Remote Sensing The Image Chain Approach 2nd Edition by John Schott ISBN‎ 0195178173 978-0195178173

Remote Sensing The Image Chain Approach 2nd Edition by John Schott – Ebook PDF Instant Download/Delivery: 0195178173, 978-0195178173
Full download Remote Sensing The Image Chain Approach 2nd edition after payment

Product details:

ISBN 10:‎ 0195178173
ISBN 13: 978-0195178173
Author: John Schott

Remote Sensing deals with the fundamental ideas underlying the rapidly growing field of remote sensing. John Schott explores energy-matter interaction, radiation propagation, data dissemination, and described the tools and procedures required to extract information from remotely sensed data using the image chain approach. Organizations and individuals often focus on one aspect of the remote sensing process before considering it as a whole, thus investigating unjustified effort, time, and expense to get minimal improvement. Unlike other books on the subject, Remote Sensing treats the process as a continuous flow. Schott examines the limitations obstructing the flow of information to the user, employing numerous applications of remote sensing to earth observation disciplines. For this second edition, in addition to a thorough update, there are major changes and additions, such as a much more complete treatment of spectroscopic imaging, which has matured dramatically in the last ten years, and a more rigorous treatment of image processing with an emphasis on spectral image processing algorithms. Remote Sensing is an ideal first text in remote sensing for advanced undergraduate and graduate students in the physical or engineering sciences, and will also serve as a valuable reference for practitioners. 

Remote Sensing The Image Chain Approach 2nd Table of contents:

