Multiresolution fusion of remote sensing images based on resolution degradation model

A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM panchromatic and multispectral images are used to assess the new method. Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS, PCA, Brovey, OWT(Orthogonal Wavelet Transform) and RWT (Redundant Wavelet Transform). The results show that the new method can keep almost the same spatial resolution as the panchromatic images, and the spectral effect of the new method is as good as those of waveletbased methods.     

一种黄土区土壤侵蚀强度遥感调查新方法

通过对TM图像的线性纹理提取和密度统计,首先获得了黄土丘陵区沟谷密度图,然后由沟谷密度反演区域土壤侵蚀强度。这种方法避开了影响土壤侵蚀量的诸多复杂因子。可直接从水土流失的外在表现---沟谷密度来反推土壤侵蚀强度。研究结果证明,这种方法对快速调查大范围黄土丘陵区的土壤侵蚀强度是十分有效的。     

An image analysis method to determine crystal size distributions of olivine in kimberlite

Crystal size distributions (CSDs) are a standard method of describing populations of crystals within magmatic rocks. Olivine is the dominant phase in kimberlite (∼40–50% by volume) and features a diverse range of sizes, shapes and origins. CSDs of olivine provide a logical means of semi-quantitatively characterising kimberlite. The CSDs can then be used to distinguish or correlate between kimberlite bodies or to investigate processes related to ascent, emplacement and eruption. In this paper, we present an automatic image analysis technique that provides efficient quantification of olivine CSDs within digital images of polished slabs of kimberlite. This technique relies on a combination of algorithms for detecting regions of interest (ROI) and for segmentation of ROIs in order to identify individual olivine crystals that are used for size distribution datasets. The detection process identifies regions expected to be olivine using a model-based colour detection technique using Mahalanobis distance combined with texture analysis based on local standard deviation and greyscale foreground enhancement techniques. The segmentation process separates adjacent domains to identify individual crystals using an iterative marker-based watershed algorithm to separate adjoined structures of varying sizes. We demonstrate the utility of automatic image analysis by comparing CSDs for olivine derived from this method versus results from manual digitisation of olivine grains. The automatic detection system correctly identified ∼86% of the manually detected olivine domains; ∼88% of the automatically detected regions correctly correlate to manually defined olivine grains. Discrepancies between the two methods are mostly the result of oversimplification of crystal margins (i.e. rounding) by manual tracing whereas automatic boundary recognition shows clear advantages in identifying irregularities in crystal edges. Closer examination of the results shows that both methods suffer from under-representation of smaller crystals due to: (1) human subjectivity and error in manual tracing and (2) noise removal processes in automatic detection. Automatic detection of olivine grains is much more efficient than conventional manual tracing; manual detection requires ∼6 h per sample versus ∼1 min for automatic analysis of the same sample.     

高分一号卫星在京津矿山遥感监测中的应用

高分一号卫星于2013年成功发射,可获取 2 m全色影像与8 m多光谱影像,在矿山遥感监测中有很大的应用空间。研究并总结了高分一号卫星在矿山遥感监测应用时的数据处理流程和方法,根据高分一号影像特征建立了矿山遥感解译标志并对部分图斑进行了野外验证,最后进行了京津矿山遥感调查与监测工作。通过应用研究得出结论,高分一号卫星拥有较高的分辨率和较好的数据质量,地物轮廓纹理清晰、数据处理方便、解译精度较高,运用高分一号卫星进行矿山遥感监测可以取得良好的效果,可以为国土资源部门制定矿产资源规划、整顿矿产资源开发秩序、治理矿山地质环境等提供技术支撑和决策依据。     

