Land surface emissivity retrieval from satellite data
01 May 2013-International Journal of Remote Sensing (Taylor & Francis)-Vol. 34, Iss: 9, pp 3084-3127
TL;DR: The theoretical basis of LSE measurements is given, a description of the published methods, and the validation methods, which are of importance in verifying the uncertainty and accuracy of retrieved emissivity.
Abstract: As an intrinsic property of natural materials, land surface emissivity LSE is an important surface parameter and can be derived from the emitted radiance measured from space. Besides radiometric calibration and cloud detection, two main problems need to be resolved to obtain LSE values from space measurements. These problems are often referred to as land surface temperature LST and emissivity separation from radiance at ground level and as atmospheric corrections in the literature. To date, many LSE retrieval methods have been proposed with the same goal but different application conditions, advantages, and limitations. The aim of this article is to review these LSE retrieval methods and to provide technical assistance for estimating LSE from space. This article first gives a description of the theoretical basis of LSE measurements and then reviews the published methods. For clarity, we categorize these methods into 1 semi-empirical or theoretical methods, 2 multi-channel temperature emissivity separation TES methods, and 3 physically based methods PBMs. This article also discusses the validation methods, which are of importance in verifying the uncertainty and accuracy of retrieved emissivity. Finally, the prospects for further developments are given.
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TL;DR: A review of the current status of selected remote sensing algorithms for estimating land surface temperature from thermal infrared (TIR) data is presented in this article, along with a survey of the algorithms employed for obtaining LST from space-based TIR measurements.
1,470 citations
Cites background or methods from "Land surface emissivity retrieval f..."
...profiles (atmospheric quantities) from hyperspectral TIR data As stated by Li et al. (2013), the coupling of the surface-emitted radiance and the atmospheric absorption, diffusion and emission complicates the separate retrieval of surface parameters (LST and LSEs) and atmospheric profiles....
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...In practice, the heterogeneity of the surface and the angular and spectral variation of the LSE (Li et al., 2013) make it challenging to exactly determine the LSE at the satellite pixel scale in advance....
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...This correlation represents a problem even if the LST is made solvable either by reducing the number of unknowns or by increasing the number of equations through reasonable assumptions or constraints on the LSEs (Gillespie et al., 1996; Li et al., 2013)....
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...A change in the satellite VZA causes a change in the LSE, consequently violating the assumption of time-invariant LSEs and decreasing the accuracy of the TTM (Li et al., 2013)....
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...…is on the same order of magnitude as the radiance directly emitted by the surface, if the surface albedo is about 0.1, the introduction of theMIR channels in LST retrieval significantly reduces the correlation of the RTE sets and greatly improves the accuracy of the estimated LST (Li et al., 2013)....
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1,327 citations
TL;DR: This letter proposes SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval, and results show slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents.
Abstract: The importance of land surface temperature (LST) retrieved from high to medium spatial resolution remote sensing data for many environmental studies, particularly the applications related to water resources management over agricultural sites, was a key factor for the final decision of including a thermal infrared (TIR) instrument on board the Landsat Data Continuity Mission or Landsat-8. This new TIR sensor (TIRS) includes two TIR bands in the atmospheric window between 10 and 12 $\mu\hbox{m}$ , thus allowing the application of split-window (SW) algorithms in addition to single-channel (SC) algorithms or direct inversions of the radiative transfer equation used in previous sensors on board the Landsat platforms, with only one TIR band. In this letter, we propose SC and SW algorithms to be applied to Landsat-8 TIRS data for LST retrieval. Algorithms were tested with simulated data obtained from forward simulations using atmospheric profile databases and emissivity spectra extracted from spectral libraries. Results show mean errors typically below 1.5 K for both SC and SW algorithms, with slightly better results for the SW algorithm than for the SC algorithm with increasing atmospheric water vapor contents.
607 citations
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...This letter does not attempt to review different LST/emissivity retrieval methodologies, as detailed, for example, in two recent publications [5], [6]....
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TL;DR: For the investigated sites and scenes, results show that the LST inverted from the radiative transfer equation-based method using band 10 has the highest accuracy with RMSE lower than 1 K, while the SW algorithm has moderate accuracy and the SC method has the lowest accuracy.
