The Winchcombe meteorite fell on February 28, 2021 and was the first recovered meteorite fall in the UK for 30 years, and the first UK carbonaceous chondrite. The meteorite was widely observed by meteor camera networks, doorbell cameras, and eyewitnesses, and 213.5 g (around 35% of the final recovered mass) was collected quickly—within 12 h—of its fall. It, therefore, represents an opportunity to study very pristine extra‐terrestrial material and requires appropriate careful curation. The meteorite fell in a narrow (600 m across) strewn field ~8.5 km long and oriented approximately east–west, with the largest single fragment at the farthest (east) end in the town of Winchcombe, Gloucestershire. Of the total known mass of 602 g, around 525 g is curated at the Natural History Museum, London. A sample analysis plan was devised within a month of the fall to enable scientists in the UK and beyond to quickly access and analyze fresh material. The sample is stored long term in a nitrogen atmosphere glove box. Preliminary macroscopic and electron microscopic examinations show it to be a CM2 chondrite, and despite an early search, no fragile minerals, such as halite, sulfur, etc., were observed.
Multispectral imaging instruments have been core payload components of Mars lander and rover missions for several decades. In order to place into context the future performance of the ExoMars Rosalind Franklin rover, we have carried out a detailed analysis of the spectral performance of three visible and near‐infrared (VNIR) multispectral instruments. We have determined the root mean square error (RMSE) between the expected multispectral sampling of the instruments and high‐resolution spectral reflectance data, using both laboratory spectral libraries and Mars orbital hyperspectral data. ExoMars Panoramic Camera (PanCam) and Mars2020 Perseverance Mastcam‐Z instruments have similar values of RMSE, and are consistently lower than for Mars Science Laboratory Mastcam, across both laboratory and orbital remote sensing data sets. The performance across mineral groups is similar across all instruments, with the lowest RMSE values for hematite, basalt, and basaltic soil. Minerals with broader, or absent, absorption features in these visible wavelengths, such as olivine, saponite, and vermiculite have overall larger RMSE values. Instrument RMSE as a function of filter wavelength and bandwidth suggests that spectral parameters that use shorter wavelengths are likely to perform better. Our simulations of the spectral performance of the PanCam instrument will allow the future use of targeted filter selection during ExoMars 2022 Rosalind Franklin operations on Mars.
<p><strong>Introduction:</strong>&#160; The ExoMars 2022 Rosalind Franklin rover is scheduled to be launched in summer 2022 with a suite of instruments to investigate the Martian surface and near sub-surface [1]. The context instruments: the Panoramic Camera (PanCam), composed of the two Wide Angle Cameras (WACs), and High Resolution Camera (HRC), and the Infrared Spectrometer for ExoMars (ISEM) will be imperative in the selection of drill and analysis sites. The PanCam stereo imaging system will be the primary mode of scientific observation during the mission with two multispectral WACs in the Visible to Near Infrared (VNIR, 440-1000 nm) range mounted at the top of the 2 meter mast [2]. Within the 36&#176; field of view of &#160;the PanCam WACs, HRC will provide 5&#176; field of view colour images at up to submillimetre resolutions [2]. Lastly, ISEM can them be utilised within the WAC/HRC field of views to provide 1&#176; spot size, hyper-spectral coverage in the Near to Mid (1150-3300 nm) Infrared range [3]. In preparation for the mission, spectral analysis tools are being developed to automate as much of the analysis process as is feasible to reduce time and effort costs during mission tactical planning and analysis, as well as improving ability to discriminate between different minerals of interest. Here we report on our effort to constrain the spectral and spatial response of the context instruments for ExoMars using Martian meteorite targets</p> <p><strong>Martian Meteorite Imaging:</strong> This study used instruments emulators for PanCam WAC, ISEM (extended to 300-2500 nm range to provide coverage of PanCam filter wavelengths for comparison) and HRC to investigate the spectral response of a variety of SNC meteorites, to determine the instrument spectral and spatial capabilities and build reliable mission analysis tools. Preliminary analysis has been undertaken on the largest of the Martian meteorite samples. Meteorites were imaged at minimum mission configuration, in semi-directional lighting and operated under mission-similar protocols [2]. The Shergottite Tissint, BM2012, M1, was imaged to assess the instrument ability to distinguish visual and spectral features in the fresh face of the specimen. The PanCam emulator data was first flat-fielded, and environmentally colour corrected and radiometrically corrected using the ExoSpec Software developed by the PanCam science team [4]. &#160;</p> <p><em>Preliminary Results.</em> The fresh face of Tissint is comprised of olivine macrocrysts with black glass veins [5]. These features can be distinguished visually in both the WAC and HRC images (Figure 1). These features, however, are too small to target alone with the hyperspectral instrumentation. To probe the spectral response of these regions a 530-570-670 decorrelation stretch &#160;was applied to highlight variation associated with a characteristic olivine spectral feature in this region, shown in Figure 2. This decorrelation stretch does show significant spectral variation between the dominant face material and the black glass veins.</p> <p><img src="data:image/png;base64, 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