Integration of Landsat-8 and Sentinel-1 dataset to extract geological lineaments in complex formations of Tepal mountain area,Shahrood, north Iran

Recently, the detection and extraction of geological lineaments have become an essential analytical technique to find relationships between the characteristics and occurrence of hydrogeology, and tectonic studies. The use of remote sensing, with the progressive development of image enhancement techniques, provides an opportunity to produce more reliable and comprehensive lineament maps. In this paper, semi-automatic approach based on Landsat 8 and Sentinel 1 radar data is proposed for lineaments extraction and validation. The combined method of linear filtering and automatic line module ensures a high degree of accuracy resulting in a lineament map. Based on identified lineaments, Sentinel1 is more capable of detecting edges than Landsat8, but the primary orientation lineaments extracted from Landsat8 and Sentinel1 were different. So, by combining band6 of Landsat8, and VV and VH polarization of Sentinel1, the area lineaments were extracted with high accuracy. Rose diagram showed the extracted lineaments' orientation is in good compliance with the region's existing faults. Also, the formations' lineament length density has good consistent with the density of the faults in the geological map.     

Multiple sensor geocoded data

The problem of integrating remotely sensed images acquired from different sensor systems is primarily associated with their registration into a common reference projection. This registration problem has to be considered not only between the image data themselves but also with other data already existing in various geographical data bases.The advent of the second generation of earth observation satellites is emphasizing this situation by providing imagery in different geometric configurations. Images will be acquired from many sensors at different spatial resolutions (LANDSAT MSS and TM, SPOT HRV MLA and PLA) on different dates and modes (panchromatic, multispectral, nadir and off-nadir).In order to provide image data in a geometric format compatible with the Canadian National Topographic System, Canada is developing a Multi-Observational Satellite Image Correction System (MOSAICS) that will provide geocoded data resampled into a common reference projection. This paper presents the characteristics of the geocoded products with examples from multiple sensors and different dates, and addresses the processing requirements of the satellite ground station. It also illustrates the use of digital processing techniques to derive digital elevation information from geocoded stereo imagery.     

空间目标的ISAR成像及轮廓特征提取

空间目标的逆合成孔径雷达（ISAR）成像由于受自身遮挡及噪声干扰等影响,导致生成的ISAR像难以直接进行图像分析及目标识别。由此,以空间目标的ISAR成像建模为基础对ISAR像处理及特征提取展开了研究。首先,分别建立了目标卫星的ISAR成像模型、ISAR信号模型及ISAR图像函数提取模型,并经过旁瓣抑制与相干斑滤波等初步处理得到了目标卫星的ISAR像。其次,采用Otsu算法、canny算子及Hough变换使卫星旋转至最长轴平行于像平面横轴,通过闭运算填充卫星内部孔洞,去除外部孤立噪声,并基于连通域思想分割出卫星所在子区域,实现了卫星的轮廓提取。所设计的图像处理算法能有效改善ISAR像质量,提取的卫星轮廓线能较好地勾勒出目标卫星的外形结构,为进一步展开卫星的识别工作奠定了重要基础。      

Use of the ASTER satellite images for evaluation of structural changes in the Popocatépetl volcano related to microseismicity

Mexico is one of the most volcanically active regions in North America. Volcanic activity in central Mexico is associated with the subduction of the Cocos and Rivera plates beneath the North American plate. Periods of enhanced microseismic activity, associated with the volcanic activity of the Popocatépetl volcano are compared with periods, during which the microseismic activity was low. We detected systematical changes in the number of lineaments, associated with the microseismic activity due to lineament analysis of a temporal sequence of high resolution satellite images of the Popocatépetl volcano, provided by the ASTER/VNIR instrument. The Lineament Extraction and Stripes Statistic Analysis (LESSA) software package was used for the lineament extraction. In the future it would allow develop a methodology for detection of possible elevation of pressure in volcano edifice.     

