Compact Reconnaissance Imaging Spectrometer For Mars Data Research Articles

Martian cloud map retrievals for 2006–2008 from MRO CRISM multi-spectral data

As the state of Mars Climate modeling advances, there will be a growing need to provide observational results to act as comparisons or even as assimilation products to the next generation of models. This is especially true for atmospheric aerosols that are hard to model as they either have unspecified and/or ubiquitous sources (dust clouds) or form faster than the model time-steps can efficiently use (ice clouds). To that end, we present here our technique to recover ice and dust cloud optical depth maps from Mars Reconnaissance Orbiter (MRO) Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) multi-spectral mapping mode data. We use a multi-step, boot-strapping technique that does not make any a priori assumptions about the aerosols or surface reflectance at any point other than assuming the surface, at any time, can be constructed from a linear combination of a finite number of spectral endmembers. It uses singular value decomposition (SVD) and target transformation (TT) to define a candidate endmember space then uses N-FINDR and Hyperplane-based Craig Simplex Identification (HyperCSI) to locate the spectral endmembers. Radiative transfer models are then used to recover the ice and dust optical depth and surface reflectance that best fits the CRISM spectrum. Our resulting optical depth maps are shown to be in gross agreement with ultraviolet (UV), visible wavelength (VIS), and thermal infrared (TIR) results covering the same time periods. Retrieved optical depth values are, on average, within about 50% of those previously reported (Wolff et al., 2019; Montabone et al., 2015), although specific locations can vary by about a factor of 2 indicating some refinements to our retrievals will be needed before we can go into production mode on the remaining CRISM data.

The CRISM investigation in Mars orbit: Overview, history, and delivered data products

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on the Mars Reconnaissance Orbiter (MRO) collected hyperspectral images of the Martian surface and atmosphere from September 27, 2006, through May 7, 2022. Over that time, nearly twenty scientific investigations were completed, most of which arose as a result of the findings from previous investigations. Two review papers published in 2009 (Murchie et al., 2009a, b) described the initial two-year investigation during MRO's Primary Science Phase, its key findings, and the CRISM data products that were developed and released to the community through that time. Here we describe the conduct and evolution of the CRISM investigation since then, which includes MRO's Extended Science Phase and first five Extended Missions. We document the physical changes in the instrument as it aged, including capabilities that were lost as well as new modes of operation not initially envisioned; the new science questions that were investigated and their key findings; anatomy of the extensive collection of data products that have been released to the Planetary Data System; the “final” radiometric calibration; high-order derived products produced from high-resolution targeted observations and global mapping campaigns; and data processing and analysis tools which have been developed and released by the CRISM team.

A Fully-Automated Framework for Mineral Identification on Martian Surface Using Supervised Learning Models

The availability of various spectral libraries for CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) data on NASA PDS (Planetary Data System) hugely facilitated the research on the surface mineralogy of Mars, however, building supervised learning models for mineral mapping appears to be challenging due to the lack of ground-truth/training data. In this paper, an automated framework is presented that classifies the spectra in a CRISM hyperspectral image using supervised learning models, where the required training data is produced by augmenting the mineral spectra available in the MICA (Minerals Identified in CRISM Analysis) spectral library, that keeps the key absorption signatures in the mineral spectra intact while providing adequate variability. The framework contains a pre-processing pipeline that in addition to some conventional pre-processing steps includes a new feature extraction method to capture the information of the most distinguishable absorption patterns in the spectra. The proposed framework is validated on a set of CRISM images captured from different locations on the Martian surface by using different types of supervised learning models, like random forests, support vector machines, and neural networks. An uncertainty analysis of the different steps involved in the pre-processing pipeline is provided, as well as a comparison of performances with some of the previously used methods for this purpose, which shows this framework works comparably well with a mean accuracy of around 0.8. Interactive mineral maps are also provided for the detected dominant minerals.

