基于DSM阴影仿真和高度场光线跟踪的影像阴影检测

介绍了一个建筑物阴影检测的模型。首先利用摄影测量学原理来计算阴影坐标。即用数字表面模型(digitalsurfacemodel,缩写为DSM)和太阳高度和方位来计算建筑物阴影的空间坐标,并由相机模型计算出每个阴影单元对应的扫描行和相机空间坐标。由高度场光线跟踪判断阴影的可见性,对可见阴影计算出它在投影图像上的坐标。然后在这个结果的基础上再对图像进行阴影的细分割。     

基于地表定量参数的沙漠化遥感监测方法

利用野外沙漠化调查的定位数据和ETM+ 遥感数据，在实验分析的基础上，探讨了沙漠化程度与地表参数之间的定量关系，即沙漠化与植被指数（NDVI）、地表辐射温度（LST）之间的关系，提出了综合反映沙漠化土地生物物理特征的遥感监测指数——沙漠化遥感监测差值指数（DDI），为沙漠化遥感监测提供有效的定量化方法。     

Outlier detection algorithms and their performance in GOCE gravity field processing

The satellite missions CHAMP, GRACE, and GOCE mark the beginning of a new era in gravity field determination and modeling. They provide unique models of the global stationary gravity field and its variation in time. Due to inevitable measurement errors, sophisticated pre-processing steps have to be applied before further use of the satellite measurements. In the framework of the GOCE mission, this includes outlier detection, absolute calibration and validation of the SGG (satellite gravity gradiometry) measurements, and removal of temporal effects. In general, outliers are defined as observations that appear to be inconsistent with the remainder of the data set. One goal is to evaluate the effect of additive, innovative and bulk outliers on the estimates of the spherical harmonic coefficients. It can be shown that even a small number of undetected outliers (<0.2 of all data points) can have an adverse effect on the coefficient estimates. Consequently, concepts for the identification and removal of outliers have to be developed. Novel outlier detection algorithms are derived and statistical methods are presented that may be used for this purpose. The methods aim at high outlier identification rates as well as small failure rates. A combined algorithm, based on wavelets and a statistical method, shows best performance with an identification rate of about 99%. To further reduce the influence of undetected outliers, an outlier detection algorithm is implemented inside the gravity field solver (the Quick-Look Gravity Field Analysis tool was used). This results in spherical harmonic coefficient estimates that are of similar quality to those obtained without outliers in the input data.     

Development of a remotely sensed,historical land-cover change database for rural Chihuahua,Mexico

The purpose of this article is to describe the development of a remotely sensed, historical land-cover change database for the northwestern quarter of Chihuahua, Mexico, The database consists of multi-temporal land-cover classifications and change detection images. The database is developed to facilitate future investigations that examine urban–rural linkages as possible drivers of rural land-use and land-cover changes. To develop the needed land-cover change database, this study uses the North American Landsat Characterization (NALC) MSS triplicates because of their temporal depth and spatial breadth. Challenges exist, however, to effective classification and change detection using the NALC triplicates, including illumination differences across multiple scenes and periods caused by topographic and solar variations and the lack of ground reference data for historic periods. Therefore, creation of the database is a four step process. First, extensive pre-processing is performed to enhance comparability of multi-date images. Pre-processing includes topographic correction, mosaic creation and multi-date radiance normalization. Second, ancillary sources of land-cover data are combined with visual interpretations of enhanced images to define reference pixels used to classify the images using the maximum likelihood algorithm. Third, classification accuracy is assessed. Fourth, post-classification change detection is performed. Results indicate significant image improvements after pre-processing that permit very good overall classification (86.26% classified correctly) and change detection. To conclude, findings are presented that indicate significant changes to arid grasslands/shrublands and forest resources in mountainous regions.     

Particle size dependent response of aerosol counters

During an international workshop at the Institute for Experimental Physics of the University of Vienna, Austria, which was coordinated within the Committee on Nucleation and Atmospheric Aerosols (IAMAS-IUGG), 10 instruments for aerosol number concentration measurement were studied, covering a wide range of methods based on various different measuring principles. In order to investigate the detection limits of the instruments considered with respect to particle size, simultaneous number concentration measurements were performed for monodispersed aerosols with particle sizes ranging from 1.5 to 50 nm diameter and various compositions.The instruments considered show quite different response characteristics, apparently related to the different vapors used in the various counters to enlarge the particles to an optically detectable size. A strong dependence of the 50% cutoff diameter on the particle composition in correlation with the type of vapor used in the specific instrument was found. An enhanced detection efficiency for ultrafine hygroscopic sodium chloride aerosols was observed with water operated systems, an analogous trend was found for n-butanol operated systems with nonhygroscopic silver and tungsten oxide particles.     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.     

