玉兔号月球车巡视点矿物丰度及粒径分布高光谱反演

矿物的类型、丰度及其粒径分布对理解月球和行星表面曾经存在过怎样的地质演化过程具有重要的意义。本文提出基于辐射传输模型和稀疏分解模型反演矿物丰度及其粒径分布的方法,利用辐射传输模型计算各矿物端元不同粒径的单次散射反照率以构建解混光谱库,然后基于稀疏分解算法得到在每个可观测像元的端元最优丰度和粒径分布。利用实验室测量数据进行验证,表明本文方法具有较高的精度。最后根据玉兔号月球车的实地测量光谱数据,利用本文方法获得了其矿物的丰度及粒径分布,结果显示,辉石、橄榄石、斜长石、熔融玻璃和钛铁矿的丰度在4个观测点的平均丰度分别为28.1%、4.5%、39%、28%、0.4%,辉石的平均粒径为166.02μm,橄榄石为8.34μm,斜长石为196.31μm,熔融玻璃为44.21μm,一定程度上表明在这些观测点不同矿物对太空风化的响应不同。     

火星表面含水矿物探测进展

火星表面含水矿物类型识别和空间分布特征研究对圈定火星表面生命活动有利区域和探索可能存在的火星生命形式具有重要科学意义。本文总结了20世纪90年代以来火星表面含水矿物的探测进展,从火星轨道器光谱仪遥感探测、着陆器和巡视器就位探测两方面介绍了矿物探测使用的数据源,重点阐述了目前火星表面已经探测到的各类含水硅酸盐矿物、硫酸盐矿物、碳酸盐矿物、氯盐及高氯酸盐矿物等含水矿物的光谱特征、矿物具体类别及分布特征,分析了火星表面含水矿物定量反演的主要方法与地质意义。最后从比较行星学角度倡议开展地球和火星含水矿物形成环境和形成过程的类比研究。     

火星伊西底斯平原的壁垒撞击坑：遥感分析及环境启示意义

伊西底斯平原是中国首次火星探测任务“天问一号”的预选着陆区之一,地表广泛发育指纹地形和壁垒撞击坑。壁垒撞击坑具有一层或多层流态化的连续溅射物,一般被认为是地下富含水/冰的地层（以下简称“地下水冰层”）与超高速撞击体作用的产物,是分析火星当前和过去地下水冰层的关键研究对象。基于高分辨率影像,本文采用影像解译、形貌分析、撞击坑统计定年等方法,开展了伊西底斯平原壁垒撞击坑的遥感综合分析。解译发现该平原目前共存在120个壁垒撞击坑,它们的最小直径为1.5 km,连续溅射物平均分布在撞击坑周围约1.3个半径范围之内,且外观不规则程度（弯曲度）高。采用撞击坑直径—频率分布定年方法确定了15个连续溅射物保存完整的壁垒撞击坑的绝对模式年龄（地质年龄）,发现它们全部形成于亚马逊纪。根据连续溅射物与指纹地形的空间叠加关系,本文推断构成指纹地形的锥状物形成于2.38—3.24 Ga（早亚马逊纪）。它们更可能是大量岩浆流过湿润或冰冻地面时下覆（融化）水分迅速气化而发生爆裂并冲破岩浆形成的无根锥/伪火山口。根据撞击坑直径和挖掘深度之间的经验关系,本文揭示伊西底斯平原有利于形成壁垒撞击坑的地下水冰层的平均埋藏深度至少稳定保持在1 km,并可能因火星自转倾角周期性变化对气候的影响而发生0.1 km的小幅上升或下降。本文研究成果对于重建伊西底斯平原地下水冰环境演变历史具有重要科学意义,并有望得到中国“天问一号”巡视器和轨道器次表层探测雷达探测结果的验证。     

热红外遥感火星矿物填图方法初步研究及应用

利用热辐射光谱仪（TES）数据,对火星进行热红外遥感矿物填图。通过对几种典型填图方法的简要介绍,结合火星环境及方法的使用条件,对填图结果进行简单比较,初步分析了填图方法的差异性,为火星矿物填图的进一步研究提供了基础,并为方法和模型的进一步改进提供了依据。     