Investigation of Absorption Bands around 3.3 μm in CRISM Data

Absorptions in the range 3.1 μm to 3.6 μm are under the spotlight in the context of planetary research, because hydrocarbon molecules show absorption bands in this range. Consequently, even knowing that the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) was designed for the detection of mineralogical features on Mars’s surface, we exploited CRISM data in the range 3.2 μm to 3.4 μm to search for potential hydrocarbon compounds. To date, methane has been the only hydrocarbon detected on Mars. Therefore, we began our investigation into CRISM data in locations in which methane had been detected and where it could form due to the mineralogy of the specific site. The datasets chosen for this study included observation sites in the Oxia Planum, the Gale Crater, and Nili Fossae areas. We mapped the modified Gaussian model (MGM) to fit the CRISM data in order to extract the band parameters of the absorptions in the 3.3 μm spectral region. As a result, we found clusters of pixels with spectra that exhibited band centers between approximately 3.28 and 3.35 μm. The hydrocarbons showing absorptions in this range included polycyclic aromatic compounds as well as methane, ethane, and aliphatic compounds. We speculated that some absorptions of approximately 3.3 μm could be related to methane, so we calculated a theoretical lower limit of detection for each observation in the selected CRISM datasets. This was performed by simulating the CRISM spectra for the different sites, with diverse concentrations of CH4, using NASA’s Planetary Spectrum Generator online tool. These simulations established the relationship between the concentration and methane band depths, as detected by the CRISM. Methane band depths exceeding the thresholds varied from one observation to another, in the range of 0.0136 to 0.0237, which corresponded to a range of theoretically lower limits of concentration between 180 and 600 ppbv. Although we could not confirm or deny the occurrences of methane seepages or hydrocarbons in the investigated datasets, we demonstrated a possible method for searching for hydrocarbons in other CRISM data and for assessing a confidence limit in the detection of the methane band in CRISM data.

Learning the Link between Albedo and Reflectance: Machine Learning-Based Prediction of Hyperspectral Bands from CTX Images

The instruments of the Mars Reconnaissance Orbiter (MRO) provide a large quantity and variety of imagining data for investigations of the Martian surface. Among others, the hyper-spectral Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) captures visible to infrared reflectance across several hundred spectral bands. However, Mars is only partially covered with targeted CRISM at full spectral and spatial resolution. In fact, less than one percent of the Martian surface is imaged in this way. In contrast, the Context Camera (CTX) onboard the MRO delivers images with a higher spatial resolution and the image data cover almost the entire Martian surface. In this work, we examine to what extent machine learning systems can learn the relation between morphology, albedo and spectral composition. To this end, a dataset of 67 CRISM-CTX image pairs is created and different deep neural networks are trained for the pixel-wise prediction of CRISM bands solely based on the albedo information of a CTX image. The trained models enable us to estimate spectral bands across large areas without existing CRISM data and to predict the spectral composition of any CTX image. The predictions are qualitatively similar to the ground-truth spectra and are also able to recover finer grained details, such as dunes or small craters.

Spatial distributions and origin of hydrated sulfate minerals at the mineral bowl in Ophir Chasma, Mars

Numerous occurrences of hydrated minerals (e.g., phyllosilicate, sulfate) have been found on the surface of Mars by remote sensing and in-situ exploration missions, providing strong evidence of the aqueous environment in Martian history. However, the detailed origin of these hydrated minerals is often controversial, reducing their usefulness in constraining the aqueous history of Mars. For instance, in Ophir Chasma, the origins of hydrated sulfates are debatable among hypotheses of precipitating from groundwater, paleolake, or meteoric water. In this study, we performed detailed mineralogy, morphology and stratigraphy analyses of the hydrated phases in the mineral bowl, a depression between the southern wall and mensa of Ophir Chasma, using datasets from Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), High Resolution Imaging Science Experiment (HiRISE) and High Resolution Stereo Camera (HRSC). A large number of monohydrate sulfates (MHS), polyhydrated sulfates (PHS) and some jarosite were identified in this region. Elevation of PHS-rich regions (mean elevation of −1130 ​m) is higher than those of MHS (mean value of −1401 ​m). Spectra of poly- and monohydrated sulfates mixtures were investigated in details in laboratory. Spectral features (i.e., band depth of ~1.9 ​μm, 2.1 ​μm, convexity at 2.1 ​μm and 2.4 ​μm) of sulfates mixtures changed regularly with the abundance of endmember. The linear function between the ratio of BD2100_2 to SINDEX2 and kieserite component was set up to estimate hydrated sulfates abundance. We employ the function onto CRISM data and find a coexistence of poly- and monohydrated sulfates for the formerly recognized PHS endmember, which may indicate a local dehydration/rehydration process for the sulfated minerals. Comprehensive mineralogy, topography, and stratigraphy analyses of hydrated sulfates outcrops suggest a complex formation scenario which could include surface runoff, paleolake, even aeolian erosion.

