Porting of a wildfire risk and fire spread application into a cloud computing environment

Effective wildfire management is an essential part of forest firefighting strategies to minimize damage to land resources and loss of human lives. Wildfire management tools often require a large number of computing resources at a specific time. Such computing resources are not affordable to local fire agencies because of the extreme upfront costs on hardware and software. The emerging cloud computing technology can be a cost- and result-effective alternative. The purpose of this paper is to present the development and the implementation of a state-of-the-art application running in cloud computing, composed of a wildfire risk and a wildfire spread simulation service. The two above applications are delivered within a web-based interactive platform to the fire management agencies as Software as a Service (SaaS). The wildfire risk service calculates and provides daily to the end-user maps of the hourly forecasted fire risk for the next 112 hours in high spatiotemporal resolution, based on forecasted meteorological data. In addition, actual fire risk is calculated hourly, based on meteorological conditions provided by remote automatic weather stations. Regarding the wildfire behavior simulation service, end users can simulate the fire spread by simply providing the ignition point and the projected duration of the fire, based on the HFire algorithm. The efficiency of the proposed solution is based on the flexibility to scale up or down the number of computing nodes needed for the requested processing. In this context, end users will be charged only for their consumed processing time and only during the actual wildfire confrontation period. The system utilizes both commercial and open source cloud resources. The current prototype is applied in the study area of Lesvos Island, Greece, but its flexibility enables expansion in different geographical areas.     

Optimizing an index with spatiotemporal patterns to support GEOSS Clearinghouse

A variety of Earth observation systems monitor the Earth and provide petabytes of geospatial data to decision-makers and scientists on a daily basis. However, few studies utilize spatiotemporal patterns to optimize the management of the Big Data. This article reports a new indexing mechanism with spatiotemporal patterns integrated to support Big Earth Observation (EO) metadata indexing for global user access. Specifically, the predefined multiple indices mechanism (PMIM) categorizes heterogeneous user queries based on spatiotemporal patterns, and multiple indices are predefined for various user categories. A new indexing structure, the Access Possibility R-tree (APR-tree), is proposed to build an R-tree-based index using spatiotemporal query patterns. The proposed indexing mechanism was compared with the classic R*-tree index in a number of scenarios. The experimental result shows that the proposed indexing mechanism generally outperforms a regular R*-tree and supports better operation of Global Earth Observation System of Systems (GEOSS) Clearinghouse.     

基于三维激光扫描仪的建筑物建模应用研究

为分析三维激光扫描仪在建筑物建模方面的精度,针对传统实测的建模方式,采用基于三维激光扫描理论技术对某建筑进行扫描,从其数据获取、数据分析处理,到获得该建筑物的表面三维模型的过程入手,对比、分析与传统测量的建模方法所获得模型的精度及可靠性。结果表明,三维激光扫描仪所获得数据的精度完全达到了预期的要求,且可以大大节省数据建模的时间,突显了三维激光扫描技术的优势,也为三维激光扫描技术在其他领域的应用提供了科学参考。     

一次西风槽过程过冷云水分布特征观测研究

过冷云水生消演变规律是云物理学和人工影响天气的重要研究领域。根据Hobbs 1974年提出的假定,利用飞机、卫星、雷达和雨量计等观测资料,对2012年9月21日河北一次西风槽天气过程进行观测研究,分析其过冷云水分布特征及演变规律。结果表明,槽前云系过冷水区宽厚并且过冷水含量较高,云滴浓度和均立方根直径较大并且均匀,冷云区厚而且没有分层,没有暖云配合;近槽云系中冷云区小粒子浓度降低但云滴直径增大,冷云区夹有干层,云系变厚出现暖云配合,冷暖云液态水含量较高,冷暖云区大粒子和降水粒子浓度和尺度增大,中尺度云团移动较快;槽后云系中云滴浓度最大,但云滴均立方根直径明显减小,过冷水区出现的高度下降、厚度很薄、过冷水含量较低,冷、暖云之间有干层,暖云对应的大粒子浓度和降水粒子浓度非常大,地面降水主要由暖云过程产生;云水(过冷水)含量峰值常出现在云内逆温层的上方;利用云粒子测量系统(PMS)资料分析过冷云水生消演变特征与卫星和雷达资料具有较高的一致性。     

Analysis of the Microphysical Properties of a Stratiform Rain Event Using an L-Band Profiler Radar