融合数据内部变化信息的丰度估计算法

丰度估计(AE)是从高光谱图像中识别地物的关键预处理技术。由于线性模型的可解释性以及数学上的可操作性,基于该模型的线性回归技术CLR(Constrained Linear Regression)在丰度估计中受到了广泛关注。目前,该方法仅仅考虑到了估计数据与被估计数据之间的能量相似性,没有考虑数据内部的变化信息之间的相似性,比如一阶梯度之间的相似性以及二阶梯度之间的相似性。为了提高丰度估计精度,本文提出了融合数据内部变化信息的稀疏低秩丰度估计算法。首先通过增加一阶梯度和二阶梯度的约束项改进传统的丰度估计的数学模型。其次,通过采用范数不等式和优化理论证明了在约束条件下,该模型的有效性及该模型在相关领域的可拓展性。接着,采用辅助变量将改进的数学模型变为增强拉格朗日函数。最后,采用交替双向乘子技术ADMM(Alternating Direction Method of Multipliers)求解该模型并估计高光谱图像的丰度。经仿真实验和实际高光谱图像的实验证明该方法能够改善仿真数据和实际高光谱数据的丰度估计的效果,特别是当端元的丰度存在丰富的变化细节时,丰度估计的精度和抗噪性能均优于当前较流行的丰度估计算法。     

块状岩石矿物组分热红外光谱反演实验研究

针对地面研究用岩石的热红外光谱反演其矿物组分过程中,由于自然岩石内矿物组分分布不均匀,给确定观测区域内矿物组分的精确值造成困难的问题,该文采用块状矿物拼接的方法模拟自然岩石,使模拟岩石的矿物组分可以精确获取。进一步,针对模拟岩石制订旋转试样法观测方案,从理论上研究该方案存在的观测误差,并通过光谱解混验证其观测精度。     

干旱区土壤水分遥感反演与同化模拟系统研究

利用遥感反演和同化模拟方法估算大范围陆表土壤水分,建立了适用于干旱区的土壤水分反演模型。在.NET平台下运用C#、IDL与ArcEngine控件,对反演模型与同化模拟模型进行了软件实现,并集成为土壤水分遥感反演与同化模拟系统,为环保部门获取大范围土壤水分信息提供了支撑软件工具。     

附有病态约束矩阵的等式约束反演问题研究

讨论等式约束反演问题的求解方法,给出约束矩阵的病态性的定义及相应的评价方法,推导约束矩阵病态对反演结果的影响公式,通过简单的例子说明约束矩阵病态对反演结果的影响;采用处理约束矩阵病态的SVD方法.有效解决约束矩阵病态造成反演结果极不稳定的问题.最后设计多个反演方案进行计算,验证方法的有效性和可行性.     

高斯混合模型在星载激光全波形数据反演树高中的应用

全波形激光雷达后向散射回波,通过分解返回波形获取多种地物属性信息,在森林结构参数反演方面具有显著的优势,但是,当波形变形或者存在饱和度和前向散射时,高斯分量参数确定不准确以及有效波形起始位置不准确,降低波形分解精度。本文采用高斯混合模型对波形进行拟合,利用期望最大算法估计混合模型参数,抑制高斯分量初值敏感问题,特别是在大范围树高估算且要求一定精度的时候,以确定波形分解并且反演树高。本算法基于C++编程实现,实验结果表明,高斯混合模型能较好地拟合GLAS波形数据且对树高提取精度提升明显,该方法有着很好的有效性、稳定性和精确性。     

小波分析在重力界面反演中的应用

基于Parker-Oldenburg反演方法,分析了低通滤波器B(K)的不同阈值对位场分离的影响。分别采用小波变换和低通滤波对青藏高原地区布格重力异常进行了位场分解和莫霍面反演,并将反演结果与地震资料作比较。结果表明,在重力位场分解中小波多尺度分解可以代替低通滤波器B(K),避免了阈值的选取。     

Comparative analysis on utilisation of linear spectral unmixing and band ratio methods for processing ASTER data to delineate bauxite over a part of Chotonagpur plateau,Jharkhand, India

We have attempted comparative analysis of the utility of linear spectral unmixing (LSU) method and band ratios for delineating bauxite from laterite within the lateritic bauxite provinces of Chotonagpur Plateau, Jharkhand of India. This was attempted based on processing of visible–near infrared (VNIR) and shortwave infrared (SWIR) spectral bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. In LSU method, spectral features of main constituent minerals of lateritic bauxite are used to decompose the pixel spectra to estimate the relative abundance of bauxite and laterite in each pixel to spatially delineate bauxite within laterite. We have also compared the bauxite map derived using LSU method with bauxite maps of two band ratios in terms of spatial disposition of bauxite. We also have attempted to relate the abundance values of pixels of LSU-based bauxite map with band ratio values of bauxite pixels of two selected bauxite indices.     