Dynamic aperture factor analysis/target transformation (DAFA/TT) for Mg-serpentine and Mg-carbonate mapping on Mars with CRISM near-infrared data

Serpentine and carbonate are products of serpentinization and carbonation processes on Earth, Mars, and other celestial bodies. Their presence implies that localized habitable environments may have existed on ancient Mars. Factor Analysis and Target Transformation (FATT) techniques have been applied to hyperspectral data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) to identify possible serpentine and Mg-carbonate-bearing outcrops. FATT techniques are capable of suggesting the presence of individual spectral signals in complex spectral mixtures. Applications of FATT techniques to CRISM data thus far only evaluate whether an entire analyzed image (≈ 3 × 105 pixels) may contain spectral information consistent with a specific mineral of interest. The spatial distribution of spectral signal from the possible mineral is not determined, making it difficult to validate a reported detection and also to understand the geologic context of any purported detections. We developed a method called Dynamic Aperture Factor Analysis/Target Transformation (DAFA/TT) to highlight the locations in a CRISM observation (or any similar laboratory or remotely acquired data set) most likely to contain spectra of specific minerals of interest. DAFA/TT determines the locations of possible target mineral spectral signals within hyperspectral images by performing FATT in small moving windows with different geometries, and only accepting pixels with positive detections in all cluster geometries as possible detections. DAFA/TT was applied to a hyperspectral image of a serpentinite from Oman for validation testing in a simplified laboratory setting. The mineral distribution determined by DAFA/TT application to the laboratory hyperspectral image was consistent with Raman analysis of the serpentinite sample. DAFA/TT also successfully mapped the spatial distribution of Mg-serpentine and Mg-carbonate previously detected in CRISM data using band parameter mapping and extraction of ratioed spectra. We applied DAFA/TT to CRISM images in some olivine-rich regions of Mars to characterize the spatial distribution of Mg-serpentine and Mg-carbonate-bearing outcrops.

Adversarial feature learning for improved mineral mapping of CRISM data

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has proven instrumental in the mineralogical analysis of the Martian surface. An essential tool for mineral identification for this dataset has been the CRISM summary parameters–which use simple mathematical functions to measure the presence/absence of specific spectral features. While the CRISM summary parameters and browse products (combinations of specific summary parameters) have proven valuable in guiding manual analysis, these hand-crafted representations are not well suited for automated analysis, as CRISM spectral artifacts and noise negatively affect their performance, making these parameters prone to false alarms. We propose an unsupervised technique based on Generative Adversarial Networks (GANs) to learn a more discriminative representation from CRISM data, such that simple metrics in the representation space are sufficient to discriminate between the various mineral spectra present in the data. We describe a simple pipeline using GAN based representations to map mineral signatures of interest across the CRISM image database. We show that the features learned by the GAN are better suited to discriminate mineral signatures in the CRISM database compared to the summary parameters and classical similarity metrics. Finally, we validate the technique over a subset of CRISM images over the Jezero crater and NE Syrtis regions of Mars.

Synergistic Ground and Orbital Observations of Iron Oxides on Mt. Sharp and Vera Rubin Ridge.

