利用TM数据提取干旱区土地覆被信息的方法比较

以柴达木盆地香日德绿洲作为研究实验区,对该区域ETM遥感数据经过空间分辨率融合、主成分分析等方法进行空间信息增强及专题信息增强处理,组合最佳视觉背景图像,分别在不同背景图像上选择训练样本,利用最大似然法监督分类方法(MLC)、多空间尺度分层聚类(SSHC)和基于知识的模糊聚类方法(KFC)等分类器,分别用各自训练样本初始化各类别信息特征值,形成类别特征值模式库,分别以此为基础对待分样本进行分类,对初分类的结果经过类别合并、碎斑滤除以及重新编码赋色等分类后处理,得到最终分类结果及分类精度评价结果。从所获数据可以得出如下结论：从总体精度和Kappa值可知,SSHC和．KFC分类方法所获结果精度较高,总体精度比MLC分类结果约高于3％,SSHC之结果精度略高于KFC之结果;SSHC、KFC和MLC三种分类方法对该区域地表覆被信息的提取分类中,SSHC分类方法对耕地、石砾地、河滩和荒漠分类结果较好,KFC分类方法对耕地、沙地、河滩和荒漠分类结果较好,MLC分类方法对耕地、河滩和荒漠分类结果较好,三种分类方法对耕地、河滩和荒漠等三种地类的分类精度较高,用户精度都在80％以上,而对沙地和石砾地的分类结果其用户精度大都低于80％。     

PolarGlobe: A web-wide virtual globe system for visualizing multidimensional,time-varying,big climate data

The increasing research interest in global climate change and the rise of the public awareness have generated a significant demand for new tools to support effective visualization of big climate data in a cyber environment such that anyone from any location with an Internet connection and a web browser can easily view and comprehend the data. In response to the demand, this paper introduces a new web-based platform for visualizing multidimensional, time-varying climate data on a virtual globe. The web-based platform is built upon a virtual globe system Cesium, which is open-source, highly extendable and capable of being easily integrated into a web environment. The emerging WebGL technique is adapted to support interactive rendering of 3D graphics with hardware graphics acceleration. To address the challenges of transmitting and visualizing voluminous, complex climate data over the Internet to support real-time visualization, we develop a stream encoding and transmission strategy based on video-compression techniques. This strategy allows dynamic provision of scientific data in different precisions to balance the needs for scientific analysis and visualization cost. Approaches to represent, encode and decode processed data are also introduced in detail to show the operational workflow. Finally, we conduct several experiments to demonstrate the performance of the proposed strategy under different network conditions. A prototype, PolarGlobe, has been developed to visualize climate data in the Arctic regions from multiple angles.     

中国经济增长与制度变迁的空间面板数据分析

以North的体制经济学为理论依据,将新古典经济学的Solow增长模型扩展为一个包含制度变量的计量经济学模型,并结合空间面板数据分析方法,使用1997—2005年中国省区的社会经济数据实证检验了经济制度环境对经济增长的影响。研究结果表明:该时期的制度变迁对中国的经济增长具有显著贡献力,证实了North的制度经济学理论假设。此外,空间面板数据的分析方法深入地揭示了省域经济活动之间存在的空间自相关性,即地区之间通过技术扩散、要素转移以及社会文化交流等在地理空间上发生相互影响。     

基于多源数据的主体功能区划分方法——以广州市为例

以广州市为例,基于城市感知数据、遥感影像等多源数据,采用卷积神经网络对遥感影像进行了语义提取,将提取结果与兴趣点（Points of Interest）样方密度的功能用地识别结果进行补充校验,根据政策和规划文件建立功能用地与主体功能区之间的关联,利用信息熵分析广州市功能用地混合程度,以辅助判别主体功能区,最终得到广州市主体功能区划分结果。将划分结果与《广州市主体功能区规划（2008—2020年）》和《广州市城市总体规划（2017—2035年）》草案对比验证,结果表明文章所提出的方法精准度较高,并能体现广州市空间格局形态,反映主体功能区实际分布情况。     