碱熔共沉淀-电感耦合等离子体质谱法测定橄榄岩中的稀土元素

橄榄岩的稀土元素特征对研究岩石成因、岩浆作用过程具有重要的意义。橄榄岩中的稀土元素含量低(∑REEs=0.1~1μg/g),且存在镁、铁等基体元素的干扰,难以准确测定。前人通常利用高压密闭酸溶-离子交换法处理样品,将稀土元素与镁、铁等基体元素分离,达到了预富集的效果,但耗时长(消解时间接近7天)、操作步骤繁多,不利于大批量样品的分析。本文建立了过氧化钠碱熔、Fe(OH)_3和Mg(OH)_2共沉淀的样品前处理方法,通过离心使溶液与沉淀分离,从而实现了稀土元素与镁、铁等基体元素的快速分离,再采用电感耦合等离子体质谱法测定稀土元素含量。方法检出限为0.17~2.18 ng/g,加标回收率为95%~101%,国家标准物质(GBW07101和GBW07102)的测定值与标准值的相对误差小于20%,相对标准偏差(RSD,n=11)小于10%。该方法既减少了分步沉淀过程中带来的损失,也缩短了分析周期(消解时间仅需一天),操作简便,分析效率高。     

成矿区三维可视化与立体定量预测——以钦-杭成矿带庞西垌地区下园垌铅锌矿区为例

矿产资源是人类生存与社会进步的根本物质保障。近年来,随着地表矿、浅部矿产资源的日益枯竭,采用新技术、新方法的深部矿产资源预测成为地质勘查的主要研究方向。基于数字化、三维可视化及矿产定量预测为主的三维地质建模技术,为当前矿产资源远景预测与找矿工作提供了有力的工具。本文在现代成矿预测理论研究基础上,运用三维地质建模技术建立了钦杭成矿带下园垌矿区地质、地球物理、地球化学、钻孔等三维模型,揭示了区内构造地质特征、地球化学异常表征及地层岩体要素,据此探讨了矿床的成因及矿体分布特征。并在此基础上,采用证据权方法对研究区地质、地球物理、地球化学等多源信息进行融合,运用断裂缓冲区、地球化学异常、东岗岭组沉积岩地层等为证据因子来计算单位体积成矿后验概率,进行立体成矿预测,并圈定出铁锰矿、方铅闪锌矿、铅锌银综合矿等3处找矿有利靶区及估算出预测区内矿产资源储量总量为88710吨。研究结果表明:综合分析地质、地球物理、地球化学及钻孔数据进行矿区的三维地质空间定位、定量预测研究,可以有效的识别矿致异常信息,圈定找矿远景区,为成矿预测研究领域提供了新方向,可以将此方法应用至其他矿山。     

Chromite typology and composition characterized through multispectral specular reflectance

Determination of multispectral specular reflectance is an important tool for ore identification in reflected light microscopy, and may be used for automated characterization of ores. However, reflectance values can be affected by compositional variations in a way that is seldom understood. The aim of the present work is to investigate this problem in chromite, an ore whose composition may show typically large natural variations as member of the spinel family, and whose relatively high reflectance variations are apparently unpredictable. For this research, eighteen samples of chromian spinel covering a large range of compositions in the base of the Hagerthy prism were selected for microprobe analysis and reflectance measure on polished sections. The samples belong to a variety of deposits and types (ultramafic massif, ophiolitic, and metamorphosed types: Ojén and Ronda Massifs, Spain; Mayarí, Moa-Baracoa, Camagüey and Sagua de Tánamo, Cuba; Golyamo Kemenyane, Avren and Yakovitsa, Bulgaria). The specular reflectances are characterized as multispectral values, measured at thirteen intervals (50 nm each) in the VNIR region (Visible and Near-Infrared: 400–1000 nm), using the automated CAMEVA System.The relationship between compositional and reflectance values is studied by multivariate analysis and subsequently tested on independent samples. For this purpose, the samples have been grouped in two sets: a larger population of fifteen samples constitutes the initial data set for mathematical processing, while a selection of three samples of widely differing compositions is used to test the resulting functions, so as to gain a critical appraisal of their validity.The results obtained show that the specular reflectance of chromite depends on composition and can be used to estimate compositional parameters, as #Cr = Cr/(Cr + Al) or #Mg = Mg/(Mg + Fe²⁺), but this relationship is complex and does not allow simple direct determinations, due to the multiplicity of possible changes and coupled substitutions (e.g. Al–Cr–Fe³⁺, or Mg-Fe²⁺, Ni, Zn, Ti …) in the chromian spinel family. On the other hand, the relationship of chromite composition with deposit type is also detectable through the reflectance values, but with a higher uncertainty. Reflectance increases with increasing Cr and Fe³⁺ contents in all cases, but the relationship of reflectance with Mg seems to be specific of the deposit type: while reflectance increases with increasing #Mg in the Ojén chromites, it shows the opposite behaviour in podiform chromites. Although these results should be regarded as preliminary until further studies on larger sample populations can be achieved, they are suggestive of possible practical applications for exploration, e. g. to approach Cr-spinel compositions or chromite deposit typology, early in an exploration campaign, by inexpensive reflected light determination of specular reflectance in a few samples.     