Visible/short‐wave infrared spectral data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) show absorptions attributed to hematite at Vera Rubin ridge (VRR), a topographic feature on northwest Mt. Sharp. The goals of this study are to determine why absorptions caused by ferric iron are strongly visible from orbit at VRR and to improve interpretation of CRISM data throughout lower Mt. Sharp. These goals are achieved by analyzing coordinated CRISM and in situ spectral data along the Curiosity Mars rover's traverse. VRR bedrock within areas that have the deepest ferric absorptions in CRISM data also has the deepest ferric absorptions measured in situ. This suggests strong ferric absorptions are visible from orbit at VRR because of the unique spectral properties of VRR bedrock. Dust and mixing with basaltic sand additionally inhibit the ability to measure ferric absorptions in bedrock stratigraphically below VRR from orbit. There are two implications of these findings: (1) Ferric absorptions in CRISM data initially dismissed as noise could be real, and ferric phases are more widespread in lower Mt. Sharp than previously reported. (2) Patches with the deepest ferric absorptions in CRISM data are, like VRR, reflective of deeper absorptions in the bedrock. One model to explain this spectral variability is late‐stage diagenetic fluids that changed the grain size of ferric phases, deepening absorptions. Curiosity's experience highlights the strengths of using CRISM data for spectral absorptions and associated mineral detections and the caveats in using these data for geologic interpretations and strategic path planning tools.

A new method for atmospheric correction and de-noising of CRISM hyperspectral data

We propose a new method to perform atmospheric correction and de-noising on hyperspectral image cubes acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on board NASA’s Mars Reconnaissance Orbiter (MRO). The CRISM imager has had an important role in advancing our understanding of many aspects of Martian mineralogy. Many mineral detections from CRISM data have been facilitated by significant efforts in the development of the CRISM data processing pipeline to retrieve surface reflectance. However, some residuals remain in CRISM spectra after atmospheric correction, causing difficulty in the interpretation of processed reflectance spectra. In addition, CRISM images are occasionally corrupted with high noise levels exhibiting heterogeneous statistical properties. This paper identifies the cause of such spectral distortions and describe a technique that simultaneously performs both atmospheric correction and de-noising for each image cube individually. In particular, our method focuses on the 1.0–2.6 μm wavelength region of CRISM images and is applicable to images of non-icy surfaces. Experimental results show that our technique is able to significantly mitigate noise and distortions from various sources like gaseous absorptions, detector temperature, and water ice aerosols, compared with the atmospheric correction method in the CRISM official processing pipeline called volcano scan correction, for a variety of scenes. Careful validations that include the qualitative examination of noise and artifacts both on ratioed and non-ratioed spectra and comparison using multiple overlapping images strengthen confidence in our approach.

Quantitative assessment of water content and mineral abundances at Gale crater on Mars with orbital observations

Context. The information of water content can help to improve atmospheric and climate models, and thus provide a better understanding of the past and present role of water and aqueous alteration on Mars. Mineral abundances can provide unique constraints on their formation environments and thus also on the geological and climate evolution of Mars. Aims. In this study, we used a state-of-the-art approach to derive the hydration state and mineral abundances over Gale crater on Mars, analysing hyperspectral visible/near-infrared data from the Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité (OMEGA) instrument onboard Mars Express and from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instrument onboard the Mars Reconnaissance Orbiter. Methods. The Discrete Ordinate Transfer model was used to perform atmospheric and thermal correction of the OMEGA and CRISM hyperspectral data in order to derive the surface single scattering albedos (SSAs) at Gale crater, Mars. Water content was estimated using a linear relationship between the derived effective single-particle absorption thickness at 2.9 μm from SSAs and the water weight percentage. Mineral abundances were retrieved by performing the linear spectral unmixing of SSAs from CRISM data. The results were compared with the ground-truth results returned from Curiosity rover. Results. The water content for most areas at Gale crater derived using the OMEGA data is around 2–3 water weight percent (water wt % hereafter), which is in agreement with that derived from the in situ measurements by Curiosity’s Sample Analysis at Mars instrument. However, the sensitivity tests show that uncertainties exist due to the combination of several factors including modelling bias, instrumental issue, and different sensing techniques. The derived mineral abundances using the orbital data are not fully consistent with that derived by Curiosity, and the discrepancy may be due to a combination of dust cover, texture, and particle size effects, as well as the effectiveness of the quantitative model. Conclusions. The ground-truth data from Curiosity provide a critical calibration point for the quantitative method used in the orbital remote-sensing observations. Our analysis indicates that the method presented here has great potential for mapping the water content and mineral abundances on Mars, but caution must be taken when using these abundance results for geological interpretations.