Remotely sensed thermal information applied to urban climate analysis

Urban heat island (UHI) effects on the ten most populated cities of Hungary, including the Budapest agglomeration area, were analyzed using remotely sensed data. Day- and night-time surface temperature time series observed by sensor MODIS on satellite Terra were used to determine UHI intensities. UHI intensity was defined as the difference in spatially averaged surface temperatures between urban and surrounding rural pixels. Spatial structures of UHIs were determined and compared for different seasons and macrocirculation conditions.     

Estimation of stress and its use in evaluation of landslide prone regions using remote sensing data

Recently, use of remote sensing data for determining the orientation of stress has been demonstrated. The present study deals with the estimation of stress pattern in the part of the Himalayan region which shows the ongoing neo-tectonic activities. The study area falls into a tectonically active zone of the Central-Himalaya, with a complex geotectonic set-up confined by a number of faults. Efforts have been made to evaluate the technique as a fast algorithm for quick and time limited analysis of linear feature from which the orientation of the lineaments are estimated by using remote sensing data. Further, the estimation of stress and the lineament analysis have been used in mapping of landslide prone areas. Terrain information such as land cover, geology, lineament, faults, mega faults, geomorphology and drainage has been derived from the satellite imageries, and the existing thematic information has been updated to enable the quantification of landslide causative parameters. Spatial and temporal multi-layered information have been used for landslides hazard susceptibility analysis. The qualitative hazard analysis has been carried out using the map overlying techniques in GIS environment along the central part of Himalayan region. It has been observed that the high potential zones have been found to have very high lineament density, moderate to low drainage density and high slope areas of the terrain. On the basis of the geological and morphological analysis, it is further suggested that the combined impacts of the crushed nature of bed rock (due to the neo-tectonic activities), heavy rainfall and lack of vegetation cover cause persistent recurrence of landslides along this region. The role of earthquake on induction of landslides will be presented.     

重力卫星高精度测距系统观测量的降速率滤波算法

在卫星时频传递、矢量测量技术领域，有效观测数据的高精度滤波处理十分重要，其基本要求是在保留有效观测信息的同时能够降低噪声干扰，实现原始信息的高效、高精度传递。以中国地球重力场测量卫星高精度测距系统的工程研制为背景，为实现高频噪声抑制、保留低频重力场信息，基于对FIR滤波器结构的优化和窗函数的改进，提出了一种对10 Hz采样率的原始测距数据降速率、降噪滤波的算法。相比其他类似算法，所提方法同时具备降速滤波和差分运算两种功能，噪声抑制抑制度优于44%，且频率截止特性陡峭，第一旁瓣抑制度达到–94 dB。该算法在提高测距精度、充分保留重力场信息的同时，实现了地面数据后处理流程的简化，为微波测量系统、激光测量系统的数据处理提供了一种优选方案。     

Computer analysis of the lineaments of Nepal

Various information has been obtained by computer analysis of the lineaments of Nepal. The data were carefully studied and correlated to establish the relationships of lineaments with geological units, structure, mineralization, etc. The lineament map of Nepal was prepared during 1977–1978; the lineament data were digitized in 1982—using a Hewlett Packard system 45 desktop computer—separated by area (east, central and west Nepal) and also according to geological units. By trial and error and using all variables, the different preferred orientation classes were identified for east, central and west Nepal. Lineaments were grouped according to length into less than 10 km, 10–20 km, 20–30 km and more than 30 km, for the entire country and also for major geological units, i.e., Siwalik (sub-Himalaya), Lesser Himalaya (midlands) and Higher Himalaya. Various rose diagrams and histograms showing frequency and lengths of lineaments were plotted for the different geological units and the different sectors. Lineaments associated with granites of major subdivisions were plotted separately and analysed.     

Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade

Lineaments refer to the linear or curvilinear textures on remote sensing image, whose general spatial distribution characteristics are often the response of deep geological sturcture at the surface. Firstly, we use wavelet modulus maximum transformation to detect the edges with 4 scales on Landsat – 8 OLI B5 image and analyze their multi-scale characteristics. As the result, it is determined that the optimal scale of edge detection is 4, and the outline that consist of the edge pixels is roughly corresponding to the geological structure of mine area. Thus the incomplete lineaments have been extracted by using the 2D otsu algorithm. Secondly, the hillshade map generated based on DEM is processed to generate binarized linear shadow. Finally, the linear shadow is superimposed on the lineaments preliminarily extracted to obtain the optimized lineaments. Experiment results show that, based on the method, there are some deformation and displacement between the lineaments extracted and the actual geological structure, and it fail to effectively extract Qilinchang Fault, but lineaments are in good correspondence with Kuangshanchang Fault, Dongtou Fault and Niulan River Fault, which are basically in accord with the geological structure framework of the mine area.     

