资源三号测绘卫星 DSM 与AST ER GDEM 精度对比分析--以高海拔山区为例

为了评价国产资源三号测绘卫星DSM数据质量,选取地貌类型丰富的云南省高海拔山区为试验样区,以1∶10 000实测地形图DEM为假定真值,以30m分辨率ASTER GDEM为评价参照,从高程精度和地形描述精度两方面着手,对国产资源三号测绘卫星DSM数据精确性进行分析。结果表明:国产资源三号测绘卫星DSM数据精度整体高于ASTER GDEM。     

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.     

ASTER GDEM垂直精度评价及其在重力地形改正中的适用性

通过构建ASTER GDEM(advanced spaceborne thermal emission and reflection radiometer global digital elevation model)高程误差与影响因子间的关系模型,可对其高程精度进行有效校正。选取陕北黄土高原境内长武、宜君、甘泉、延川4个不同地貌类型的样区,以1∶5万DEM (digital elevation model)作为参考数据,经过数据预处理后,计算各点位高程误差值及相关地形因子和地表覆盖指数; 提取一定数量的采样点和检验点,引入随机森林回归算法,建立高程误差预测模型,以对高程精度进行校正,并与多元回归模型进行比较分析。实验结果表明,ASTER GDEM的高程误差特征与地形条件有较强的相关性; 随机森林回归预测模型整体上优于多元回归模型,具有较好的适用性与误差校正效果,可分别将长武、宜君、甘泉、延川的高程误差均值减小3.08 m、3.00 m、3.61 m和6.95 m。     

Evaluation of ICA and CEM algorithms with Landsat-8/ASTER data for geological mapping in inaccessible regions

Many regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistic difficulties. Application of specialized image processing techniques is capable of revealing the hidden linear mixing spectra in multispectral and hyperspectral satellite images. In this study, the applications of Independent component analysis (ICA) and Constrained Energy Minimization (CEM) algorithms were evaluated for Landsat-8 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing data for geological mapping in Morozumi Range and Helliwell Hills areas, Northern Victoria Land (NVL), Antarctica. The results of this investigation demonstrate the capability of the two algorithms in distinguishing pixel and subpixel targets in the multispectral satellite data. The application of the methods for identifying poorly exposed geologic materials and subpixel exposures of alteration minerals has invaluable implications for geological mapping and mineral exploration in inaccessible regions.     

新疆北山地区侵入岩遥感识别方法

基于ASTER数据、Landsat 8数据及WorldView-2数据,采用波段组合法、最小噪声分离法、主成分分析法以及波段比值法,结合岩石光谱曲线,综合提取了新疆北山地区侵入岩的岩性特征。对WorldView-2进行主成分分析和最小噪声分离,并将R(PCA2)G(PCA1)B(PCA4)、R(MNF2)G(MNF1)B(PCA1)、OLI数据R(B7)G(B6)B(B5)进行假彩色合成,利用OLI数据中的B5/B2、B2/B1突出花岗岩。这些方法解决了复杂岩性的影像色调差异较小、细节不清晰等问题,降低了岩性划分及解译的难度,使各种岩性界线更加明晰。结合前人的区域地质调查成果,对研究区侵入岩岩性进行了系统解译及分析。多源遥感数据的综合利用,有助于更有效地识别复杂岩性并进行更详细的岩性分类,提高遥感岩性识别的正确率。     

基于摄影测量的ASTER影像云顶高度解算模型与实验

云顶高度是天气预报、天气监测的重要因子,准确的云顶高度对提高天气分析和数值预报的质量,具有重要的科学意义。立体几何法是公认云顶高度解算精度较高的方法,目前,普遍采用卫星-球心-投影云-真云的平面和球面三角几何关系,以及影像匹配技术解算云顶高度,由于采用了理想椭球体和重投影技术,以及对云移动考虑不足,因此误差较大。本文将数字摄影测量理论与遥感技术相结合,首次将摄影测量共线方程用于云顶高度解算。本文利用ASTER影像,依据相关系数法解求云迹风,并将其引入到摄影测量共线方程中,建立了ASTER影像的云顶高度解算模型,进行了未考虑和考虑风速的云顶高度解算,通过地面点计算,本文解算误差为2个像元（30 m）左右,经与MISR云顶高度产品对比分析,认为该模型解算的考虑风速的云顶高度精度优于MISR解算结果。     

