地球空间信息相关论文摘要

基于球面投影的单站地面激光扫描点云构网方法;应用聚类分析方法进行实测重力数据的选点优化;产生最佳Tuned模板的蜜蜂交配算法;移动道路测量系统及其在科技奥运中的应用;三维工程勘察信息系统建设及其应用     

微软和ESRI联合推出数据融合解决方案

近日,在加利福尼亚州圣地亚哥举行的ESRI全球用户大会上,微软公司和ESRI公司联合推出了数据融合解决方案。这是一个支持公共安全与国土安全解决方案的体系结构。该解决方案由两个业界领导者开发,用于帮助公共安全和国土安全领域的专业人员更加有效地防御当前不断增加的有形和无形的安全威胁。此外,该解决方案还可以增强政府机构预测、评估和应对自然灾害的能力。     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

数据智能驱动城市可持续发展

在数字经济时代,数据成为城市发展的新资源,数据智能成为城市可持续发展的新技术,如何发挥城市数据的价值是新型智慧城市发展的重要命题。新型智慧城市是数字基础设施和传统基础设施融合的系统,而城市大脑就是支撑城市可持续发展的数字基础设施,就像是城市的数据智能操作系统.     

应急测绘保障体系若干关键问题研究

  Objectives   China is one of the countries with the most severe natural disasters in the world. There are many types of natural disasters and high frequency of disasters. It often causes huge economic losses and casualties in the disaster area. Combining the key technologies of the internet of things(IOT), the Internet, and geographic information for surveying and mapping, so it is possible to grasp the disaster situation in a timely and efficient manner. Thereby we could scientifically and effectively formulate disaster prevention and mitigation strategies, and implement emergency rescue measures, which are of great significance to the safety of people’s lives and property.  Methods   The development of big data and disaster reduction technologies has brought new possibilities for disaster management and emergency response. Geographic information big data provides basic support for emergency rapid response, location and navigation big data provides location information of personnel and materials for emergency rescue. Two- and three-dimensional visualization technology more realistically restores the disaster environment, and disaster models scientifically simulate the process of disaster occurrence, internet public opinion big data in disaster assessment also plays an important role. Big data is profoundly changing emergency rescue and disaster management with its ability to visualize, analyze and predict disasters. The combination of disaster big data and surveying and mapping geographic information technology has become an important means to improve disaster prevention and mitigation capabilities.  Results   We analyze and summary the integrated and comprehensive disaster reduction technology in the context of big data. The characteristics of integrated and comprehensive disaster reduction technology are elaborated, including comprehensive and thorough perception, broadband ubiquitous interconnection, precise and fast integration, ubiquitous positioning, efficient and intelligent processing, and intelligent collaborative services. The progress of integrated comprehensive disaster reduction technology is reviewed, which includes indoor and outdoor high-precision integrated positioning, rapid integration of multi-source data, scene fusion and enhanced visualization, typical disaster model construction and management, integrated disaster reduction comprehensive services, and China’s disaster reduction service system platform. In addition, we introduced the integrated comprehensive disaster reduction intelligent service system platform, APP and its application services, and summarized and prospected the integrated comprehensive disaster reduction technology and services.  Conclusions   The continuous development of big data technology provides new ideas and methods for people to analyze and solve emergency response problems, and provides a very convenient way for the sharing, integration, analysis, mining, and decision-making of comprehensive disaster reduction services. However, with the in-depth application of new concepts, new technologies, and new methods such as      

基于编码的GPS RTK架空送电线路平断面测量系统设计

详细讨论GPS RTK架空送电线路平断面测量系统的外业工作模式、地物编码、观测方法、数据格式和数据连接,以及基于AutoCAD和MicroStation V8两个图形平台的平断面图绘制功能。提供架空送电线路工程测量从外业数据采集到内业数据处理等一整套流程的解决方案,并且自主研发、实现了该软件系统。本系统现已在架空送电线路工程中得到广泛应用。     

1∶50000正射影像数据检查库设计及实现

国家1∶50000基础地理信息数据库更新工程正射影像数据库是1∶50 000数据库更新工程建设的重要组成部分.为保证正射影像数据各项指标符合项目设计要求,保证入库数据的质量,并为今后进一步更新提供依据,设计正射影像数据检查库,并在1∶50 000 DOM更新工程中实施和应用,实现了正射影像数据入库检查的程序化处理和自动质量评判.     

高度计波高数据同化对印度洋海域海浪模式预报影响研究

为提高海浪模式预报的精度,改善初始场是途径之一。研制了基于最优插值(OI)方法的海浪数据同化并行程序模块,并将其植入第三代海浪模式WAVEWATCH IIITM,建立了印度洋海域海浪同化预报方法,使用卫星高度计波高数据进行了同化预报试验。OI模块的并行设计使得植入同化模块的海浪模式仍能以并行方式运行。文中5°S以北印度洋海域为目标区域,嵌套在WAVE-WATCH IIITM的全球网格中,使得目标区域开边界条件得到较好解决。同化数据使用Jason-2高度计测量有效波高(SWH)沿轨数据。海浪同化预报模式由大气模式WRF(Weather Research andForecasting)输出的1小时一次的海面10 m风场驱动。将同化的模式结果(SWH)、无同化的模式结果(SWH)分别与高度计沿轨数据(SWH)进行比较,表明同化改善模式预报初始场的效果是明显的。以同化初始场出发进行海浪预报试验,结果表明,高度计波高数据同化在一定程度上可改进海浪短期预报的精度。     

基于众源轨迹数据的人造地表覆盖增量信息提取

目前,我国已研制出2000年、2010年两期30m分辨率全球地表覆盖数据集。为了保持该数据集的现势性,需要及时发现全球地表覆盖增量信息并更新相应数据。采用遥感影像、测绘数据提取全球地表覆盖变化信息的传统方式,存在费用高,不及时等问题。近年来众源地理数据迅猛发展,特别是由于众源轨迹数据具有免费共享、可靠性强与准实时等优点被广泛应用在交通道路信息提取的应用中。经分析我们发现轨迹数据与人造地表覆盖之间存在一定的对应关系,因此,本文研究提出了一种采用众源轨迹提取人造地表覆盖增量信息的方法。该方法首先对原始轨迹数据进行预处理,然后将轨迹数据栅格化,再依据轨迹点栅格覆盖比率进行人造地表覆盖数据粗提取并去除微小孔洞及独立栅格单元,最后将其与全球人造地表覆盖数据作栅格运算提取人造地表覆盖增量信息,并用纽约市实际轨迹数据验证了该方法的可行性。