Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- 2 The Remote Sensing Environment
- 3 Spectral Properties of Materials
- 4 Imaging Spectrometers
- 5 Imaging Spectrometer Characterization and Data Calibration
- 6 Radiative Transfer and Atmospheric Compensation
- 7 Statistical Models for Spectral Data
- 8 Linear Spectral Transformations
- 9 Spectral Mixture Analysis
- 10 Signal Detection Theory
- 11 Hyperspectral Data Exploitation
- Appendix Introduction to Gaussian Optics
- Bibliography
- Index
- Plate section
6 - Radiative Transfer and Atmospheric Compensation
Published online by Cambridge University Press: 10 November 2016
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- 2 The Remote Sensing Environment
- 3 Spectral Properties of Materials
- 4 Imaging Spectrometers
- 5 Imaging Spectrometer Characterization and Data Calibration
- 6 Radiative Transfer and Atmospheric Compensation
- 7 Statistical Models for Spectral Data
- 8 Linear Spectral Transformations
- 9 Spectral Mixture Analysis
- 10 Signal Detection Theory
- 11 Hyperspectral Data Exploitation
- Appendix Introduction to Gaussian Optics
- Bibliography
- Index
- Plate section
Summary
The next processing step for calibrated imaging spectrometer data is the conversion from the at-aperture radiance to a surface reflectance signature, for the VNIR/SWIR spectral range, or to a surface emissivity signature and temperature, for the LWIR spectral range. This requires that the transmission and emission of the atmosphere be quantified from the aggregated information that is present in the at-aperture radiance. In the solar reflective range this includes estimates of the amount of water in the scene, which is highly variable, and of the aerosol loading in order to calculate both the diffuse radiance and the contribution from light that is scattered and reflected from the directly viewed pixel and the surrounding area. Similarly, for a sensor operating in the emissive regime, the water and the atmospheric thermal emission is quantified in order to retrieve the ground-leaving radiance that is used to estimate the temperature and emissivity of the surface.
In this chapter, the physics of radiative transfer will be developed first, in order to establish a basis for the discussion of the particular techniques that are applied in the reflective and emissive regimes. The modeling tools that are used to quantitatively describe the processes of absorption, transmission, and emission in a forward sense, i.e. in the direction of light propagation, are introduced prior to delving into the problem of retrieving the surface properties of interest. The reflectance retrieval is treated in detail and includes the derivation of the inverse radiative transfer model, the estimation of the quantities that are required to apply the inverse model, and the algorithms that are utilized, using both physics-based modeling and empirical techniques. The final sections address the problem of atmospheric compensation in the longwave infrared.
Radiative Transfer
The propagation of radiation through the atmosphere is described by the theory of radiative transfer. A complete description of radiative transfer is beyond our scope; however, the critical concepts required to understand the processes of atmospheric compensation are introduced within the limitations of a book devoted to remote sensing using an imaging spectrometer. Radiative transfer as a discipline was established by Arthur Schuster's paper in 1905, where he recognized the importance of multiple scattering (Schuster, 1905).
- Type
- Chapter
- Information
- Hyperspectral Imaging Remote SensingPhysics, Sensors, and Algorithms, pp. 295 - 359Publisher: Cambridge University PressPrint publication year: 2016