Mars Data Research Articles

Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for (18.4%), (18.5%), (57.4%), (19.0%), and (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data.

Updated Perspectives and Hypotheses on the Mineralogy of Lower Mt. Sharp, Mars, as Seen From Orbit

AbstractPrevious studies have shown that Mt. Sharp has stratigraphic variation in mineralogy that may record a global transition from a climate more conducive to clay mineral formation to one marked by increased sulfate production. To better understand how small‐scale observations along the traverse path of NASA's Curiosity rover might be linked to such large‐scale processes, it is necessary to understand the extent to which mineral signatures observed from orbit vary laterally and vertically. This study uses newly processed visible‐shortwave infrared Compact Reconnaissance Imaging Spectrometer for Mars data and corresponding visible images to reexamine the mineralogy of lower Mt. Sharp, map mineral distribution, and evaluate stratigraphic relationships. We demonstrate the presence of darker‐toned strata that appears to be throughgoing with spectral signatures of monohydrated sulfate. Strata above and below this zone are lighter‐toned and contain polyhydrated sulfate and variable distribution of Fe/Mg clay minerals. Clay minerals are observed at multiple stratigraphic positions; unlike the kieserite zone these units cannot be traced laterally across Mt. Sharp. The kieserite zone appears to be stratigraphically confined, but in most locations the orbital data do not provide sufficient detail to determine whether mineral signatures conform to or cut across stratigraphic boundaries, leaving open the question as to whether the clay minerals and sulfates occur as detrital, primary chemical precipitates, and/or diagenetic phases. Future observations along Curiosity's traverse will help distinguish between these possibilities. Rover observations of clay‐bearing strata in northwest Mt. Sharp may be more reflective of local conditions that could be distinct from those associated with other clay‐bearing strata.

Recording laser-induced sparks on Mars with the SuperCam microphone

The SuperCam instrument suite onboard the Mars 2020 Perseverance rover includes a microphone used to complement Laser-Induced Breakdown Spectroscopy investigations of the surface of Mars. The potential of the SuperCam microphone has already been demonstrated for laser ablation under Earth atmosphere in our preliminary study with a small set of samples and fixed experimental conditions. This new experimental study, conducted under Mars atmosphere, explores all the main environmental, instrumental and target dependent parameters that likely govern the laser-induced acoustic signal that will be generated on Mars. As SuperCam will observe targets at various distances from the rover, under an atmospheric pressure that follows diurnal and seasonal cycles, this study proposes a sequence of corrections to apply to Mars data in order to compare acoustic signal from targets sampled under different configurations.In addition, 17 samples, including pure metals but also rocks and minerals relevant to Mars' surface were tested to study the influence of target properties and laser-matter interactions on the acoustic signal and the ablated volume. A specific behavior is reported for metals and graphite, which rapidly disperse the incoming laser energy through heat diffusion. However, for other minerals and rocks, the growth of the crater is seen to be responsible for the shot-to-shot decrease in acoustic energy. As a consequence, it is confirmed that monitoring the acoustic energy during a burst of laser shots could be used to estimate the laser-induced cavity volume. Moreover, the amount of matter removed by the laser is all the more important when the target is soft. Hence, the decreasing rate of the acoustic energy is correlated with the target hardness. These complementary information will help to better document SuperCam targets.

Rate of infection following revision anterior cruciate ligament reconstruction and associated patient- and surgeon-dependent risk factors: Retrospective results from MOON and MARS data collected from 2002 to 2011.

Infection is a rare occurrence after revision anterior cruciate ligament reconstruction (rACLR). Because of the low rates of infection, it has been difficult to identify risk factors for infection in this patient population. The purpose of this study was to report the rate of infection following rACLR and assess whether infection is associated with patient- and surgeon-dependent risk factors. We reviewed two large prospective cohorts to identify patients with postoperative infections following rACLR. Age, sex, body mass index (BMI), smoking status, history of diabetes, and graft choice were recorded for each patient. The association of these factors with postoperative infection following rACLR was assessed. There were 1423 rACLR cases in the combined cohort, with 9 (0.6%) reporting postoperative infections. Allografts had a higher risk of infection than autografts (odds ratio, 6.8; 95% CI, 0.9-54.5; p = .045). Diabetes (odds ratio, 28.6; 95% CI, 5.5-149.9; p = .004) was a risk factor for infection. Patient age, sex, BMI, and smoking status were not associated with risk of infection after rACLR.