A methodology for quantitative analysis of hydrated minerals on Mars with large endmember library using CRISM near-infrared data

Hydrated minerals are good indicators of aqueous environments on Mars. Accurate mineral species identification and quantitative estimation of their abundance is very important for understanding past and present geologic and climatic processes of Mars. We present a novel methodology to analyze hydrated minerals using the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data. The methodology is driven by a sparse unmixing model, which can select the optimal subset of signatures from a large endmember library to best model mixed spectra. Laboratory measured spectra of minerals and rocks, scene-derived spectra of common components such as dust and synthetic flat and pure slope spectra are used to populate an endmember library. CRISM and the endmember library reflectance spectra are converted to single-scattering albedo with the Hapke radiative transfer model. The single-scattering albedos of the CRISM and endmember library spectra are then L1 normalized to eliminate the effects of the different measurement conditions between laboratory and orbital data. The sparse unmixing algorithm is finally applied to CRISM normalized single-scattering albedo data using the spectral library. Mineral identification and quantitative analysis are accomplished at the same time. The methodology shows good performance in synthetic and laboratory mineral mixture suites. Examples of six CRISM targeted mode images in three locations (Nili Fossae, Northeast Syrtis Major and Kashira crater), which have been previously thoroughly studied, were analyzed in detail in this study. In comparison with previous studies, our methodology identifies the mineral deposits detected through more manually intensive methods by expert analysts while simultaneously determining the mineral abundances. Furthermore, this new method provides an objective pathway to the determination of mineral presence from a large library of potential options. As an example of unexpected results, we detected putative serpentine in the Nili Fossae images for the first time. Even though the typical diagnostic spectral features used to identify minerals directly from CRISM data are obscured due to the mixing among mineral phases, T-test analyses of serpentine abundance provide critical statistical proof of its presence. Overall, the methodology we present works well for hydrated mineral detection with CRISM data and could provide a rigorous, objective method to map mineralogy in planetary hyperspectral remotely sensed data.

High-resolution investigations of Transverse Aeolian Ridges on Mars

Transverse Aeolian Ridges (TARs) are the most pervasive aeolian feature on Mars. Their small size requires high-resolution data for thorough analyses. We have utilized Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) and High Resolution Image Stereo Experiment (HiRISE) images, along with MRO Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) spectroscopic data to study TARs in detail. TAR deposits, along with related dark dune material and layered terrains, have been mapped in six study areas in order to identify sediment pathways and determine whether TARs are sourced locally or from global wind-borne materials. TAR morphology and orientation were mapped in grids within each study area; the results show that TARs are probably locally sourced. We constructed four HiRISE Digital Terrain Models (DTMs) to measure TAR heights, widths, spacing, areas, symmetry, and to calculate sediment volumes. Results show that TARs have average heights of ∼1.5 m, are very symmetrical, and are similar in form to terrestrial megaripples. Orthorectified HiRISE images taken 3 years apart were analyzed for TAR movement and none was found. Superposed craters on equatorial TARs give ages of ∼2 Ma, suggesting that these are relatively ancient and generally inactive aeolian deposits. CRISM data were analyzed over TAR deposits, dark dune material, and light-toned terrains. Although the surfaces were somewhat obscured by dust cover, the results did not show any remarkable difference between TARs and other deposits. We conclude that TARs may be sourced from local materials and form in a similar way to terrestrial megaripples.

Image Simulation and Assessment of the Colour and Spatial Capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three “fully”-simulated image cubes of thirty unique locations on Mars (i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage ( $\sim9.4 \times 50$ km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.

