ERDAS平台遥感专题信息提取及专题图制作

对遥感数据进行专题信息提取和制作专题图是遥感图像处理的一个重要的内容。本文基于ERDAS IMAGINE操作平台,介绍对遥感专题信息的提取过程和专题图的制作流程。     

遥感图像土地覆被专题信息提取方法综述

土地覆被是全球变化研究的重要内容，而专题信息获取是其研究的前提和基础，如何有效地利用丰富的遥感数据源获取高精度的土地覆被专题信息，对于实时动态监测具有重要的意义.在综合分析当前主要的遥感信息提取方法基础上，将土地覆被专题信息提取方法归纳为目视解译、基于统计分析的图像分类、多源信息复合和基于对象的专题信息提取四大类，并综述了各种方法的优缺点、适用领域和应用情况，最后对其研究方向和发展趋势进行了展望，指出地学专家知识、人工智能、非线性理论以及“面向地块”的信息提取方法是其发展方向.     

基于ArcScan的遥感影像中水域信息快速提取方法

将遥感信息的动态性和地理信息系统的分析功能相结合,可以快速、准确地分析水域动态变化。作者在总结前人研究的基础上,提出了基于ArcScan自动矢量化水体边界、快速提取水域信息的方法,文章主要介绍了ArcScan模块、研究流程与具体的方法,并以安徽巢湖2个时期的水域信息提取为例,取得了很好的效果;实践表明,在遥感图像分类的基础上,基于ArcScan自动提取水域信息的方法获得底图要素,可以大大提高专题制图的质量、效率和灵活性。     

基于混合特征空间MRF(Markov Random Filed)模型的高分辨率遥感影像水体提取

水体信息提取是遥感图像在水资源调查与利用、水生态监测等应用中的关键技术之一.针对现有的水体指数法或影像分类法在水体边界处理效果不够精确、易产生误提取和漏提取等问题,提出一种基于混合特征空间与MRF模型图像分割算法的水体提取新算法.结合遥感图像颜色特征与归一化差异水体指数NDWI创建混合特征空间,将遥感图像中的像素作为MRF模型中的随机变量,构建基于混合特征的能量函数,使用迭代的图割算法(Graph Cut)最小化能量函数确定水体边界,然后根据已提取的水体主体的水体指数及颜色特征等信息对水体边界进行自适应精细化处理.对石梁河水库水体提取的实验表明,该方法能够自动对周边环境复杂的水库水体信息进行提取,并且水体边界的提取效果良好,达到较高的水体提取精度.     

基于空间形态特征遥感边缘信息的提取方法

边缘信息是地物间波谱差异的反映.仅仅考虑灰度差异并不能满足专题信息-地物边缘提取的需要.加入地物的空间形态特征依据,可以使边缘信息提取更准确.在灰值形态学梯度算法和多方位形态结构元素形态学理论分析基础上,提出了提取遥感图像边缘信息的新方法.叙述了结构元素的设计和边缘提取过程,给出了应用实例并得到良好的视觉效果.     

TM遥感图像中居民点的自动提取

介绍了一种TM遥感图像中居民点目标自动提取的方法.针对TM遥感图像的光谱特征,提出一种基于多波段信息的图像分割模型,提取出居民点、道路及河滩地等光谱相近的地物.然后依据居民点的形态特征分离道路,并利用空间关系知识分离出河滩地.试验结果表明该方法能快速准确地识别提取TM遥感图像中的大部分居民点.     

基于LinkNet卷积神经网络的高分辨率遥感影像水体信息提取

针对高空间分辨率(简称高分辨率)遥感影像在水体信息提取时准确度不高的问题,采用LinkNet卷积神经网络模型对高分辨率遥感影像进行水体信息提取,验证该网络模型对于水体信息提取的可行性及有效性.首先选取包含水体的影像数据作为训练数据,然后构建LinkNet卷积神经网络模型,并利用构建好的网络模型训练得到水体信息的先验模型,最后采用该模型对真实高分辨率遥感影像进行水体信息提取,并与经典算法比较.实验结果表明:LinkNet卷积神经网络模型能够实现高分辨率遥感影像水体信息的高精度提取,且优于经典算法.     

辐射沙脊群地貌因子自动提取模型

使用常规遥感图像处理方法提取江苏沿海辐射沙脊群地貌因子,需要大量的人工解译工作,费时费力效率较低。研究使用Model Builder建模工具构建沙脊群地貌因子的自动提取模型,实现了地貌信息的一站式实时提取,避免多次重复工作,能够快速有效地得到较为准确的地貌因子。依据辐射沙脊群水边线、沙脊中心线自动化提取算法,在模型中集成了遥感图像处理和GIS的数据转换与空间分析功能。使用三期Landsat TM影像进行了提取试验;并将结果与原影像、传统目视解译方法获得的地貌特征数据进行了比较验证。结果表明,该方法有较高的实用意义,在水边线、沙脊中心线信息提取速度快、精度较高。     

海战场的目标检测与识别

针对海战场图像信息的目标检测与识别,提出了一种适于海战场区域特征的遥感图像目标检测与识别方法．研究采用线性滤波器将图像划分为若干个空间尺度,并对不同空间尺度的图像,根据生物视觉生理特性的原理,提取图像中目标的视觉显著性特征,此特征包含目标不同于其周围区域的程度和空间分布状态．根据分析提取的目标空间特征信息,使用支持向量机对视觉显著性特征图像进行分类,实现目标信息提取,并通过Dempster-Shafer证据理论的分析方法判断目标的相关信息及其置信度,达到识别目标的目的．实验结果表明：此方法能以高可靠性和高精确度检测出海战场图像信息中的目标,获取目标相关信息．     

基于卫星遥感的水体信息提取研究进展与展望

水体时空分布特征对于水资源监测与应用具有重要意义,而包括水体分布在内的地物覆盖类型分类和变化分析是遥感技术最常见的应用。对大区域的水体参数提取,尤其是高山无人区的水体的定量分析,利用卫星遥感数据进行水体位置、面积、形状和河宽等水体参数提取,不仅节省人力、保障安全,还提高了工作效率,已经成为一种快速获取水体参数的有效方法和手段。该文从4个方面对卫星遥感在水体信息提取上的应用现状进行综述:水体在电磁波波谱各波谱段的反射特性; 1980年以来国内外基于雷达和光学遥感数据提取水体信息的研究状况和具体应用方向;各种水体信息提取方法的工作原理和优缺点;应用卫星遥感技术提取水体信息面临的挑战和尚待解决的关键问题,利用遥感技术提取水体遥感信息的发展趋势展望。     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

正~~     

An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Wuhan University Journal of Natural Sciences TOTAL CONTENTS

<正>~~