Mapping of bauxite mineral deposits in the northern region of Saudi Arabia by using Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite data

Mineral deposit mapping is very essential for sustainable and eco-friendly exploitation of natural resources. The Kingdom of Saudi Arabia has abundant natural resources such as natural gas, oil and minerals. It reserves high quantity of minerals such as phosphates, bauxites, copper, gold and other industrial minerals. The red soil regions located in Hail and Qassim provinces of Saudi Arabia have rich amount of bauxite (major aluminum ore) deposits. In order to initiate the focus on mapping of mineral deposits along this area, standardized hyper-spectral analysis has been carried out by using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. The spectral signature of gibbsite (major element in bauxite) samples is analyzed with reference to the spectral features of gibbsite in the visible near infrared and short-wave infrared bands electromagnetic spectrum. Advanced hyper-spectral transformations such as minimum noise fraction function and pixel purity index have been performed to identify the target end-member. The existence of the mineral is confirmed by comparing the spectral signatures of the end-member with the predefined spectral plots of ASTER and United States Geological Survey spectral libraries. Finally, the end-members are mapped and their abundance is estimated in 0–1 scale. The study has opened up new areas for mapping of bauxite deposits in the area and leads to eco-friendly exploitation of natural resources. It also validates the high potential of ASTER multispectral satellite data for the exploration and mapping of mineral resources.     

Spatial distribution of altered minerals in the Gadag Schist Belt (GSB) of Karnataka,Southern India using hyperspectral remote sensing data

Spatial distribution of altered minerals in rocks and soils in the Gadag Schist Belt (GSB) is carried out using Hyperion data of March 2013. The entire spectral range is processed with emphasis on VNIR (0.4–1.0 μm) and SWIR regions (2.0–2.4 μm). Processing methodology includes Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes correction, minimum noise fraction transformation, spectral feature fitting (SFF) and spectral angle mapper (SAM) in conjunction with spectra collected, using an analytical spectral device spectroradiometer. A total of 155 bands were analysed to identify and map the major altered minerals by studying the absorption bands between the 0.4–1.0-μm and 2.0–2.3-μm wavelength regions. The most important and diagnostic spectral absorption features occur at 0.6–0.7 μm, 0.86 and at 0.9 μm in the VNIR region due to charge transfer of crystal field effect in the transition elements, whereas absorption near 2.1, 2.2, 2.25 and 2.33 μm in the SWIR region is related to the bending and stretching of the bonds in hydrous minerals (Al-OH, Fe-OH and Mg-OH), particularly in clay minerals. SAM and SFF techniques are implemented to identify the minerals present. A score of 0.33–1 was assigned for both SAM and SFF, where a value of 1 indicates the exact mineral type. However, endmember spectra were compared with United States Geological Survey and John Hopkins University spectral libraries for minerals and soils. Five minerals, i.e. kaolinite-5, kaolinite-2, muscovite, haematite, kaosmec and one soil, i.e. greyish brown loam have been identified. Greyish brown loam and kaosmec have been mapped as the major weathering/altered products present in soils and rocks of the GSB. This was followed by haematite and kaolinite. The SAM classifier was then applied on a Hyperion image to produce a mineral map. The dominant lithology of the area included greywacke, argillite and granite gneiss.     

Knowledge-guided data-driven evidential belief modeling of mineral prospectivity in Cabo de Gata,SE Spain

Spurious evidence and spurious spatial associations between target mineral deposits and certain classes of spatial data undermine GIS-based data-driven modeling of mineral prospectivity. In a case study application of data-driven evidential belief functions, such problems were recognized and then, based on sound geological judgment, were addressed accordingly. By invoking knowledge of genetic associations between mineral deposits of the type sought and spatial geological attributes (lithology, fault/fracture density, hydrothermal alteration intensity), spurious spatial associations depicted in ‘original’ evidence maps were addressed by treatment of input spatial data via applications of certain basic GIS functionalities in order to derive ‘treated’ evidence maps. By invoking knowledge of geological processes involved in the formation of mineral deposits of the type sought and knowledge of how operations to combine evidence maps function, the integration of evidence maps was guided such that the inter-play of geological processes involved in the formation of mineral deposits of the type sought is represented in the modeling procedure and such that spurious evidence is filtered and not transmitted into the output map representing likelihood of mineral deposit occurrence in every location within a study area. The results show that: (a) using ‘treated’ evidence maps, instead of ‘original’ evidence maps, results in better mineral prospectivity maps and, thus, (b) knowledge-guided data-driven modeling of mineral prospectivity is better than a ‘purely’ data-driven modeling of mineral prospectivity.     