CHAPTER 1 INTRODUCTION

1.1 WHAT IS REMOTE SENSING (AS FAR AS WE’RE CONCERNED)?

1.2 WHY REMOTE SENSING?

1.3 WHAT KINDS OF REMOTE SENSING?

1.4 THE IMAGE CHAIN APPROACH

1.5 REFERENCES

CHAPTER 2 HISTORICAL PERSPECTIVE AND PHOTO MENSURATION

2.1 PHOTO INTERPRETATION

2.2 QUANTITATIVE ANALYSIS OF AIR PHOTOS

2.2.1 Photogrammetry

2.2.2 Camera as a Radiometer

2.3 EVOLUTION OF EO SYSTEMS

2.4 SPACE-BASED EO SYSTEMS

2.5 DIGITAL CONCEPTS

2.6 REFERENCES

CHAPTER 3 RADIOMETRY AND RADIATION PROPAGATION

3.1 ENERGY PATHS

3.1.1 Solar Energy Paths

3.1.2 Thermal Energy Paths

3.2 RADIOMETRIC TERMS

3.2.1 Definition of Terms

3.2.2 Blackbody Radiators

3.2.3 Polarization Concepts

3.3 RADIOMETRIC CONCEPTS

3.3.1 Inverse-Square Law for Irradiance from a Point Source

3.3.2 Projected Area Effects (cos θ)

3.3.3 Lambertian Surfaces

3.3.4 Magic π

3.3.5 Lens Falloff

3.4 ATMOSPHERIC PROPAGATION

3.4.1 Atmospheric Absorption

3.4.2 Atmospheric Scattering

3.5 CHARACTERISTICS OF THE EM SPECTRUM

3.6 REFERENCES

CHAPTER 4 THE GOVERNING EQUATION FOR RADIANCE REACHING THE SENSOR

4.1 IRRADIANCE ONTO THE EARTH’S SURFACE

4.1.1 Solar Irradiance

4.1.2 Downwelled Radiance (Skylight)

4.1.3 Reflected Background Radiance

4.2 REFLECTED SOLAR IRRADIANCE AND BIDIRECTIONAL REFLECTANCE

4.2.1 Ways to Characterize Reflectance

4.2.2 Reflected Solar Radiance

4.3 SOLAR RADIANCE REACHING THE SENSOR

4.3.1 Solar Scattered Upwelled Radiance (Path Radiance)

4.3.2 Cumulative Solar Effects

4.3.3 Multiple Scattering and Nonlinearity Effects

4.4 THERMAL RADIANCE REACHING THE SENSOR

4.4.1 Self-Emission

4.4.2 Thermal Emission from the Sky and Background Reflected to the Sensor

4.4.3 Self-Emitted Component of Upwelled Radiance

4.5 INCORPORATION OF SENSOR SPECTRAL RESPONSE

4.6 SIMPLIFICATION OF THE BIG EQUATION AND RELATIVE MAGNITUDE ASSESSMENT

4.6.1 Simplification

4.6.2 Sensitivity Analysis—Error Propagation

4.7 REFERENCES

CHAPTER 5 SENSING SYSTEMS

5.1 CAMERAS AND FILM SYSTEMS

5.1.1 Irradiance onto the Focal Plane

5.1.2 Sensitometric Analysis

5.2 SIMILARITIES BETWEEN SIMPLE CAMERAS AND MORE EXOTIC ELECTRO-OPTICAL IMAGING SYSTEMS

5.2.1 Optics and Irradiance at the Focal Plane

5.2.2 System Characterization

5.3 DETECTORS AND SENSOR PERFORMANCE SPECIFICATIONS

5.3.1 Detector Types

5.3.2 Detector Figures of Merit

5.3.3 Sensor Performance Parameters

5.4 DETECTOR-SENSOR PERFORMANCE CALCULATIONS

5.5 REFERENCES

CHAPTER 6 IMAGING SENSORS AND INSTRUMENTICALIBRATION

6.1 SINGLE-CHANNEL AND MULTISPECTRAL SENSORS

6.1.1 Line Scanners

6.1.2 Whisk-Broom and Bow-Tie Imagers

6.1.3 Push-Broom Sensors

6.1.4 Framing (2-D) Arrays

6.2 IMAGING SPECTROMETERS

6.2.1 Imaging Spectrometer Issues

6.2.2 Agile Spectrometers

6.3 LUMINESCENCE SENSORS

6.4 CALIBRATION ISSUES

6.5 SENSOR CASE STUDY

6.6 REFERENCES

CHAPTER 7 ATMOSPHERIC COMPENSATION: SOLUTIONS TO THE GOVERNING EQUATION

7.1 TRADITIONAL APPROACH: CORRELATION WITH GROUND-BASED MEASUREMENTS

7.2 APPROACHES TO ATMOSPHERIC COMPENSATION

7.3 APPROACHES TO MEASUREMENT OF TEMPERATURE

7.3.1 Ground Truth Methods (Temperature)

7.3.2 In-Scene Compensation Techniques (Temperature)

7.3.3 Atmospheric Propagation Models (Temperature)

7.3.4 Emissivity

7.3.5 Summary of Thermal Atmospheric Compensation

7.4. APPROACHES TO MEASUREMENT OF REFLECTIVITY

7.4.1 Ground Truth Methods (Reflectance), a.k.a. Empirical Line Method (ELM)

7.4.2 In-Scene Methods (Reflectance)

7.4.3 Atmospheric Propagation Models (Reflectance)

7.5 RELATIVE CALIBRATION (REFLECTANCE)

7.5.1 Spectral Ratio Techniques

7.5.2 Scene-to-Scene Normalization

7.6 COMPENSATION OF IMAGING SPECTROMETER DATA FOR ATMOSPHERIC EFFECTS

7.6.1 Inversion to Reflectance

7.6.2 Spectral Polishing

7.7 SUMMARY OF ATMOSPHERIC COMPENSATION ISSUES