基于ASTER热红外数据的SiO2及岩性类别信息提取——以青海省绿梁山—双口山地区为例

岩性识别目前是遥感地质应用的热点和难点。青海省绿梁山—双口山地区属于干旱、植被稀少的地区,基岩裸露程度较高,为利用多光谱遥感数据进行岩性类别信息提取提供了便利条件。本文基于ASTER热红外数据,对青海省绿梁山—双口山地区的SiO_2含量进行反演,其结果显示SiO_2含量的高低范围基本与区内的岩性类别相对应,利用ASTER的热红外数据对于确定地表地质体的长英质、镁铁质大类具有良好效果。     

基于ASTER遥感数据的西藏多龙矿集区示矿信息的提取

矿化蚀变信息的提取对圈定成矿区具有重要意义。近年来,运用多光谱遥感数据进行示矿信息提取得到了长足的发展。常用的示矿信息提取技术方法包括优化的主成分分析方法、比值算法、光谱角算法等。选取西藏改则县多龙地区为研究区,以区内多不杂斑岩型铜矿为典型的已知矿床,基于ASTER遥感数据,运用多种示矿信息提取方法进行靶区圈定综合研究,多种技术方法相互印证,避免了单一算法的局限性,为成矿靶区的圈定提供了更为准确的遥感依据。     

基于ASTER VNIR SWIR多光谱遥感数据识别与提取干旱地区岩性信息——以西南天山柯坪隆起东部为例

ASTER多光谱遥感数据目前可以用于岩石矿物资源信息的识别和提取。本研究尝试利用ASTER 可见光近红外（VNIR）和短波红外（SWIR）的多光谱遥感数据提取干旱地区的岩石与矿物信息。基于新疆天山西南缘柯坪隆起东部不同地层单元岩石的化学组成和矿物成份以及VNIR SWIR谱域光谱吸收特征的分析,我们采用相关吸收波段深度（RBD）和波段比值（BR）方法对研究区的多光谱遥感数据进行图像处理,有效区分和识别了白云岩、石灰岩、砂岩以及阿克苏群的蓝片岩—绿片岩和砂质片岩。白云岩的CO2-3吸收谱带中心波长位于232〖KG*3〗μm,与灰岩的CO2-3 吸收谱带中心波长位置235 μm相比,具有向短波长方向移动的特点,据此可以利用RBD7、RBD8分别有效的识别白云岩和灰岩; 长英质岩石显示Al OH和Fe3+ VNIR SWIR吸收特征,而基性 超基性岩石显示Fe2+ 和Fe、Mg OH特征,利用不同的铁价态和次要矿物可以区分它们：ASTER band2/band1代表了含Fe3+ 矿物分布信息、ASTER band5/band4代表了含Fe2+ 矿物分布信息、RBD6可以估计Al OH矿物的丰度; 砂质/泥质片岩含较多的多硅白云母、绿泥石、黑硬绿泥石以及风化后表面覆盖的其它粘土矿物,在221 μm（band 6）存在有特征的吸收谱带,并且在165 μm（band 4）具有较高的反射率,而蓝片/绿片岩在221 μm（band 6）反射率较高,不具有明显特征吸收谱带,同时其在165 μm（band 4）反射率较低,因此蓝片/绿片岩ASTER band4/band6 比值低。应用ASTER band4/band6波段比值可以有效的区分开砂质/泥质片岩与蓝片岩/绿片岩。     

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) after fifteen years: Review of global products

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a 15-channel imaging instrument operating on NASA’s Terra satellite. A joint project between the U.S. National Aeronautics and Space Administration and Japan’s Ministry of Economy, Trade, and Industry, ASTER has been acquiring data for 15 years, since March 2000. The archive now contains over 2.8 million scenes; for the majority of them, a stereo pair was collected using nadir and backward telescopes imaging in the NIR wavelength. The majority of users require only a few to a few dozen scenes for their work. Studies have ranged over numerous scientific disciplines, and many practical applications have benefited from ASTER’s unique data. A few researchers have been able to mine the entire ASTER archive, that is now global in extent due to the long duration of the mission. Six examples of global products are described in this contribution: the ASTER Global Digital Elevation Model (GDEM), the most complete, highest resolution DEM available to all users; the ASTER Emissivity Database (ASTER GED), a global 5-band emissivity map of the land surface; the ASTER Global Urban Area Map (AGURAM), a 15-m resolution database of over 3500 cities; the ASTER Volcano Archive (AVA), an archive of over 1500 active volcanoes; ASTER Geoscience products of the continent of Australia; and the Global Ice Monitoring from Space (GLIMS) project.