华南地区典型种植园地遥感分类研究

华南地区种植园地广泛分布,类型混杂多样,导致园地分布信息难以正确获取,为农业管理造成了较大困难。本研究基于Landsat8 OLI数据,通过数据融合、特征优化,应用随机森林算法构建面向对象的种植园地分类规则集,对华南地区典型经济作物香蕉、柑橘、葡萄、蒲葵、海枣、番木瓜和火龙果等进行类别识别,同时对比贝叶斯分类法、K最邻近分类法、支持向量机法、决策树分类法的分类效果。结果表明：数据融合会在一定程度上影响分类结果精度;植株形态、光谱特征接近,种植期交错是影响华南地区典型园地分类精度的重要原因;以中分辨率影像为数据源,面向对象的随机森林算法应用于种植园地分类研究总体精度可达88.05%,Kappa系数0.87,可以有效区分华南地区典型种植园地类别;相比于其他算法,随机森林算法在分类精度、可靠性和稳定性上具有一定优势,可为园地作物生长监测和种植管理提供科学依据。     

Discontinuous Data 3D/4D Variation Fusion Based on the Constraint of L1 Norm Regularization Term

Classical 3D/4D variation fusion is based on the theory that error follows Gaussian distribution. When using minimization iteration, the gradient of objective function is involved, and the solution of which requires the continuity of data. This paper adopted the extended classical 3D/4D variation fusion method, and explicitly applied the prior knowledge, which was based on L1-norm, as regularization constraint to the classical variation fusion method. Original data was firstly projected into the wavelet domain during the implementation process, and new fusion model was adopted for data fusion in wavelet space, then inverse wavelet transform was used to project the result to the observation space. Ideal experiment was carried out by using linear advection-diffusion equation as four-dimensional prediction model, which made a hypothesis of the discontinuity with the data between background and observation, and that meant the derivatives between left and right were not equal on some points. The result of the experiment showed that the method adopted here was practicable. A further research was also done for multi-source precipitation fusion. Firstly, CMORPH inversion precipitation data were corrected through PDF (Probability Density Function, PDF) matching method based on GAMMA fitting function. Then corrected data was fused with the observation one. By comparison with the reference field, the result showed that this method can keep some outliers better, which might represent certain weather phenomenon. The L1-norm regularization variation fusion in this paper provided a possible way to deal with discrete data, especially for jump point.     

塔里木盆地周边地区土地退化的遥感研究

以20世纪70年代陆地卫星MSS和90年代ETM图像为基础,通过分析对比,并配合野外检查验证,快速提取了塔里木盆地周边地区4种程度土地沙化类型的分布信息.根据获取的两个时期4种程度的土地沙化类型分布信息,编制了全区土地沙化程度及范围变迁图.该图客观地反映了区内近30a来土地退化的实际情况,为干旱-半干旱地区的土地退化研究提供了遥感技术应用实例.