-of-the-Art Classification Techniques
8: Applications of Remote Sensing
9: Land Use and Land Cover Mapping and Modelling
10: Remote Sensing Platforms for Agricultural Applications
11: Disaster Monitoring and Management Using Remote Sensing Technology
12: Remote Sensing of Snow Cover
13: Feature/Object Extraction from Remote Sensing Algorithms
14: Applying Remote Sensing for a Smart City
15: The Future of Remote Sensing References
Index
P. K. Garg, PhD
P. K. Garg holds a PhD in remote sensing (University of Bristol) and is a professor of civil engineering, specializing in geomatics engineering. He is a member of the advisory committee of CSSTEAP (Centre for Space Science and Technology Education in Asia and the Pacific).