CRISM 초분광 영상과 표적 탐지 알고리즘을 이용한 Spirit 로버 탐사 지역: Gusev Crater의 광물 분포 조사

Compact Reconnaissance Imaging Spectrometer for Mars(CRISM)은 489개의 밴드를 가지는 화성정찰궤도선의 초분광 카메라로써 이를 이용한 화성 지표의 광물 분포에 대한 많은 연구가 진행되어 왔다. 본 연구에서는 USGS의 스펙트럼 라이브러리를 기반으로 화성 Gusev Crater의 Spirit(Mars Exploration Rover A) 로버 착륙지에 대한 CRISM 영상에 Matched Filter와 Adaptive Cosine Estimator(ACE) 표적 탐지 알고리즘을 적용하여 광물 분포를 확인하고자 하였다. 연구 결과 감람석, 휘석, 자철석 등의 광물들이 Gusev 크레이터의 Columbia Hills에서 탐지되어 Spirit 로버의 지상 탐사 결과와 일치하고 있음을 확인하였다. 본 연구는 그간 CRISM의 광물 분포 연구가 일부 몇 개 밴드의 반사도만을 통해 계산된 광물 지수에 의존하던 것에서 관측 파장 대역 전체를 활용하는 초분광 표적 탐지 알고리즘을 이용한 새로운 적용방법을 제시한 것에 의의가 있다고 할 수 있다. Compact Reconnaissance Imaging Spectrometer for Mars(CRISM) is 489-band hyperspectral camera of Mars Reconnaissance Orbiter(MRO) that provided data used on many mineral researches over Martian surface. For the detection of minerals in planet, mineral index using a few spectral bands have been used. In this study, we applied Matched Filter and Adaptive Cosine Estimator(ACE) target detection algorithm on CRISM data over Gusev Crater: landing site of Spirit(Mars Exploration Rover A) to investigate its mineral distribution. As a result, olivine, pyroxene, magnetite, etc. is detected at Gusev Crater's Columbia Hills. These results are corresponding to the Spirit rover's field survey result. It is expected that hyperspectral target detection algorithms can be used as effective and easy to use method for the detection and mapping of surface minerals in planet.

Extensive aqueous deposits at the base of the dichotomy boundary in Nilosyrtis Mensae, Mars

Thermal emission imaging system (THEMIS) and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) spectral datasets were used to identify high bulk SiO2 and hydrated compositions throughout the Nilosyrtis Mensae region. Four isolated locations were identified across the region showing short wavelength silicate absorptions within the 8–12μm spectral region, indicating surfaces dominated by high Si phases. Much more extensive exposures of hydrated compositions are present throughout the region, indicated by a spectral absorption near 1.9μm in CRISM data. Although limited in spatial coverage, detailed spectral observations indicate that the hydrated materials contain Fe/Mg-smectites and hydrated silica along with minor exposures of Mg-carbonates and an unidentified hydrated phase. The high SiO2 and hydrated materials are present in layered sediments near the base of topographic scarps at the hemispheric dichotomy boundary, typically near or within low albedo sand deposits. The source of the high SiO2 and hydrated materials appears to be from groundwater discharge from Nili Fossae and Syrtis Major to the south, where there is evidence for extensive aqueous alteration of the subsurface. Although discontinuous, the exposures of high SiO2 and hydrated materials span a wide area and are present in a similar geomorphological context to previously identified deposits in western Hellas Basin. These regional deposits may reflect aqueous conditions and alteration within the adjacent crust of the martian highlands.

Description of CoTCAT (Complement to CRISM Analysis Toolkit)

Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) hyperspectral data have a spatial resolution ranging from 12 to 36 m/pixel allowing the high-resolution mapping of minerals at the surface of Mars. However, the signal-to-noise ratio (SNR) makes the discrimination of minerals with close spectral signature such as hydrated minerals challenging. We describe here a pipeline to be used as complement to CRISM Analysis Toolkit (CAT) together with different ratioing methods used to highlight the signal. We present tests on library spectra artificially noised as well as on CRISM data. These tests show that our pipeline is efficient to improve the visualization and the qualitative analysis CRISM data with an SNR higher than 20.