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.     

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

Lineament mapping and fractal analysis using SPOT-ASTER satellite imagery for evaluating the severity of slope weathering process

The present study describes a remote sensing approach for preparing lineament map that subsequently indicates the influence of lineament density in the severity of weathering development. In this study, SPOT-5 data, the integration of SPOT-ASTER and Digital Elevation Model (DEM) data were used and processed. The existence of an active fault system in the south of Mashhad city, NE Iran and presence of schistose rocks in this area result in the development of numerous lineament features. This region was selected for this research. Lineament features including fractures, bedding plane, cleavage, shear zones and schistosity were mapped in the study area. The results indicate that the highest concentration of lineaments occurred in the central-western and south-eastern parts of the study area, which coincide with metamorphic outcrops and NW-SE trending fault system. A comparison of lineament statistical analysis and field survey demonstrated that the structural discontinuities have a significant effect on forming and distribution of weathering profiles. It was observed that increasing the number, length and density of structural discontinuities led to strong severity in weathering, which can produce deep residual soils susceptible to landslide occurrence. The remote sensing approach developed in this study can be applicable for preparing lineament maps and evaluating the severity of weathering development in other active fault zones around the world.     

Prediction of landslides using ASTER imagery and data mining models

The aim of this study was to identify landslide-related factors using only remotely sensed data and to present landslide susceptibility maps using a geographic information system, data-mining models, an artificial neural network (ANN), and an adaptive neuro-fuzzy interface system (ANFIS). Landslide-related factors were identified in Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. The slope, aspect, and curvature of topographic features were calculated from a digital elevation model that was made using the ASTER imagery. Lineaments, land-cover, and normalized difference vegetative index layers were also extracted from the imagery. Landslide-susceptible areas were analyzed and mapped based on occurrence factors using the ANN and ANFIS. The generalized bell-shaped built-in membership function of the ANFIS was applied to landslide susceptibility mapping. Analytical results were validated using landslide test location data. In the validation results, the ANN model showed 80.42% prediction accuracy and the ANFIS model showed 86.55% prediction accuracy. These results suggest that the ANFIS model has a better performance than does the ANN in predicting landslide susceptibility.     

Different atmospheric effects in remote sensing of uniform and nonuniform surfaces

The atmospheric effect on the radiance of sunlight scattered from the Earth-atmosphere system is greatly dependent on the surface reflectance pattern, the contrast between adjacent fields, and the optical properties of the atmosphere. In addition, the atmospheric effect is described by the range and magnitude of the adjacency effects, the atmospheric modulation transfer function, and the apparent spatial resolution of remotely sensed imagery. This paper discusses the atmospheric effect on classification of surface features and shows that surface nonuniformity can be used for developing procedures to remove the atmospheric effect from the satellite imagery.     

干涉SAR图像的降噪方法及水平地形效应消除

考察不同滤波器抑制干涉SAR(Synthetic Aperture Radar)图像噪声的效果.为有效地使用低通滤波处理,首先对原始干涉图像进行水平地形效应消除,保证图像信号频率的中心在零频处,降低由干涉SAR系统几何结构引起的信号频率偏移对滤波效果的影响.同时水平地形效应消除后的干涉SAR相位图可直观地反映地形的拓扑结构.实际数据处理结果证明本文提出的水平地形效应消除算法及滤波算法的可行性及有效性.      