This paper investigates spatial and temporal distributions of the microphysical properties of precipitating stratiform clouds based on Doppler spectra of rain particles observed by an L-band profiler radar.The retrieval of raindrop size distributions（RSDs） is accomplished through eliminating vertical air motion and isolating the terminal fall velocity of raindrops in the observed Doppler velocity spectrum.The microphysical properties of raindrops in a broad stratiform region with weak convective cells are studied using data collected from a 1320-MHz wind profiler radar in Huayin,Shaanxi Province on 14 May 2009.RSDs and gamma function parameters are retrieved at altitudes between 700 and 3000 m above the surface,below a melting layer.It is found that the altitude of the maximum number of raindrops was closely related to the surface rain rate.The maximum number of large drops was observed at lower altitudes earlier in the precipitation event but at higher altitudes in later periods,suggesting decreases in the numbers of large and medium size raindrops.These decreases may have been caused by the breakup of larger drops and evaporation of smaller drops as they fell.The number of medium size drops decreased with increasing altitude.The relationship between reflectivity and liquid water content during this precipitation event was Z = 1.69×10~4M~（1.5）,and the relationship between reflectivity and rain intensity was Z = 256I~（1.4）.     

面向海量遥感影像的数据模型与管理模型设计

分析了传统集中式存储管理的遥感影像管理体系的不足,提出了针对当前成几何级数倍增影像大数据管理的解决方案,包括数据集模型和云架构模型;并基于VMWare和ArcGIS平台实现了实验模型;通过实验数据分析,证明了新的数据模型和平台架构的科学性和高效性。     

基于语义的GP服务多层次发现算法

随着云技术的飞速发展,"一切资源皆服务"成为可能,"数字地球"的实现也不例外。观测技术的快速发展使数据资源变得很丰富,但数据利用率低是普遍存在的现象,如何完成空间数据信息的再加工是亟待解决的问题,在云时代,具有数据处理功能的服务是解决此问题的方法之一,如何描述、发现和集成数据处理服务,从云端服务池中发现最优的服务是其关键所在。为了提高服务的查全率和查准率,引入了本体的概念,服务的语义描述很大程度上提高了空间数据处理服务的应用范围,缓解了非专业用户和专业人员之间的沟通障碍。本文分析了相关领域服务匹配算法的优缺点,结合GP服务自身的特点,提出了本体的GP服务的多层次发现算法:通过包含关系和线索关系完成服务间隐含关系的挖掘,主要是父子关系和前驱后继关系的表述;扩展传统本体表达模型,增加包含和线索关系,为服务的查找做准备;服务的多层次查找,第一次筛选主要针对服务预处理中包含和线索关系的表达查找,第二次筛选利用神经网络的突触原理,结合传统的服务匹配算法,完成服务的准确查找。经试验证明,此方法大大地提高了服务的查准率和查全率,具有重要的实践意义。     

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Transition from the southern mode of the mei-yu front cloud system to other leading modes

Based on normalized six-hourly black body temperature （TBB） data of three geostationary meteorological satellites,the leading modes of the mei-yu cloud system between 1998 and 2008 were extracted by the Empirical Orthogonal Function （EOF） method,and the transition processes from the first typical leading mode to other leading modes were discussed and compared.The analysis shows that,when the southern mode （EOF1） transforms to the northeastern mode （EOF3）,in the mid-troposphere,a low trough develops and moves southeastward over central and eastern China.The circulation pattern is characterized by two highs and one low in the lower troposphere.A belt of low pressure is sandwiched between the weak high over central and western China and the strong western North Pacific subtropical high （WNPSH）.Cold air moves southward along the northerly flow behind the low,and meets the warm and moist air between the WNPSH and the forepart of the low trough,which leads to continuous convection.At the same time,the central extent of the WNPSH increases while its ridge extends westward.In addition,transitions from the southern mode to the dual centers mode and the tropical-low-influenced mode were found to be atypical,and so no common points could be concluded.Furthermore,the choice of threshold value can affect the number of samples discussed.     

全天空成像仪云量计算方法的改进

全天空成像仪（total sky imager 440,TSI-440）可以实现白天全天空云量的持续自动监测,时空分辨率较高,得到的云量计算结果更精确.首先介绍了TSI-440的基本原理和资料格式,并基于太湖地区2008年5-10月的TSI-440资料及无锡站地面观测资料,采用统计方法详细地分析了不同天气情况下图像的成像特征及云量的计算误差.结果发现：图像的成像特征与能见度密切相关,红蓝比值随着能见度的减小而增大.另外,仪器在处理阴天图像及复杂天空（多云）图像时,易造成一定的云量计算误差.针对上述问题,本文通过直方图分析,重新选定了红蓝比阈值（晴空点阈值0.62,云点阈值0.66）,基于新阈值计算的云量结果较仪器自带的处理结果更为准确,减小了因天气状况不同而产生的云量计算误差.