甘肃省席芨水地区遥感蚀变信息提取及找矿远景分析

在地质工作程度较低、基岩出露较好的地区,充分重视遥感数据的使用,可有效地缩小工作靶区,提高找矿效率。该文以甘肃省席芨水地区为研究区,基于ETM+遥感数据,利用多元数据分析、准归一化、掩膜分析、主成分分析、密度分割等方法,从Landsat7ETM+数据中提取金矿化蚀变信息。在遥感地质解译的基础上,充分分析提取的羟基异常和铁染异常,结合区域地质特征、区域成控矿条件及区域物化探异常特征等,尽可能去掉假、弱异常。结果表明:该方法能有效消除植被、水系、阴影等干扰信息的影响,从遥感数据载体中提取微弱的金矿化蚀变信息。提取的矿化蚀变信息与断裂构造具有较好的相关性,主要分布于断裂构造交会处、断裂与岩体交会处等成矿优势部位,对今后的找矿工作具有一定的指导意义。     

松辽盆地西部斜坡区烃渗漏蚀变信息遥感探测

使用陆地卫星ETM+7图像对松辽盆地西部斜坡区进行稠油探测,图像增强方法有主成分分析、波段比值和假彩色合成等.主成分因子1,3,4,5-PC3(1,3,4,5主成分分析的第3主成分),1,3,5,7-PC3,2,3,5,7-PC3和3,4,5,7-PC4与波段比值3/1,4/3,7/5和(4/3)-(2/3)等用丁假彩色合成,在合成影像上圈定烃渗漏蚀变区域.结果表明烃渗漏蚀变区域与地质背景密切相关,与下伏油藏的分布大致相符.     

ETM遥感图像在措勤东部第四系含水性研究中的应用

措勤东部属于极端缺水的地区,利用遥感技术开展第四系松散堆积物含水性调查具有重要作用。本文选用ETM753与8波段融合图像作为遥感解译底图,结合地形地貌、地质和气象影响,建立残积、冲积、洪积、冲洪积、冰川永久积雪、湖积、沼泽和坡积的识别知识体系,划定第四系松散堆积物的高、中、低、差四个含水等级,利用G IS实现第四系松散堆积物及其含水性的高程、坡度和坡向分布,为区内水资源的深入调查提供有力支持。     

Characteristics of snow cover in the Hindukush,Karakoram and Himalaya region using Landsat satellite data

Estimation of snow cover characteristics (snow grain size, snow contamination, snow depth and liquid water content) from satellite data are important components for many hydrological models used for the water resource management. This research aimed to use Landsat ETM+ (Enhanced Thematic Mapper Plus) data to estimate the snow pack characteristics in northern Pakistan. The Normalized Difference Snow Index (NDSI), Snow Contamination Index (SCI) and Snow Grain Size Index (SGI) are applied to estimate the snow cover characteristics in northern Pakistan for the first time. Qualitative maps are generated to show the snow cover distribution, snow contamination concentration and snow grain size distribution over snow cover area. Our results show that NDSI, SCI and SGI can be effectively used to identify snow area, contaminated snow and ageing snow. Furthermore, the results of the current study indicate that in the HKH region 99.8% of the snow is least contaminated whereas 94.50% of the area has fine snow grain size. As no such attempt in the past has been made in northern Pakistan, it is envisaged that the results of this study will be helpful in planning remote sensing data for the water resource management and in characterizing the snow cover for the climate change applications in the region. Copyright © 2011 John Wiley & Sons, Ltd.     

基于à trous小波变换的Landsat 7 ETM＋图像融合研究

 以胶州湾及周边海岸带为研究区，采用Landsat 7 ETM+数据，提出一种基于à trous小波变换的全色图像和多光谱图像融合改进算法。对全色图像和多光谱图像进行适当层数的小波分解，多光谱图像的低频部分采用全色图像和其低频分量的比来调制； 最高分解层外的其余分解层采用多光谱图像和全色图像在该层分解系数的加权和，加权系数由局部区域能量比来确定； 最高分解层则采用绝对值最大准则。实验表明，该方法得到的图像可提高空间分辨率，对多光谱图像的光谱信息扭曲也较小，为提高海岸带地物分类和信息提取精度奠定了基础。     

新疆谢米斯台地区小岩体型矿化遥感探测

中酸性小岩体易被地质填图遗漏,严重制约了该类型矿化的发现。在新疆西准噶尔谢米斯台地区找矿工作中,首先利用ETM+数据进行小岩体扫面,进而选取重点区采用ETM+和中巴资源卫星02B HR数据进行分辨率融合后解译、识别中酸性小岩体,并利用主成分分析法提取蚀变遥感异常,结合地质、化探信息综合分析后确定重点检查区域。利用此方法共解译出14个钾质花岗岩和3个黑云母花岗岩小岩体,这些小岩体大多被野外检查所证实。经野外检查发现了5处铜、金矿化点,证实了该方法的有效性。本研究中采用的方法可以为西部地区地质填图和中酸性小岩体型矿产资源勘查提供借鉴。     

Fusion of TerraSAR-x and Landsat ETM+ data for protected area mapping in Uganda

TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping. A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99%, 83.12% and 85.38% and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for protected area mapping in Uganda.     

基于ETM＋遥感影像反演不同土地利用类型地表温度的研究

采用Landsat7 ETM＋为基本数据源,运用3种算法（大气辐射传输方程RTE、Qin等单窗算法和Jimenez—Munoz＆Sobrino普适性单通道算法）定量反演了黄河三角洲部分地区的地表温度（land surface temperature,LST）,并进行了不同算法反演结果的差值比较：以RTE反演结果为标准,在大气水汽含量较低时,Qin等单窗算法和JM＆S普适性单通道算法精度较高,与RTE的反演结果相差均在1K以内;在大气水汽含量较高时,Qin等单窗算法在采用地面气象资料估算水汽含量条件下仍保持较高的精度,比RTE反演结果平均偏小0．95K;而根据估算的大气水汽含量进行反演的JM＆S普适性单通道算法的反演偏差比Qin等单窗算法要大,达到1．94K,但JM＆S普适性单通道算法根据实测的大气水汽含量得到的反演结果要略优于Qin等单窗算法,比RTE结果偏大0．67K。同时计算了经过6s模式校正后归一化植被指数（INDV）,然后利用GIS中的空间分析功能,分析LST、INDV在不同土地利用类型之间的差异以及二者之间的定量关系。发现研究区内,就所有土地利用类型而言,平均LST和INDV之间存在显著的负相关关系;对于各种土地利用类型,这种相关关系也存在．但相关程度不同。     

地形抹平与半经验模型的Landsat TM/ETM+地形校正方法

地形校正可以减小地形起伏对地物光谱的影响,提高计算机分类在山区的精度。设计了针对全球土地覆盖分类的Landsat TM/ETM+数据地形校正方法 SCOS(Smoothed COS余弦),首先对地形的坡度角进行抹平处理,很大程度上削弱了地表非朗伯性对地形校正的影响,然后利用简单有效的余弦校正去除地形效应。该方法与其他常用地形校正算法的对比分析是通过对全球不同区域、不同地表覆盖的有代表性的6景Landsat TM/ETM+数据的试验,采用统计分析与目视判读的方式,从过度校正和类内均一性两个方面进行的。结果表明,该方法在目视效果和统计结果上优于常规方法,并且更加简单有效,无需复杂的大气参数及传感器参数,满足全球地表覆盖分类对地形校正的需求。     

Evaluation of directional normalization methods for Landsat TM/ETM+ over primary Amazonian lowland forests

Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross–Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.