Fitting the curve in Excel®:Systematic curve fitting of laboratory and remotely sensed planetary spectra

Spectroscopy in planetary science often provides the only information regarding the compositional and mineralogical make up of planetary surfaces. The methods employed when curve fitting and modelling spectra can be confusing and difficult to visualize and comprehend. Researchers who are new to working with spectra may find inadequate help or documentation in the scientific literature or in the software packages available for curve fitting. This problem also extends to the parameterization of spectra and the dissemination of derived metrics. Often, when derived metrics are reported, such as band centres, the discussion of exactly how the metrics were derived, or if there was any systematic curve fitting performed, is not included. Herein we provide both recommendations and methods for curve fitting and explanations of the terms and methods used. Techniques to curve fit spectral data of various types are demonstrated using simple-to-understand mathematics and equations written to be used in Microsoft Excel® software, free of macros, in a cut-and-paste fashion that allows one to curve fit spectra in a reasonably user-friendly manner. The procedures use empirical curve fitting, include visualizations, and ameliorates many of the unknowns one may encounter when using black-box commercial software. The provided framework is a comprehensive record of the curve fitting parameters used, the derived metrics, and is intended to be an example of a format for dissemination when curve fitting data

Reflectance and Emission Spectroscopy: Curve Fitting Methods with Application to Impact Glasses and the Varying Grain Size of Planetary Analogue Minerals

Spectroscopy, i.e., the measurement of electromagnetic radiation as a function of wavelength, is arguably the technique most responsible for the majority of what is collectively known about the composition of stars, the distances to galaxies, the age of the universe and so on. Spectroscopy is also the tool most used to discern the mineralogy of planetary bodies remotely. Measuring the speed at which a star is receding and its composition, or the composition of an interstellar cloud of gas are well understood uses of spectroscopy. When it comes to spectroscopies use to discern mineralogy, the scientific literature on the subject of the application of spectroscopy to the solid surfaces of asteroids and the nearby planets would lead one to conclude it too is as robust a measure as that of stellar composition or Doppler shift, although it is not. A number of properties of the target under investigation, namely, mineralogy, grain size, packing (i.e., loose grains versus consolidated rock), phase angle and temperature strongly affect the reflectance and emission spectrum of the common minerals encountered when interrogating planetary surfaces. These effects can be profound and significantly complicate our ability to robustly identify mineralogy when the properties of the surface are not known. The works herein address some of these issues, by firstly, providing a set of methods/functions and a set of guidelines for empirically curve fitting spectra in a robust and repeatable manner. Chapter 2 and its appendices were conceived in an effort to provide the spectroscopic community with a set of curve fitting tools, to be put freely in the hands of spectroscopists in the hopes that the community can see its way to providing fit metrics of spectra presented in the literature with transparency so the metrics can be widely understood and applied. Secondly, the methods presented in Chapter 2 were applied in Chapters 3 and 4 to the spectra of impact glasses and hydrothermal silicate evaporates to aid in their robust identification, and to the effects of significant grain size variation on the most common planetary surficial analogue materials pyroxene, olivine and basalt