MC-ICP-MS锂同位素溶液分析技术与应用

Li同位素是一种新兴的非传统稳定同位素示踪工具,在地质学、地球化学研究中具有广阔的应用前景。目前,Li同位素溶液分析技术主要采用热电离质谱仪（TIMS）和多接收电感耦合等离子质谱仪（MC-ICP-MS）,与TIMS相比,MC-ICP-MS具有分析精度高、样品量少、测试速度快等诸多优点。本研究团队近年来建立了MC-ICP-MS高精度Li同位素分析方法,在天然样品、标准物质以及石英包裹体的Li同位素测定中都取得了良好结果。以此为依托,研究团队建立了适用于西藏本地岩石成因研究的Li同位素地质端元,并将Li同位素应用于青藏高原岩石圈结构及其隆升历史、川西碳酸岩型稀土矿床富集机制、四川呷村VMS型矿床成矿流体来源和四川甲基卡硬岩型Li矿床富集机理等方面。本文比较详细地综述了这些研究进展,旨在加深对Li同位素溶液分析技术的理解,展示其在地球化学研究中的良好应用前景。     

石漠化程度遥感信息提取方法研究

岩溶石漠化是中国西南地区的一种严重的生态环境问题。近年来有进一步恶化的趋势。本文以贵州省普定县典型研究区IKONOS遥感数据为例,给出了一种利用多光谱遥感数据定量提取岩溶石漠化程度信息的算法。在多维光谱的向量空间分析的基础上,提出了“植被线”的概念,并定义“石漠化几何指数”（GRI）为多维向量空间中不同程度的石漠化像元到“植被线”的归一化距离。作者认为使用这种方法提取石漠化程度,可以避免人工解译的主观性强,工作量大的缺点。使提取到的石漠化程度结果客观稳定。     

Understanding hydrological processes of glacierized catchments in the western Himalayas by a multi-year tracer-based hydrograph separation analysis

Snow and glacier melt are significant contributors to streamflow in Himalayan catchments, and their increasing contributions serve as key indicators of climate change. Consequently, the quantification of these streamflow components holds significant importance for effective water resource management. In this study, we utilized the spatio-temporal variability of isotopic signatures in stream water, rainfall, winter fresh snow, snowpack, glaciers, springs, and wells, in conjunction with hydrometeorological observations and Snow Cover Area (SCA) data, to identify water sources and develop a conceptual understanding of streamflow dynamics in three catchments (Lidder, Sindh, and Vishow) within the western Himalayas. The following results were obtained: (a) endmember contributions to the streamflow exhibit significant spatial and seasonal variability across the three catchments during 2018–2020; (b) snowmelt dominates streamflow, with average contributions across the entire catchment varying: 59% ± 9%, 55% ± 4%, 56% ± 6%, and 55% ± 9% in Lidder, 43% ± 6%, 38% ± 6%, 32% ± 4%, and 33% ± 5% in Sindh and 45% ± 8%, 40% ± 6%, 39% ± 6%, and 32% ± 5% in Vishow during spring, summer, autumn, and winter seasons, respectively; (c) glacier melt contributions can reach ~30% to streamflow near the source regions during peak summer; (d) The primary uncertainties in streamflow components are attributed to the spatiotemporal variability of tracer signatures of winter fresh snow/snowpack (±1.9% to ±20%); (e)regarding future streamflow components, if the glacier contribution were to disappear completely, the annual average streamflow in Lidder and Sindh could decrease up to ~20%. The depletion of the cryosphere in the region has led to a rapid increase in runoff (1980–1900), but it has also resulted in a significant streamflow reduction due to glacier mass loss and changes in peak streamflow over the past three decades (1990–2020). The findings highlight the significance of environmental isotope analysis, which provides insights into water resources and offers a critical indication of the streamflow response to glacier loss under a changing climate.     