A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis,United States

This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying urban landscape changes in Indianapolis, Indiana, the United States, and for examining the environmental impact of such changes on land surface temperatures (LST). Three dates of Landsat TM/ETM+ images, acquired in 1991, 1995, and 2000, respectively, were utilized to document the historical morphological changes in impervious surface and vegetation coverage and to analyze the relationship between these changes and those occurred in LST. Three fraction endmembers, i.e., impervious surface, green vegetation, and shade, were derived with an unconstrained least-squares solution. A hybrid classification procedure, which combined maximum-likelihood and decision-tree algorithms, was developed to classify the fraction images into land use and land cover classes. Correlation analyses were conducted to investigate the changing relationships of LST with impervious surface and vegetation coverage. Results indicate that multi-temporal fraction images were effective for quantifying the dynamics of urban morphology and for deriving a reliable measurement of environmental variables such as vegetation abundance and impervious surface coverage. Urbanization created an evolved inverse relationship between impervious and vegetation coverage, and brought about new LST patterns because of LST's correlations with both impervious and vegetation coverage. Further researches should be directed to refine spectral mixture modeling by stratification, and by the use of multiple endmembers and hyperspectral imagery.     

Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region,Texas, USA

The Google Earth terrain model could prove beneficial for extraction of positional data in the future. At present, only an aging independent benchmark study (Potere, D., 2008. Horizontal position accuracy of Google Earth's high-resolution imagery archive. Sensors, 8, 7973–7981) provides constraints on positional accuracy for Google Earth imagery. In this investigation, we compared virtually traced positions against high-precision (<1 m) field measurements along three stratigraphic unconformity sub-sections in the Big Bend region to determine current positional accuracy for the Google Earth terrain model. A horizontal position accuracy of 2.64 m RMSE_r was determined for the Google Earth terrain model with mean offset distance being 6.95 m. A vertical position accuracy of 1.63 m RMSE_z with mean offset distance of 2.66 m was also calculated for the terrain model. Results suggest data extracted from the Google Earth terrain model could plausibly be used in future studies. However, we urge caution in using Google Earth data due to limited information disclosures by developers.     

Atmospheric pollution assessment near potential source of natural aerosols in the South Gobi Desert region,China

ABSTRACT

Rapid economic growth, a high degree of urbanization and the proximity of a large number of desert and semidesert landscapes can have a significant impact on the atmosphere of adjacent territories, leading to high levels of atmospheric pollution. Therefore, identifying possible sources of atmospheric pollution is one of the main tasks. In this study, we carried out an analysis of spatial and temporal characteristics of five main atmospheric pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and CO) near potential source of natural aerosols, affecting seven cities (Wuhai, Alashan, Wuzhong, Zhongwei, Wuwei, Jinchang, Zhangye), located in immediate proximity to the South Gobi deserts. The results, obtained for the period from 1 January 2016 to 31 December 2018, demonstrate total concentrations of PM_2.5 and PM₁₀ are 38.2 ± 19.5 and 101 ± 80.7 μg/m³ exceeding the same established by the Chinese National Ambient Air Quality Standard (CNAAQS), being 35 and 70 μg/m³, respectively. Based on the data from Moderate Resolution Imaging Spectroradiometer (MODIS) for the whole period, Clean Сontinental (71.49%) and Mixed (22.29%) types of aerosols prevail in the region. In the spring and winter seasons maximum concentrations of pollutants and high values of Aerosol Optical Depth (AOD) in the region atmosphere are observed. PM_2.5 and PM₁₀ ratio shows the presence of coarse aerosols in the total content with value 0.43. The highest concentrations of pollutants were in the period of dust storms activity, when PM_2.5 and PM₁₀ content exceeded 200 and 1000 µg/m³, and AOD value exceeded 1. UV Aerosol Index (UVAI), Aerosol Absorbing Optical Depth (AAOD), and Single Scattering Albedo (SSA), obtained from Ozone Monitoring Instrument (OMI), demonstrate the high content of dust aerosols in the period of sandstorms. Analysis of backward trajectories shows that dust air masses moved from North to Northwest China, affecting large deserts such as Taklamakan, Gurbantunggut, Badain Jaran, Tengger, and Ulan Buh deserts.     

Use of geo-spatial information and technologies for analyzing morphological changes in the Greater Visakhapatnam coastal region,east coast of India

The objective of this study was to investigate the land use/land cover, landforms, shoreline and coastal regulation zone (CRZ) changes of Greater Visakhapatnam coastal region using Indian Remote Sensing-IRS P6 (Resourcesat-I) satellite data and collateral information. Prominent changes have been observed during the past 30 years through land use/land cover analyzes which clearly indicate that thecoastal regulatory zones have altered in respect of both natural and anthropogenic activities. Various geomorphic units were identified and confirmed with appropriate field work. Significant changes have been recognized in the shoreline map, which denote that the area of erosional shoreline is larger than the accretional and stable prone shoreline. The availability of high resolution data has helped to prepare large-scale maps for implementation of CRZ measures. The results were promising and suggest that the modern geo-spatial information and technological tools are extremely helpful for conducting coastal morphological studies.