RNSS通道分数码片时延标定软件的设计与实现

一种基于Matlab GUI环境开发的导航卫星RNSS发射通道分数码片绝对时延自动化标定软件的设计,该软件通过GPIB口控制高速数字示波器,对卫星下行导航信号和卫星钟的秒脉冲信号双通道高速数据采样,对采样后的导航信号进行平方律检波和FIR滤波等数字信号处理,寻找码片换相点,根据秒脉冲触发电平样本点和换相点,获取分数码片时延,根据设定的标定次数,自动完成导航卫星分数码片绝对时延多次测量,并求平均,从而得到最终测量值;软件具有界面友好,操作简单,显示直观等特点,在导航卫星整星综合测试中得到应用。     

Relationships between soil properties of the abandoned fields and spectral data derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER)

The structural transformation of Polish agriculture after 1989 has been leading to significant changes in land use. As a result a large part of formerly ploughed fields lies abandoned and they occur across considerable variability in soil typological units. Accurate information about soil conditions within the abandoned fields facilitates proper management in the new socio-economic situation. Such information can be collected using satellite images since the structure and condition of the vegetation growing on the abandoned fields reflects soil properties. The objective of this study is to evaluate the relationships between physical and chemical attributes of soil within the abandoned fields and spectral reflectance patterns recorded by ASTER sensors onboard Terra Satellite. Soil samples were collected at five abandoned fields which have not been ploughed since 2000 and analyzed in the laboratory to determine their physical and chemical properties. Nine ASTER nearly cloud-free pictures were used for this study in order to derive the remote-sensing attributes of the abandoned fields. In order to evaluate the relationships between soil fertility and remotely sensed data, partial least-squares (PLS) and a multiple linear regression (MLR) analysis between these two datasets were carried out. In the regression analysis, only soil TEB (total exchangeable bases) stock in the whole profile displayed the highest correlation with remotely sensed data acquired in April and May and the best predictors were NDVI and LSWI vegetation indices.     

Low cost training in remote sensing applications for developing countries

This presentation introduces the Polish Remote Sensing Centre /OPOLiS/, which offers various types of training possibilities in remote sensing techniques and applications. It deals with a wide range of applications and experiences reached by OPOLiS for various branches of national economy, as well as introduction to analog and digital satellite data processing possibilities with the existing equipment.The offered training possibilities include analog and digital data handling and its interpretation such as visual and computer assisted integration of multiple data sets, as well as image processing, enhancements, mosaics etc.It also includes training and applications of interpretations results for exploration of minerals, energy, and ground water resources, as well as inventories, monitoring and forecasting for agriculture, forest, and natural environmental purposes.The cost factor of the offered training possibilities includes a reasonable input from the Polish Government, which results in low cost input by the participants from developing countries. It also accepts the participation fee in non - convertible currency.     

基于免疫抗体编码机理的卫星图像云探测

针对卫星遥感图像中云与下垫面的复杂性和多样性,提出了一种新的在复杂背景下常用目标图像描述方法.通过类比生物免疫抗体特异性与其构成单元氨基酸性质的相关性,得到目标图像的免疫基元集合形式及其分类方法.借鉴生物免疫抗体编码顺序中氨基酸结合能量最小原则,统计分析出训练样本的免疫基元亲和度计算公式,实现了目标图像描述的有限多特征优化组合.对于云检测问题,最终提出云的免疫抗体编码方法,定义了云的免疫亲和度计算公式,并成功构建了云免疫抗体.经200幅IKONOS卫星图像测试,验证了该方法在识别率和运行时间效率方面的有效性.      

基于奇异值分解的红外热图像序列处理

在红外热像无损检测中直接获取的原始热像往往信噪比较低、温度对比度较差.为了抑制各种噪声的不良影响,使红外热像无损检测所重构的数字图像有较高的缺陷对比度,从而提高缺陷探测能力,提出了采用奇异值分解法对红外数字图像序列进行处理和增强的方法,并进行了验证.介绍了奇异值分解法的原理;用奇异值分解法对实验中采集的红外热像序列进行处理;以信噪比为指标对图像处理效果进行了定量评定.研究表明奇异值分解法具有抽取红外热像序列中反映试件内部缺陷信息代数特征的能力,可消除加热不均效应、提高图像的信噪比,且缺陷在图像中所处的位置不影响奇异值分解法的使用效果. 因此奇异值分解法是红外热像无损检测中红外热图像序列处理的有效方法.