Remote Sensing: Models and Methods for Image Processing
Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standards. Dr. Schowengerdt presents an advanced unified framework and rationale that uniquely empowers the reader with the latest critical thinking skills and prerequisite knowledge needed to successfully design, develop and incorporate maintainable remote sensing solutions for real-world application. Advanced remote sensing image processing techniques such as hyperspectral image analysis, fusion of multisensor images and digital elevation model extraction from stereo imagery are discussed theoretically in terms of spectral, spatial, and geometric models. An expanded exercise section is also included at the end of each chapter allowing for the greatest level of mastery ever.
*Features a new lively discussion of the NASA EOS satellites, Terra and Aqua, and the commercial satellites IKONOS and Quickbird.
*New larger format provides additional access to 32 PAGE - FULL COLOR plate insert and improved readability
*Additional data processing algorithms help connect and enhance the collective understanding of engineering design and remotely sensed data
Why Read This Book
You should read this book if you work with airborne or satellite imagery and need a rigorous, application-oriented grounding in the physics of sensing together with practical image-processing and interpretation techniques. It ties sensor/radiometric fundamentals to common algorithmic workflows (preprocessing, enhancement, classification, multispectral/hyperspectral analysis), so you can move from raw measurements to reliable geospatial products.
Who Will Benefit
Remote-sensing engineers, image-processing practitioners, and graduate students who need to design or implement preprocessing, radiometric correction, spectral analysis, and classification workflows for satellite/airborne imagery.
Level: Intermediate — Prerequisites: Basic calculus and linear algebra, introductory signals or image-processing concepts (sampling, filtering), and a general familiarity with electromagnetic spectrum concepts; some exposure to programming or numerical environments (e.g., MATLAB or Python) is helpful but not strictly required.
Key Takeaways
- Explain the radiative-transfer basics and how sensor radiometry maps scene radiance into digital image values.
- Apply radiometric and atmospheric correction methods to make multisource imagery quantitatively comparable.
- Perform geometric correction, image registration, mosaicking, and basic georeferencing for airborne and satellite data.
- Implement multispectral and hyperspectral analysis techniques for material discrimination, classification, and target detection.
- Use image enhancement, filtering, spectral transforms, and statistical classifiers to improve interpretability and extract features.
- Assess sensor/platform tradeoffs and evaluate image quality and spatial/spectral resolution for operational applications.
Topics Covered
- 1. Introduction to Remote Sensing and the Electromagnetic Spectrum
- 2. Radiometry and the Physics of Remote Sensing
- 3. Atmospheric Effects and Correction
- 4. Sensors, Optics, and Detectors (Satellite and Airborne Platforms)
- 5. The Signal Chain: From Photons to Digital Numbers
- 6. Image Preprocessing: Radiometric and Geometric Correction
- 7. Image Enhancement and Filtering (Spatial and Spectral)
- 8. Spectral Analysis: Multispectral and Hyperspectral Methods
- 9. Image Classification and Pattern Recognition
- 10. Change Detection, Feature Extraction, and Target Detection
- 11. Data Mosaicking, GIS Integration, and Visualization
- 12. Applications and Advanced Topics (thermal, active sensors overview, special-case methods)
Languages, Platforms & Tools
How It Compares
Covers similar classroom territory to Lillesand & Kiefer and Jensen's Intro to Remote Sensing, but Schowengerdt is more focused on radiometric rigor and algorithmic image-processing workflows rather than purely interpretive or survey perspectives.