Automatic preprocessing of laser-induced breakdown spectra using partial least squares regression and feed-forward artificial neural network: Applications to Earth and Mars data

Due to its relatively simple and versatile nature, laser-induced breakdown spectroscopy experiments can yield enormous amount of data that normally needs to be preprocessed to remove background signal, electron continuum, and noise, and for some applications, correct for the instrument response function and normalize the signal prior to conducting spectroscopic analysis. In experiments where the focus is on the analysis of samples of similar composition, preprocessing can be repetitive and tedious. We show that preprocessing of such LIBS data can be performed in an automated or semi-automated manner using machine learning tools. To demonstrate this approach, we apply partial least squares regression and artificial neural networks on two laser-induced breakdown spectra datasets. The first dataset is used to develop predictive models for abundances of various elements in geological samples analyzed by a laboratory model of ChemCam. The second dataset consists of spectra obtained from ChemCam as it interrogates Martian targets. We show that using the two machine learning techniques, we can predict the preprocessed spectra of samples with a relatively high accuracy for both datasets.

Toward the geological significance of hydrated silica detected by near infrared spectroscopy on Mars based on terrestrial reference samples

Hydrated silica detected on the martian surface, from both orbital and in-situ data, is an indicator of past aqueous conditions. On Earth, several near infrared (NIR) spectral criteria can be used to discriminate silica phases (e.g. opal-A, opal-CT and chalcedony) and their formation processes. We have applied these spectral criteria to Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data in order to investigate the geological origin of hydrated silica on Mars. We used two spectral criteria: (i) the crystallinity spectral criteria on the 1.4- and 1.9 μm absorption bands to distinguish between amorphous (opal-A and hydrated glasses) and more crystalline (opal-CT and chalcedony) varieties of silica, and (ii) the Concavity-Ratio-Criterion (CRC) to differentiate opals of hydrothermal origin from weathering origin. We first adapted the CRC measurements on terrestrial samples to make them comparable to CRISM measurements on Mars: we resampled our terrestrial spectra down to the CRISM resolution, and tested the martian pressure effect on spectral signatures. Then, we selected several areas over nine sites where hydrated silica has been detected on Mars, on the basis of good quality detections. Our results show that two main types of spectra can be distinguished, and these are consistent with two distinct geomorphological contexts proposed by Sun and Milliken (2018): amorphous and/or dehydrated silica-bearing bedrock deposits, and more crystalline and/or hydrated silica-bearing aeolian deposits. The concavity criterion also indicates silica origins that are in agreement with most of the hypothesized geological origins proposed in the literature. Although these results need further strengthening, they are promising for the use of NIR signatures as means of investigating the processes of hydrated silica on Mars.

Missing Value Imputation via Clusterwise Linear Regression

In this paper a new method of preprocessing incomplete data is introduced. The method is based on clusterwise linear regression and it combines two well-known approaches for missing value imputation: linear regression and clustering. The idea is to approximate missing values using only those data points that are somewhat similar to the incomplete data point. A similar idea is used also in clustering based imputation methods. Nevertheless, here the linear regression approach is used within each cluster to accurately predict the missing values, and this is done simultaneously to clustering. The proposed method is tested using some synthetic and real-world data sets and compared with other algorithms for missing value imputations. Numerical results demonstrate that the proposed method produces the most accurate imputations in MCAR and MAR data sets with a clear structure and the percentages of missing data no more than 25%

Study of Exospheric Neutral Composition of Mars observed from Indian Mars Orbiter Mission

The exospheric composition data of Mars for the period 2014–15 has been extracted and analysed using the observations carried out by the MENCA (Mars Exospheric Neutral Composition Analyser) payload on-board the Mars Orbiter Mission (MOM) launched by India. The latitude, longitude, altitude and solar zenith angle coverage of the partial pressure values of different exospheric constituents are determined and assigned to create a new data-set with orbit-wise data assimilation particularly between 260 and 600 km altitude range. Apart from getting the results on mean individual orbits’ partial pressure profiles, the variations of the total as well as partial pressures are studied with respect to the distribution of the major atmospheric constituents and their dependence on solar activity. In particular, CO2 and O variations are considered together for any differential effects due to photolysis and photo-ionisation. The results on the gradual reduction in densities due to decreasing daily mean sunspot numbers and strong response of CO2 and O pressures to solar energetic particle events like that of 24 December 2014 are presented.