7.8 REFERENCES

CHAPTER 8 DIGITAL IMAGE PROCESSING PRINCIPLES

8.1 POINT PROCESSING

8.2 NEIGHBORHOOD OPERATIONS-KERNEL ALGEBRA

8.3 STRUCTURE OR TEXTURE MEASURES

8.4 GLOBAL OPERATIONS

8.5 IMAGE RESTORATION

8.6 REFERENCES

CHAPTER 9 MULTISPECTRAL REMOTE SENSING ALGORITHMS: LAND COVER CLASSIFICATION

9.1 REVIEW OF MATRIX METHODS

9.1.1 Vector Algebra

9.1.2 Matrix Algebra

9.1.3 Eigenvectors and Singular Value Decomposition (SVD)

9.2 IMAGE CLASSIFICATION

9.2.1 Supervised Classification of a Single-Band Image

9.2.2 Supervised Multispectral Image Classification

9.2.3 Unsupervised Multivariate Classifier

9.2.4 Multivariate Classification Using Texture Metrics

9.2.5 Evaluation of Class Maps

9.2.6 Limitations of Conventional Multispectral Classification

9.3 IMAGE TRANSFORMS

9.4 HIERARCHICAL IMAGE PROCESSING

9.5 REFERENCES

CHAPTER 10 SPECTROSCOPIC IMAGE ANALYSIS

10.1 PERSPECTIVES ON SPECTRAL DATA

10.1.1 The Geometric or Deterministic Perspective

10.1.2 The Statistical Perspective

10.1.3 Spectral Feature Representation

10.2 ISSUES OF DIMENSIONALITY AND NOISE

10.2.1 Dimensionality Reduction

10.2.2 Noise Characterization: Noise versus Clutter

10.2.3 Noise-Sensitive Dimensionality Reduction

10.2.4 Estimation of the Dimensionality of a Data Set

10.3 GEOMETRIC OR DETERMINISTIC APPROACHES TO SPECTRAL IMAGE ANALYSIS

10.3.1 End Member Selection

10.3.2 Detection and Mapping Algorithms Using the Geometric or Structured Perspective

10.3.3 Linear Mixture Models and Fraction Maps

10.4 STATISTICAL APPROACHES TO SPECTRAL IMAGE ANALYSIS

10.4.1 Estimation of Relevant Statistical Parameters

10.4.2 Target Detection Using Statistical Characterization of the Image

10.5 SPECTRAL FEATURE APPROACHES TO SPECTRAL IMAGE ANALYSIS

10.6 HYBRID APPROACHES TO SPECTRAL IMAGE ANALYSIS

10.7 REFERENCES

CHAPTER 11 USE OF PHYSISCS-BASED MODELS TO SUPPORT SPECTRAL IMAGE ANALYSIS ALGORITHMS

11.1 SPECTRAL THERMAL INFRARED ANALYSIS METHODS

11.2 MODEL MATCHING USING RADIATIVE TRANSFER MODELS

11.2.1 Model Matching Applied to Atmospheric Compensation

11.2.2 Model Matching Applied to Water-Quality Parameter Retrieval

11.3 STATISTICAL INVERSION OF PHYSICAL MODELS

11.4 INCORPORATION OF PHYSICS-BASED MODELS INTO SPECTRAL ALGORITHM TRAINING

11.5 INCORPORATION OF PHYSICS-BASED SPATIAL SPECTRAL MODELS INTO ALGORITHM TRAINING

11.6 REFERENCES

CHAPTER 12 IMAGE/DATA COMBINATION ANDINFORMATION DISSEMINATION

12.1 IMAGE DISPLAY

12.2 THEMATIC AND DERIVED INFORMATION

12.3 OTHER SOURCES OF INFORMATION

12.3.1 GIS Concepts

12.3.2 Databases and Models

12.4 IMAGE FUSION

12.5 KNOW YOUR CUSTOMER

12.6 REFERENCES

CHAPTER 13 WEAK LINKS IN THE CHAIN

13.1 RESOLUTION EFFECTS (SPATIAL FIDELITY)

13.1.1 Spatial Image Fidelity Metrics

13.1.2 System MTF

13.1.3 Measurement of, and Correction for, MTF Effects

13.2 RADIOMETRIC EFFECTS

13.2.1 Noise

13.2.2 Noise Artifacts

13.2.3 Approaches for Correction of Noise and Periodic Structure in Images

13.3 SPECTRAL AND POLARIZATION EFFECTS

13.3.1 Feature/Spectral Band Selection

13.3.2 Polarization Issues

13.4 SPATIAL, SPECTRAL, AND RADIOMETRIC TRADEOFFS

13.5 IMAGE-QUALITY METRICS

13.6 SUMMARY OF IMAGE CHAIN CONCEPTS

13.7 REFERENCES

CHAPTER 14 IMAGE MODELING

14.1 SIMULATION ISSUES

14.2 APPROACHES TO SIMULATION

14.2.1 Physical Models

14.2.2 Fully Computerized Models

14.3 A MODELING EXAMPLE

14.4 APPLICATION OF SIG MODELS

14.5 SIG MODELING AND THE IMAGE CHAIN APPROACH

14.6 REFERENCES

People also search for Remote Sensing The Image Chain Approach 2nd :

remote sensing the image chain approach pdf

remote sensing technique

remote sensing types

remote sensing image stitching

remote sensing image correction

Tags: John Schott, Remote Sensing, The Image