Visible–near infrared spectra of hydrous carbonates, with implications for the detection of carbonates in hyperspectral data of Mars

We present visible–near infrared (VNIR, 0.35–5μm) spectra for a suite of hydrous carbonates that may be relevant to the surface of Mars. This includes VNIR spectra for ikaite, nesquehonite, synthetic monohydrocalcite and lansfordite over the 0.35–2.5μm range that are new to the literature. The spectral features of the hydrous carbonates are dominated by absorptions at ∼1.0, 1.2, 1.4–1.5, 1.9 and 2.8μm that are due to overtones and combinations of fundamental water and hydroxyl vibrations. Absorptions due to (CO3)2−, Mg-OH, Fe-OH, and/or water are seen at ∼2.3–2.5, 3.4, and 3.9μm in hydrous Mg and Mg–Fe3+ carbonates containing hydroxyl groups, but are weaker than in the common anhydrous carbonates. When present in the hydrous carbonates, the positions of the centers of the 2.3μm and/or 2.5μm absorptions are often shifted relative to the anhydrous carbonates, which may be diagnostic. Some or all of the (CO3)2− absorptions typical of anhydrous carbonates are weak to absent in the hydrous carbonates, and thus this group may be difficult to distinguish from other hydrous minerals like sulfates, phyllosilicates or chlorides in Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data using standard spectral search parameters for anhydrous carbonates. We present strategies for recognizing hydrous carbonates in CRISM data using combinations of spectral parameters that measure the intensity and shape of the water-related absorptions in these minerals.

Integrating CRISM and TES hyperspectral data to characterize a halloysite-bearing deposit in Kashira crater, Mars

We present morphologic observations and spectral modeling results of a large, kaolin-group mineral-bearing deposit within Kashira crater in the southern highlands of Mars. We employ both non-linear unmixing of Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) visible to near-infrared (VNIR) reflectance data and linear unmixing of Thermal Emission Spectrometer (TES) thermal infrared (TIR) emissivity data to quantitatively analyze the kaolin-group mineral within this deposit. We use a novel approach for quantitative analysis of CRISM data through non-linear unmixing with in-scene, orbitally-derived endmembers combined with laboratory measured endmembers. Results from this approach indicate that the deposit within Kashira crater is best modeled as a combination of surrounding spectral units (i.e., in-scene derived endmembers) with the addition of the kaolin-group mineral halloysite. Linear unmixing of TES data suggest that the deposit contains ∼30% halloysite, a result that is supported by a sensitivity analysis. Potential formation mechanisms for this deposit include hydrothermal alteration, arid-environment pedogenic weathering of a basaltic mound deposit, or pedogenic weathering of a volcanic ash deposit. Our modeling results offer a quantitative reconciliation of the CRISM and TES datasets, and provide a consistent mineralogy from spectral unmixing for an aqueous alteration mineral-bearing deposit on Mars using a combined analysis of both VNIR and TIR hyperspectral data.

The spectral variability of kieserite (MgSO4·H2O) with temperature and grain size and its application to the Martian surface

AbstractWe spectrally characterize (λ = 0.35–10 µm) the low‐humidity polymorph of kieserite (MgSO4·H2O), which is abundant on Mars and likely present on Europa, at various grain sizes and temperatures (100–300 K) relevant to the surfaces of Mars and Europa. Compositional analysis of these surfaces often relies on remote sensing using imaging spectrometers such as Mars Reconnaissance Orbiter Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), Mars Express Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité, and Galileo Near‐Infrared Mapping Spectrometer. To estimate surface abundances from these observations, well‐characterized laboratory spectra are required for comparison. Several variables, including temperature and grain size, affect the observed spectra and must be quantified in the laboratory to more confidently evaluate the returned data. Certain spectral features of kieserite exhibit predictable variability with changes in temperature and grain size that may be exploited to better understand the nature of kieserite on the surface of Mars. For instance, trends in our spectral analysis suggest that absorption features centered at λ < 3.0 µm were primarily sensitive to temperature changes, while features at λ > 3.0 µm were additionally sensitive to grain size changes. We compare our laboratory spectra with selected CRISM data of suspected Martian kieserite and assess the inherent uncertainty that exists in using band center minima to determine surface composition. Incorporation of these temperature and grain size‐specific spectra into linear mixture models of planetary surface spectra will improve the compositional interpretation and contribute to our understanding of surface geochemistry and chemical evolution.