Abstract: Accurate inversion of land surface geo/biophysical variables from remote sensing data for earth observation applications is an essential and challenging topic for the global change research. Land surface temperature (LST) is one of the key parameters in the physics of earth surface processes from local to global scales. The importance of LST is being increasingly recognized and there is a strong interest in developing methodologies to measure LST from the space. Landsat 8 Thermal Infrared Sensor (TIRS) is the newest thermal infrared sensor for the Landsat project, providing two adjacent thermal bands, which has a great benefit for the LST inversion. In this paper, we compared three different approaches for LST inversion from TIRS, including the radiative transfer equation-based method, the split-window algorithm and the single channel method. Four selected energy balance monitoring sites from the Surface Radiation Budget Network (SURFRAD) were used for validation, combining with the MODIS 8 day emissivity product. For the investigated sites and scenes, results show that the LST inverted from the radiative transfer equation-based method using band 10 has the highest accuracy with RMSE lower than 1 K, while the SW algorithm has moderate accuracy and the SC method has the lowest accuracy.
557 citations
TL;DR: An adjustment of the split window algorithm (SWA) for TIRS that uses atmospheric transmittance and land surface emissivity (LSE) as inputs is presented that is leading to progress in the determination of LST by Landsat-8 TirS.
Abstract: Land surface temperature (LST) is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS). This paper presents an adjustment of the split window algorithm (SWA) for TIRS that uses atmospheric transmittance and land surface emissivity (LSE) as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE) of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.
313 citations
References
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01 Jan 1974
TL;DR: The use of vibrational spectroscopy as a tool in identifying mineral species and in deriving information concerning the structure, composition and reactions of minerals and mineral products is discussed in this paper.
Abstract: The principal concern of this book is the use of vibrational spectroscopy as a tool in identifying mineral species and in deriving information concerning the structure, composition and reactions of minerals and mineral products. This does not mean that the approach is purely empirical; some theoretical understanding of the vibrational spectra of solids is essential to an assessment of the significance of the variations in the spectra that can be found within what is nominally a single mineral species, but which usually includes a range of compositions and defect structures. Theory alone, however, can give only limited support to the mineral spectroscopist, and careful studies of well-characterized families of natural and synthetic minerals have played an essential role in giving concrete structural significance to spectral features. The publication of this book represents a belief that theory and practice have now reached a state of maturitity and of mutual support which justifies a more widespread application of vibrational spectroscopy to the study of minerals and inorganic materials. The wide area of theory and practice that deserves to be covered has required a careful selection of the subject matter to be incorporated in this book. Since elementary vibrational spectroscopy is now regularly included in basic chemistry courses, and since so many books cover the theory and practice of molecular spectroscopy, it has been decided to assume the very basic level of knowledge which will be found, for example, in the elementary introduction of Cross and Jones (1969). With this assumption, it has been possible to concentrate on those aspects that are peculiar to or of particular significance for mineral spectroscopy.
2,720 citations
"Land surface emissivity retrieval f..." refers background in this paper
...The structures of mineral molecules and the force constants between atoms, as well as the long-range order of crystal lattices contribute to the spectral behaviour of rocks (Farmer 1974; Salisbury and D’Aria 1992)....
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TL;DR: In this paper, a simple radiative transfer model with vegetation, soil, and atmospheric components is used to illustrate how the normalized difference vegetation index (NDVI), leaf area index (LAI), and fractional vegetation cover are dependent.
2,429 citations
Additional excerpts
...Pv is the fraction of vegetation that can be derived either from the NDVI (Valor and Caselles 1996; Carlson and Ripley 1997; Sobrino and Raissouni 2000) or from the variable atmospherically resistant index (VARIgreen) and spectral mixture analysis (SMA) techniques (Sobrino et al. 2008), dελ is the…...
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TL;DR: In this paper, the authors present an approach to calculate the energy levels of Diatomic molecules in terms of the number of excited states in the molecules and the lifetime of these states.