A New Regression-Based Approach to Estimate the Shape Parameter of MQ-RBFs in a Free Convection Problem

Abstract In this study, a novel procedure is proposed to determine the shape parameter of multiquadric (MQ) radial basis function (RBF) utilizing multivariate adaptive regression splines (Mars) in a free convection problem. Input data (truth data) of Mars is prepared by applying MQ-RBF pseudospectral (PS) method to a free convection problem in a cavity with differentially heated vertical walls. Shape parameter determination in this step is also proposed. The input data obtained by the numerical method and by the proposed way to determine shape parameter is used in the package earth of R project, and a model function is built to estimate the shape parameter. Then, instead of using the proposed search inside the numerical method, the model function determines the shape parameter at any truth data. Results are also compared with a benchmark study, and good agreement is observed in the same free convection problem. The model function built is also tested against the results of the original method.

Terra Mars: When Earth Shines on Mars through AI’s Imagination

Terra Mars presents artistic renderings of Mars with visual reference to our very own planet Earth. The author trained an artificial neural network with topographical data and satellite imagery of Earth so that it can learn the relation between them. The author then applied the trained model to topographical data of Mars to generate images that resemble satellite imagery of Earth. This project suggests a new approach to creative applications of artificial intelligence—using its capability of remapping to broaden the domain of artistic imagination.

Novel pendrin inhibitor attenuates airway hyperresponsiveness and mucin expression in experimental murine asthma

Novel pendrin inhibitor attenuates airway hyperresponsiveness and mucin expression in experimental murine asthma

Abstract TP585: Long-Term Outcomes in Unruptured Brain Arteriovenous Malformation Patients: The Multicenter Arteriovenous Malformation Research Study (MARS)

Introduction: Accurately balancing risks of interventional treatment and intracranial hemorrhage (ICH) in the untreated course of unruptured brain arteriovenous malformation (uBAVM) patients is critical for optimal management. Observational studies of uBAVM afford an opportunity to address important gaps and previous criticisms of randomized data to help guide treatment decisions and assess long-term risk/benefit ratio. We previously published an individual patient data meta-analysis (IPDMA) in 4 MARS cohorts and identified ICH presentation and increasing age as significant predictors of ICH during follow-up, but was not powered to detect predictors in those with uBAVM. Thus, the goals of this project are to identify risk factors for ICH in uBAVMs, to estimate the risk with precision, and to create personalized, risk-prediction models. Methods: MARS is an international, multi-center study of 11 cohorts with target enrollment of 4,500 uBAVM patients ascertained through population-based or referral-based studies. We are harmonizing both retrospective and prospective data, including clinical, lifestyle, imaging, and angiographic factors. Treatments, complications, and functional outcomes (physician and patient-reported) will be updated annually between 2018-2022. We propose to: 1) identify predictors of outcome in uBAVMs using IPDMA; 2) test whether long-term outcomes differ by treatment using statistical approaches for causal inference and unbiased estimates; 3) compare treatment outcomes in randomized and non-randomized data to address generalizability; and 4) validate models and provide a novel tool for calculating individualized risks. Eligible sites have: a) prior BAVM publications; b) data from a minimum of 100 uBAVM patients; c) agree to random outcome adjudication; and d) agree to MARS data sharing policy. Discussion: The NIH-funded MARS consortium will provide important and comprehensive characterization of the untreated and treated course of uBAVMs, using large observational datasets and sophisticated epidemiological approaches. The data and models generated will be a useful resource for decision-making. We welcome participation from eligible sites with longitudinal data on uBAVM patients

Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM

We propose a new algorithm, hypothesis-based estimation with regularization (HyBER), to reconstruct and denoise hyperspectral image data without extra statistical assumptions. The hypothesis test selects the best statistical model approximating measurements based on the data only. A regularized maximum log-likelihood estimation method is derived based on the selected model. A spatially dependent weighting on the regularization penalty is presented, substantially eliminating row artifacts that are due to nonuniform sampling. A new spectral weighting penalty is introduced to suppress varying detector-related noise. HyBER generates reconstructions with sharpened images and spectra in which the noise is suppressed, whereas fine-scale mineral absorptions are preserved. The performance is quantitatively analyzed for simulations with 0.002% relative error, which is better than the traditional nonstatistical methods (baselines) and statistical methods with improper assumptions. When applied to the Mars Reconnaissance Orbiter's Compact Reconnaissance Imaging Spectrometer for Mars data, the spatial resolution and contrast are approximately two times better as compared to map projecting data without the use of HyBER.

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.

Simulation of the future sea level contribution of Greenland with a new glacial system model

Abstract. We introduce the coupled model of the Greenland glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dynamics, the model of basal hydrology HYDRO and a parameterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, imposing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961–1990 standard climatology derived from simulations of the regional atmosphere model MAR with ERA reanalysis boundary conditions. For the palaeo-part of the spin-up, we add the temperature anomaly derived from the GRIP ice core to the years 1961–1990 average surface temperature field. For our projections, we apply surface temperature and surface mass balance anomalies derived from RCP 4.5 and RCP 8.5 scenarios created by MAR with boundary conditions from simulations with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Further on, the impact of elevation–surface mass balance feedback, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation–surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we investigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temperature and subglacial discharge are about equally important for the melting of the examined outlet glaciers.

Jupiter's Influence on the Building Blocks of Mars and Earth

AbstractRadiometric dating indicates that Mars accreted in the first ~4 Myr of the solar system, coinciding with the formation and possible migration of Jupiter. While nebular gas from the protoplanetary disk was still present, Jupiter may have migrated inward and tacked at 1.5 AU in a 3:2 resonance with Saturn. This migration excited planetary building blocks in the inner solar system, resulting in extensive mixing and planetesimal removal. Here we evaluate the plausible nature of Mars's building blocks, focusing in particular on how its growth was influenced by Jupiter. We use dynamical simulations and an isotopic mixing model that traces the accretion. Dynamical simulations show that Jupiter's migration causes the late stages of Earth's and Mars's accretion to be dominated by EC (enstatite chondrite)‐type material due to the loss of ordinary chondrite planetesimals. Our analysis of available isotopic data for Mars shows that it consists of approximately ordinary chondrite by mass (2σ). The large uncertainties indicate that isotopic analyses of Martian samples are generally too imprecise to definitely test model predictions; in particular, it remains uncertain whether or not Mars accreted predominantly EC material in the latter stages of its formation history. Dynamical simulations also provide no definitive constraint on Mars's accretion history due to the great variety of dynamical pathways that the Martian embryo exhibits. The present work calls for new measurements of isotopic anomalies in Martian meteorites targeting siderophile elements (most notably Ni, Mo, and Ru) to constrain Mars's accretion history and its formation location.

Raman and reflectance spectroscopy of serpentinites and related hydrated silicates: Effects of physical properties and observational parameters, and implications for detection and characterization on Mars