A multi-scale study on land use and land cover quality change: The case of the Yellow River Delta in China

This paper presents a case study of the Yellow River Delta in China, to trace land use and land cover changes during the past 20 years, with an emphasis on land quality changes. Three sets of data are used in this case study: remote sensing data derived from satellite images; crop yield data from statistics; and soil data collected by the researchers in the field. Our study reveals that at the regional scale, LUCC has taken place in a positive direction: vegetation cover has been expanding and crop yields per hectare have been on rise. However, while the overall eco-environment has improved, the improvement is uneven across the Delta region. At local levels, some areas show signs of increased salinization and declining organic content. Both natural forces and human activities are responsible for the LUCC, but human activities play a more important role. While some impacts of human activities are positive, the damages are often long-lasting and irreversible. We also conclude that it is necessary to use both macro data (such as remote sensing data) and micro data (data collected in the field) to study land quality change. The former are efficient in examining land quality changes at the regional scale, the latter can serve to verify ground patterns revealed from macro data and help to identify local variations, so as to get a comprehensive understanding of LUCC and promote sustainable land use and land management. This revised version was published online in July 2006 with corrections to the Cover Date.     

Structure and tectonic evolution of the Southern Eurasia Basin, Arctic Ocean

Multichannel seismic reflection data acquired by Marine Arctic Geological Expedition (MAGE) of Murmansk, Russia in 1990 provide the first view of the geological structure of the Arctic region between 77–80°N and 115–133°E, where the Eurasia Basin of the Arctic Ocean adjoins the passive-transform continental margin of the Laptev Sea. South of 80°N, the oceanic basement of the Eurasia Basin and continental basement of the Laptev Sea outer margin are covered by 1.5 to 8 km of sediments. Two structural sequences are distinguished in the sedimentary cover within the Laptev Sea outer margin and at the continent/ocean crust transition: the lower rift sequence, including mostly Upper Cretaceous to Lower Paleocene deposits, and the upper post-rift sequence, consisting of Cenozoic sediments. In the adjoining Eurasia Basin of the Arctic Ocean, the Cenozoic post-rift sequence consists of a few sedimentary successions deposited by several submarine fans. Based on the multichannel seismic reflection data, the structural pattern was determined and an isopach map of the sedimentary cover and tectonic zoning map were constructed. A location of the continent/ocean crust transition is tentatively defined. A buried continuation of the mid-ocean Gakkel Ridge is also detected. This study suggests that south of 78.5°N there was the cessation in the tectonic activity of the Gakkel Ridge Rift from 33–30 until 3–1 Ma and there was no sea-floor spreading in the southernmost part of the Eurasia Basin during the last 30–33 m.y. South of 78.5°N all oceanic crust of the Eurasia Basin near the continental margin of the Laptev Sea was formed from 56 to 33–30 Ma.     

《CT理论与应用研究》杂志新刊标和地幔速度模型的说明

在《ＣＴ理论与应用研究》杂志１９９４~２００１年本杂志“刊标”的基础上,在其上方增加了象征三维体视学成像的三角形四面体的透视图;该刊标的右下侧为医学断面成像扫描仪(包括各种Ｘ－ＣＴ机与核磁共振ＭＲＩ扫描仪等);其左下侧为三维地幔速度模型和地球核的示意图,切出有两个地幔剖面,表示纵波速度二维变化的剖面。该速度剖面系根据赵大鹏教授的理论和计算方法,按照地球上的两个大圆弧做计算和绘制的彩色图,排在本期封４:第一大圆弧,从北极经西巴基斯坦(２８°Ｎ, ６４°Ｅ)到马尔代夫群岛(３°Ｎ,７３°Ｅ);第二大圆弧从马尔代夫群岛点(３°Ｎ,７３°Ｅ)连接巴布新几内亚之南点(１２°Ｓ,１５０°Ｅ),来计算两剖面速度分布并作图的结果,其具体分布参见封４的两条彩色剖面和相应的地理位置图。由于赵教授这篇论文[１]在中国国内只有很少数图书馆收藏,在Ｅｌｓｅｖｉｅｒ Ｓｃｉｅｎｃｅ的ＥＰＳＬ网站上一般人只能查到摘要,本刊对于该地幔速度模型的制作方法和所用数据资料,该模型的优越性和特征进行了叙述,他所用的地震事件数目,多达７１２８个;用于层析反演成像的震相到时数多到近一百万条。该速度如下的特点:在所采用的速度结构中,包含用几个复杂形状的地质速度界面,如莫霍面,以及下沉板块的分界     

克孜尔水库大坝的面波检测

1999年 3月 15日克孜尔地震之后对克孜尔水库坝体出现的裂缝进行了面波勘探。首先介绍了面波勘探法的基本原理 ,然后通过典型剖面检测与资料处理找出异常区、带并进行解释。试验表明面波勘探法适用于克孜尔水库大坝监测