Abstract: 1. Introduction.- 2. Units of Physical Quantities.- 2.1 Systems of Units in Physics.- 2.2 Fundamental Physical Constants.- 2.3 Systems of Units Based on "Natural Standards".- 2.4 Tables of Conversion Factors.- I Atoms and Atomic Ions.- 3. Isotopic Composition, Atomic Mass Table and Atomic Weights of the Elements.- 3.1 Parameters of Stable and Long-Lived Isotopes.- 3.2 Atomic Weights of the Elements and Atomic Mass Table.- 4. Structure of Atomic Electron Shells.- 4.1 Electron Configurations and Ground-State Terms.- 4.2 The Periodic Table.- 4.3 Parameters of Wavefunctions for Valence Electrons in Atoms, Positive and Negative Ions.- 5. Energetics of Neutral Atoms.- 5.1 Ionization Potentials of Atoms.- 5.2 Quantum Defects of Atomic Rydberg States.- 5.3 Fine-Structure Splitting of Atomic Energy Levels.- 5.4 Hyperfine Structure of Atomic Energy Levels.- 5.5 Isotope Shifts of Low-Lying Atomic Levels.- 5.6 Atoms in Static Electric and Magnetic Fields. Atomic Polarizabilities and Magnetic Susceptibilities.- 6. Energetics of Atomic Ions.- 6.1 Ionization Potentials of Atomic Ions.- 6.2 Electron Affinities of Atoms.- 6.3 Energy Levels of Multiply Charged Atomic Ions.- 7. Spectroscopic Characteristics of Neutral Atoms.- 7.1 Low-Lying Atomic Terms.- 7.2 Diagrams of Atomic Energy Levels and Grotrian Diagrams.- 7.3 Atomic Oscillator Strengths in Absorption.- 7.4 Lifetimes of Resonant Excited States in Atoms.- 7.5 Energy Levels and Lifetimes for Metastable States in Atoms.- 7.6 Lifetimes of Atomic Rydberg States.- 8. Spectroscopic Characteristics of Atomic Positive Ions.- 8.1 Low-Lying Terms of Singly Ionized Atoms.- 8.2 Lifetimes of Resonant Excited States in Atomic Ions.- 8.3 Energy Levels and Lifetimes for Metastable States in Singly Ionized Atoms.- 8.4 Optical Parameters of Multiply Charged Atomic Ions.- II Molecules and Molecular Ions.- 9. Interaction Potentials Between Atomic and Molecular Species.- 9.1 Van der Waals Coefficients for Interatomic Multipole Interactions.- 9.2 Long-Range Exchange Interactions of Atoms.- 9.3 Short-Range Repulsive Interactions Between Atomic and Molecular Species.- 10. Diatomic Molecules.- 10.1 Electron Configurations of Diatomic Molecules.- 10.2 Asymptotic Parameters of Wavefunctions for Valence Electrons in Diatomic Molecules.- 10.3 Spectroscopic Constants of Diatomic Molecules.- 10.4 Potential Energy Curves.- 10.5 Ionization Potentials of Diatomic Molecules.- 10.6 Dissociation Energies of Diatomic Molecules.- 10.7 Lifetimes of Excited Electron States in Diatomic Molecules.- 10.8 Parameters of Excimer Molecules.- 10.9 Einstein Coefficients for Spontaneous Emission from Vibrationally Excited Diatomic Molecules.- 11. Diatomic Molecular Ions.- 11.1 Electron Configurations and Asymptotic Parameters of Wavefunctions for Valence Electrons in Diatomic Molecular Ions.- 11.2 Spectroscopic Constants of Diatomic Molecular Ions.- 11.3 Dissociation Energies of Diatomic Molecular Ions.- 11.4 Electron Affinities of Diatomic Molecules.- 11.5 Proton Affinities of Atoms.- 11.6 Lifetimes of Excited Electron States in Diatomic Molecular Ions.- 12. Van der Waals Molecules.- 12.1 Potential Well Parameters of Van der Waals Molecules.- 12.2 Potential Well Parameters of Van der Waals Molecular Ions.- 12.3 Ionization Potentials of Van der Waals Molecules.- 13. Polyatomic Molecules.- 13.1 Constants of Triatomic Molecules.- 13.2 Ionization Potentials of Polyatomic Molecules.- 13.3 Bond Dissociation Energies of Polyatomic Molecules.- 13.4 Lifetimes of Vibrationally Excited Polyatomic Molecules.- 14. Polyatomic Molecular Ions.- 14.1 Bond Dissociation Energies of Complex Positive Ions.- 14.2 Bond Dissociation Energies of Complex Negative Ions.- 14.3 Electron Affinities of Polyatomic Molecules.- 14.4 Proton Affinities of Molecules.- 15. Electrical Properties of Molecules.- 15.1 Dipole Moments of Molecules.- 15.2 Molecular Polarizabilities.- 15.3 Quadrupole Moments of Molecules.- Mathematical Appendices.- A. Coefficients of Fractional Parentage.- B. Clebsch-Gordan Coefficients.
1,688 citations
TL;DR: In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared data supplied by band 6 of the Thematic Mapper (TM) sensor onboard the Landsat 5 satellite are compared.
1,594 citations
"Land surface emissivity retrieval f..." refers background in this paper
...…Airborne Imaging Spectrometer (DAIS) (Sobrino et al. 2002), MODIS (Sobrino, Kharraz, and Li 2003; Momeni and Saradjian 2007), Thematic Mapper (TM) (Sobrino, Jimenez-Munoz, and Paolini 2004), Advanced Along Track Scanning Radiometer (AATSR), Spinning Enhanced Visible and Infrared Imager (SEVIRI),…...
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