走航测深数据的自动采集

本文介绍应用IBM微机实现走航实时水深及定位数据的自动采集系统。给出了联机系统方框图及采集、传送数据的程序流程图。并对IBM-PC/XT微机与测深仪之间的接口、数码转换和数据处理作了简要的叙述。     

松潘地区岩金统计成矿予测中泛克立格法的应用

川西北地区是国内重要的岩金普查靶区。本文对松潘地区的地质特征,泛克立格法原理,及在本区的应用情况作了介绍,对主要计算步骤,给出基本结果,对计算获得的有意义异常区,进行地质解释,并将此方法与趋势面分析进行对比。     

中国国家自然地图集Internet版的设计和研制

本文系统阐述了国家自然地图集Ｉｎｔｅｒｎｅｔ版的设计和研制过程中的若干问题,包括系统的概念设计、系统开发中的ＷｅｂＧＩＳ技术和策略,系统的主要功能和特色,以及系统维护和更新方案等。本系统从概念设计来看分为服务器端软件模块、浏览器端软件模块、国家自然地图集数据库支持等几个部分。系统开发中采取的ＷｅｂＧＩＳ技术和策略有:兼顾服务器端和客户端的综合型ＷｅｂＧＩＳ策略,基于Ｊａｖａ Ａｐｐｌｅｔ的 ＷｅｂＧＩＳ浏览器开发技术,基于Ｍａｐ Ｏｂｊｅｃｔ(ＭＯ)的ＷｅｂＧＩＳ服务器开发技术等３个方面。在系统的主要功能特色方面,本文从以下５个方面进行了论述:科学有序的内容结构、清晰精练并带导航的界面、富有特色的信息查询功能、多重表达的地图可视化效果、一定的空间信息分析和制图功能。在系统维护和更新方案上,本文从网络技术、数据更新、功能开发３个方面介绍了计划,并对今后的发展趋势进行了展望。     

基于深度学习的滑坡灾害易发性分析

滑坡灾害成因机理复杂、影响因素众多,深度学习作为当前人工智能领域的热点,能够更好地模拟滑坡灾害的形成并准确预测潜在的斜坡。为了挖掘深度学习在滑坡易发性的应用潜能,本文构建了一维、二维和三维的滑坡数据表达形式,并提出3种基于卷积神经网络模型（Convolutional Neural Networks, CNN）的滑坡易发性分析处理框架：基于CNN分类器、基于CNN与逻辑回归的融合和基于CNN集成,最后以江西省铅山县为研究对象进行验证,结果表明：所有基于CNN的易发性模型都能够获得准确且可靠的滑坡易发性分析结果。其中,基于二维数据的CNN模型在所有单分类器中预测精度最高,为78.95%。此外,二维CNN特征提取能够显著提升逻辑回归的预测精度,其准确率提升7.9%。最后,异质集成策略能够大幅度提升基于CNN分类器的滑坡预测精度,其准确率提升4.35%~8.78%。     

Simulations for multi-object spectrograph planet surveys

Radial velocity surveys for extrasolar planets generally require substantial amounts of large telescope time in order to monitor a sufficient number of stars. Two of the aspects which can limit such surveys are the single-object capabilities of the spectrograph, and an inefficient observing strategy for a given observing window. In addition, the detection rate of extrasolar planets using the radial velocity method has thus far been relatively linear with time. With the development of various multi-object Doppler survey instruments, there is growing potential to dramatically increase the detection rate using the Doppler method. Several of these instruments have already begun usage in large-scale surveys for extrasolar planets, such as Fibre Large Array Multi Element Spectrograph (FLAMES) on the Very Large Telescope (VLT) and Keck Exoplanet Tracker (ET) on the Sloan 2.5-m wide-field telescope.
In order to plan an effective observing strategy for such a program, one must examine the expected results based on a given observing window and target selection. We present simulations of the expected results from a generic multi-object survey based on calculated noise models and sensitivity for the instrument and the known distribution of exoplanetary system parameters. We have developed code for automatically sifting and fitting the planet candidates produced by the survey to allow for fast follow-up observations to be conducted. The techniques presented here may be applied to a wide range of multi-object planet surveys.