图像端元全自动提取方法研究

传统端元提取算法一般需要人工指定端元数目，易导致多选或漏选端元。提出了一种端元全自动提取方法，通过研究分类结果的均方根误差、端元间光谱相关性与端元数目的关系，设置两种循环结束条件，当分类结果的均方根误差最小或端元间恰未出现强相关现象时，获得最佳端元数。实验表明，该方法是正确有效的，能够克服现有方法的不足，提高了端元提取自动化程度。     

基于端元独立性的端元数目自动获取方法

目前端元数目主要是图像处理者目视判读影像获得的经验值,往往与影像中实际典型地物种类数目不符合。根据端元数目取值不同时的分类结果均方根误差(RMSE)的大小,能够得到实际端元数,但该方法因多次分类导致计算量过大。本文在研究端元间光谱相关性与端元数目之间关系的基础上,提出一种基于端元独立性的端元数目自动获取方法。与基于RMSE的端元数目自动获取方法的对比实验表明,该方法不仅能够正确有效地获取实际端元数,提高端元提取自动化程度,而且能够大大减少运算时间。     

Recent advances in hyperspectral image processing

Hyperspectral images (HSI) provide a new way to exploit the internal physical composition of the land scene. The basic platform for acquiring HSI data-sets are airborne or spaceborne spectral imaging. Retrieving useful information from hyperspectral images can be grouped into four categories. (1) Classification: Hyperspectral images provide so much spectral and spatial information that remotely sensed image classification has become a complex task. (2) Endmember extraction and spectral unmixing: Among images, only HSI have a complete model to represent the internal structure of each pixel where the endmembers are the elements. Identification of endmembers from HSI thus becomes the foremost step in interpretation of each pixel. With proper endmembers, the corresponding abundances can also be exactly calculated. (3) Target detection: Another practical problem is how to determine the existence of certain resolved or full pixel objects from a complex background. Constructing a reliable rule for separating target signals from all the other background signals, even in the case of low target occurrence and high spectral variation, comprises the key to this problem. (4) Change detection: Although change detection is not a new problem, detecting changes from hyperspectral images has brought new challenges, since the spectral bands are so many, accurate band-to-band correspondences and minor changes in subclass land objects can be depicted in HSI. In this paper, the basic theory and the most canonical works are discussed, along with the most recent advances in each aspect of hyperspectral image processing.     

基于MERIS影像空间、光谱及时间维信息提取亚像元级的土地覆盖组分

及时获取有效的土地覆盖信息是地球系统模拟的基础。因此,中等空间分辨率传感器如MODIS或MERIS空前的通道设置与观测能力,使其具有快速更新土地覆盖图的能力。本文说明了如何结合MERIS的空间维（像元大小为300m）、光谱维（可见光与近红外范围内15个通道）和时间维（重返周期2—3d）,用于获取不同区域土地覆被组分的亚像元级组成权重。利用4月、7月和8月三期MERIS FR1b级数据得到荷兰主要土地覆被类型的组成权重。单一时相和多时相的数据都使用单个像元最优化的端元数进行线性光谱分解。利用一种形态偏离指数得到MERIS的空间维并用于端元的选择。应用荷兰土地利用数据库（LGN5）25m分辨率的栅格数据作为本文的参考数据。基于这种数据的高分辨率,因此可以从像元和亚像元的水平同时评价的分类精度。结果显示,结合4月和7月的影像可以获得最优的分类结果,精度约为58%。总的说来,亚像元和像元级的分类精度相似。通过几种组分类别和日期的光谱融合表明,物候状况对于数据获取时相最佳结合的选择以及正确识别土地覆盖类型的重要性。     

光谱角法在ASTER影像土地利用分类中的应用

为了验证光谱角法(SAM)对ASTER影像分类效果,本文对SAM分类的原理进行了阐述和分析,采用了SAM方法以ASTER遥感影像数据为数据源对泸沽湖地区的土地利用进行分类研究,并对分类精度进行了分析。研究结果表明SAM方法用于ASTER数据是一种有效的分类方法,对提高ASTER影像分类精度具有重要的意义。     

Study of spectral signatures for exploration of Bauxite ore deposits in Panchpatmali,India

Spectral analysis technique has been utilized to identify the Bauxite mineral occurrences in Panchpatmali, Orissa, India. Spectral processing of Landsat ETM+ data has been carried out by converting the digital data from quantized and calibrated values to reflectance values. Minimum noise fraction transformation is used to determine the inherent dimensionality of reflected Landsat ETM+ data, to segregate noise in the data, and to reduce the computational requirements for subsequent processing and interactively to locate pure pixels within the data-set, projecting n-dimensional scatterplots. Spectral processing results are displayed in the form of images corresponding to each group of pixels (endmembers). Mixed tune matched filtering method has been applied on Landsat ETM+ images which gave three score (abundance) images for three different classes (endmembers) such as Bauxite, vegetation and soil. Further, mineralized zones are identified using image fusion of ERS-2 SAR and Landsat ETM+ data using intensity-hue-saturation technique.