Remote sensing from satellite or airborne platforms of land or sea surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to target (surface) to sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non lambertian surface conditions, and new absorbing species (CH/sub 4/, N/sub 2/O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-the-art approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.

Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

/pdf/vertex-component-analysis-a-fast-algorithm-to-unmix-1egulrpm76.pdf

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras. Imaging spectrometers are therefore often referred to as hyperspectral cameras (HSCs). Higher spectral resolution enables material identification via spectroscopic analysis, which facilitates countless applications that require identifying materials in scenarios unsuitable for classical spectroscopic analysis. Due to low spatial resolution of HSCs, microscopic material mixing, and multiple scattering, spectra measured by HSCs are mixtures of spectra of materials in a scene. Thus, accurate estimation requires unmixing. Pixels are assumed to be mixtures of a few materials, called endmembers. Unmixing involves estimating all or some of: the number of endmembers, their spectral signatures, and their abundances at each pixel. Unmixing is a challenging, ill-posed inverse problem because of model inaccuracies, observation noise, environmental conditions, endmember variability, and data set size. Researchers have devised and investigated many models searching for robust, stable, tractable, and accurate unmixing algorithms. This paper presents an overview of unmixing methods from the time of Keshava and Mustard's unmixing tutorial to the present. Mixing models are first discussed. Signal-subspace, geometrical, statistical, sparsity-based, and spatial-contextual unmixing algorithms are described. Mathematical problems and potential solutions are described. Algorithm characteristics are illustrated experimentally.

/pdf/hyperspectral-unmixing-overview-geometrical-statistical-and-2lb11fr9l4.pdf

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

Rates and reactions of biogeochemical processes vary in space and time to produce both hot spots and hot moments of elemental cycling. We define biogeochemical hot spots as patches that show disproportionately high reaction rates relative to the surrounding matrix, whereas hot moments are defined as short periods of time that exhibit disproportionately high reaction rates relative to longer intervening time periods. As has been appreciated by ecologists for decades, hot spot and hot moment activity is often enhanced at terrestrial-aquatic interfaces. Using examples from the carbon (C) and nitrogen (N) cycles, we show that hot spots occur where hydrological flowpaths converge with substrates or other flowpaths containing complementary or missing reactants. Hot moments occur when episodic hydrological flowpaths reactivate and/or mobilize accumulated reactants. By focusing on the delivery of specific missing reactants via hydrologic flowpaths, we can forge a better mechanistic understanding of the factors that create hot spots and hot moments. Such a mechanistic understanding is necessary so that biogeochemical hot spots can be identified at broader spatiotemporal scales and factored into quantitative models. We specifically recommend that resource managers incorporate both natural and artificially created biogeochemical hot spots into their plans for water quality management. Finally, we emphasize the needs for further research to assess the potential importance of hot spot and hot moment phenomena in the cycling of different bioactive elements, improve our ability to predict their occurrence, assess their importance in landscape biogeochemistry, and evaluate their utility as tools for resource management.

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Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems

Acknowledgements 1. Introduction 2. Electromagnetic wave propagation 3. The absorption of light 4. Specular reflection 5. Single particle scattering: perfect spheres 6. Single particle scattering: irregular particles 7. Propagation in a nonuniform medium: the equation of radiative transfer 8. The bidirectional reflectance of a semi-infinite medium 9. The opposition effect 10. A miscellany of bidirectional reflectances and related quantities 11. Integrated reflectances and planetary photometry 12. Photometric effects of large scale roughness 13. Polarization 14. Reflectance spectroscopy 15. Thermal emission and emittance spectroscopy 16. Simultaneous transport of energy by radiation and conduction Appendix A. A brief review of vector calculus Appendix B. Functions of a complex variable Appendix C. The wave equation in spherical coordinates Appendix D. Fraunhoffer diffraction by a circular hole Appendix E. Table of symbols Bibliography Index.

Theory of Reflectance and Emittance Spectroscopy

Introduction: Visible (VIS) and near-infrared reflectance (400 – 2800 nm) of the lunar regolith is dominantly controlled by variations in the abundance of three components: 1) opaque minerals (ilmenite), 2) iron bearing silicate minerals, and 3) maturation products (glasses, coatings bearing nanophase metallic iron). The same parameters control reflectance into the near-UV (250 to 400 nm), with varying degrees of importance.

HST UV-Visible Observations of the Apollo 17 Landing Area

Validity of Regolith Reflectance Models Based on the Radiative Transfer Equation and Coherent Backscatter Theory

The research on solar wind radiation damage and other effects in lunar samples which was conducted to understand the optical properties of lunar materials is reported. Papers presented include: solar radiation effects in lunar samples, albedo of the moon, radiation effects in lunar crystalline rocks, valence states of 3rd transition elements in Apollo 11 and 12 rocks, and trace ferric iron in lunar and meteoritic titanaugites.

https://ntrs.nasa.gov/api/citations/19720007157/downloads/19720007157.pdf

Solar wind radiation damage effects in lunar material

/pdf/measurement-of-reflectivities-of-rocks-minerals-and-glosses-1tc69j1skg.pdf

Measurement of reflectivities of rocks, minerals and glosses in the vacuum ultraviolet

[1] In his Forum, Kenneth Verosub (Eos, 91(33), 291, doi:10.1029/2010EO330003, 2010) tries to explain the climate denial phenomenon as due to postmodernist misinterpretation of scientific results. Unfortunately, I fear that this is only a minor cause and that the true explanation is much more insidious, with serious ramifications for all scientists, not just climatologists. As documented in several recent publications [e.g., Mayer, 2010], climate scientists are currently bearing the brunt of a deliberate, antiscience, misinformation campaign that is financed by certain fossil fuel companies and propagated by certain conservative radio programs, television organizations, and think tanks. Verosub wonders why no one has offered an explanation for why scientists worldwide are engaged in this supposed hoax. But explanations are frequently offered on conservative talk shows. For example, I found myself listening to The War Room With Quinn and Rose last fall while driving in the Pittsburgh, Pa., area and was appalled by the scenario painted in the show by cohost Jim Quinn. Apparently, all academics are socialists. Further, the Earth is not warming—it has been getting cooler since 1999. Quinn continued with this gem: Climate warming is an international conspiracy, funded by billionaire George Soros, perpetrated by scientists everywhere, and intended to delude governments into spending vast sums of money to counter a non-existent threat until the governments become bankrupt. Then in the ensuing chaos, socialists can take over and form a world socialist government.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011EO150004

Bruce Hapke

Papers

HST UV-Visible Observations of the Apollo 17 Landing Area

Validity of Regolith Reflectance Models Based on the Radiative Transfer Equation and Coherent Backscatter Theory

Solar wind radiation damage effects in lunar material

Measurement of reflectivities of rocks, minerals and glosses in the vacuum ultraviolet

Climate Change “Hoax”: Comment on “Climate Science in a Postmodern World”