Raman and high-resolution reflectance spectrometers will play an increasingly important role in future surface exploration of Mars. We undertook a study of the 532 nm Raman and 0.35–2.5 μm reflectance spectral properties of a suite of terrestrial serpentinites and related rocks from the Southern Quebec Ophiolite Belt, Canada in order to: (1) determine what factors control the appearance of their Raman and reflectance spectra; and (2) enable more robust analysis of Raman and reflectance observational data for Mars to be provided by future Mars landed missions. We examined the effects of surface texture, presence of weathered surfaces, sample heterogeneity, grain size (whole rock versus powder) on Raman and reflectance spectra, and of integration time on the Raman spectra. The Raman spectra are characterized by strong induced fluorescence, however they usually still allow the strongest peaks of the major silicate phase (serpentine, tremolite-actinolite, or talc) to be identified. The different serpentine polymorphs (antigorite, chrysotile, lizardite) can also normally be identified by differences in some Raman peak positions. Only a few of the accessory phases are recognizable in the Raman spectra. There is no systematic difference relating the presence or absence of Raman peaks between whole rock and powder spectra. Increasing integration time can allow weak Raman peaks to be more confidently recognized. Reflectance spectra are dominated by the numerous absorption bands of serpentine or talc, making these phases easily identifiable, but also making accessory phases difficult to identify. Factors such as tetrahedrally-coordinated Fe3+, mixed valence Fe (Fe2+/Fe3+), and the presence of octahedrally coordinated Fe2+ in serpentine can also be recognized. As in the Raman spectra, accessory phases are generally not identifiable in the reflectance spectra due to low abundance, weak absorption bands, or because their absorption bands are overlapped by the stronger hydrated silicate absorption bands. In the reflectance spectra the presence of magnetite can be recognized by a lowering of reflectance and a negatively-sloped spectrum. The presence of other opaque phases may be inferred from a lowering of reflectance. Reflectance spectroscopy is generally superior to Raman spectroscopy for identifying the presence of serpentine because of the aforementioned induced fluorescence seen in some of the Raman spectra. Raman and reflectance spectra do not always allow for identification of the same accessory phases, demonstrating their complementarity for analysis of hydrated silicate-dominated rocks.

Interactive visual analysis and classification of hyperspectral imaging data

Hyperspectral imaging is a widely used remote sensing technique in planetary sciences. Captured data consist of arrays of images of the same scene taken at a high number of sensor wavelengths. Studying these data, scientists search to understand, for example, the mineral composition of the surface, or types and kinds of vegetation present in the region. Different mineral or vegetation classes induce spectral features that allow for their identification and mapping. The two main tasks are selecting a subset of bands that best capture the relevant spectral features and separating different mixtures from summary products in these bands. It is common practice that the subsets of bands used in the analysis are predefined based on experience, i.e., without taking into account actual data. Then, classification of the regions is performed by analyzing the summary products. We, instead, propose an approach that allows for data-driven selection of subsets of bands and for a more accurate separation of different mixtures. Our approach relies on an interactive visual analysis using suitable visual encodings and interaction mechanisms. In a first step, we produce a similarity plot of the bands of the hyperspectral imaging data by employing a projection-based dimensionality reduction technique. The similarity plot allows for the selection of most informative bands. In a second step, we apply an automatic hierarchical density-based clustering approach to the pixels of the selected bands. The resulting cluster hierarchy is interactively explored and adjusted using coordinated views of a cluster tree visualization, a parallel coordinate plot of the bands, and a spatial data visualization. Brushing and linking in the coordinated views allows for an intuitive interactive analysis of the bands leading to the desired mineral mapping result. The effectiveness of our approach is demonstrated by applying it to mineral mapping of Compact Reconnaissance Imaging Spectrometer for Mars data and vegetation classification of Airborne Visible/Infrared Imaging Spectrometer data.

Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm

Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm

RETRIEVAL OF MINERAL ABUNDANCES OF THE DELTA REGION IN EBERSWALDE, MARS

Abstract. Eberswalde Crater, a hotspot of Mars exploration, possesses an unambiguous hydrological system. However, little research has been performed on the large-scale mineral abundances retrieval in this region. Hence, we employed hyperspectral unmixing technology to quantitatively retrieve mineral abundances of the delta region in Eberswalde. In this paper, the single-scattering albedos were calculated by the Hapke bidirectional reflectance function from Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data (FRT000060DD) and CRISM spectral library respectively, and a sparse unmixing algorithm was adopted to quantitatively retrieve mineral abundances. The abundance maps show that there are six kinds of minerals (pyroxene, olivine, plagioclase, siderite, diaspore, and tremolite). By comparing minerals spectra obtained from images with corresponding spectra in spectral library, we found the similar trend in both curves. Besides, the mineral abundance maps derived in this study agree well spatially with CRISM parameter maps. From the perspective of mineralogy, the instability of pyroxene and olivine indicates the area in which they distribute is close to provenance, and the original provenance is ultrabasic rock (e.g. peridotite) and basic rock (e.g. gabbro), respectively. And minerals, existing in the area of alluvial fan, also distribute in the outside of alluvial fan, which might be caused by fluid transportation.