A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology

Cellular automata (CA) models can simulate complex urban systems through simple rules and have become important tools for studying the spatio-temporal evolution of urban land use. However, the multiple and large-volume data layers, massive geospatial processing and complicated algorithms for automatic calibration in the urban CA models require a high level of computational capability. Unfortunately, the limited performance of sequential computation on a single computing unit (i.e. a central processing unit (CPU) or a graphics processing unit (GPU)) and the high cost of parallel design and programming make it difficult to establish a high-performance urban CA model. As a result of its powerful computational ability and scalability, the vectorization paradigm is becoming increasingly important and has received wide attention with regard to this kind of computational problem. This paper presents a high-performance CA model using vectorization and parallel computing technology for the computation-intensive and data-intensive geospatial processing in urban simulation. To transfer the original algorithm to a vectorized algorithm, we define the neighborhood set of the cell space and improve the operation paradigm of neighborhood computation, transition probability calculation, and cell state transition. The experiments undertaken in this study demonstrate that the vectorized algorithm can greatly reduce the computation time, especially in the environment of a vector programming language, and it is possible to parallelize the algorithm as the data volume increases. The execution time for the simulation of 5-m resolution and 3 × 3 neighborhood decreased from 38,220.43 s to 803.36 s with the vectorized algorithm and was further shortened to 476.54 s by dividing the domain into four computing units. The experiments also indicated that the computational efficiency of the vectorized algorithm is closely related to the neighborhood size and configuration, as well as the shape of the research domain. We can conclude that the combination of vectorization and parallel computing technology can provide scalable solutions to significantly improve the applicability of urban CA.     

Random encounters in probabilistic time geography

Probabilistic time geography considers the encounter of moving agents to be random; therefore, a quantitative time geography analysis must consider the actual encounter probability. The existing algorithm of encounter probability is oriented over a discrete space and is sensitive to the unit definition of a virtual grid; thus, it is not suitable for continuous space. For this reason, a new method is presented in this paper for the encounter of two moving agents in continuous space. When the encounters are less than a specified distance threshold apart, an encounter event occurs based on the probability of the product, which is calculated by their respective probability density functions over their respective potential location areas. This probability provides a quantitative basis for predicting the likelihood of two agents meeting, as well as the location of this meeting point. Finally, the validity of the proposed model is verified by an experiment, which uses tracking data to calculate the encounter probabilities of three zebras and analyse the distribution characteristics of these probabilities over time and space.     

Local meteorology in a northern Himalayan valley near Mount Everest and its response to seasonal transitions

An automatic weather station(AWS) has been installed at the Qomolangma Station of the China Academy of Sciences(QOMS) since 2005, in a northern Himalayan valley near Mount Everest, with an altitude of 4,270 m a.s.l.. Nine years of meteorological records(2006–2014) from the automatic weather station(AWS) were analyzed in this study, aiming to understand the response of local weather to the seasonal transition on the northern slopes of Mount Everest, with consideration of the movement of the subtropical jet(STJ) and the onset of the Indian Summer Monsoon(ISM). We found:(1) Both the synoptic circulation and the orography have a profound influence on the local weather, especially the local circulation.(2) Southwesterly(SW) and southeasterly(SE) winds prevail alternately at QOMS in the afternoon through the year. The SW wind was driven by the STJ during the non-monsoon months, while the SE was induced by the trans-Himalayan flow through the Arun Valley, a major valley to the east of Mount Everest, under a background of weak westerly winds aloft.(3) The response of air temperature(T) and specific humidity(q) to the monsoon onset is not as marked as that of the nearsurface winds. The q increases gradually and reaches a maximum in July when the rainy period begins.(4) The alternation between the SW wind at QOMS and the afternoon SE wind in the pre-monsoon season signals the northward shift of the STJ and imminent monsoon onset. The average interval between these two events is 14 days.     

公路积水阻断与降雨关系的探讨

利用2011—2013年全国公路积水阻断资料,分析了公路积水阻断的时空分布特征,并对公路积水阻断与不同时效降雨的关系进行了探讨。结果表明,公路积水阻断事件发生时间主要集中在5—9月,其中7月最为频繁,公路积水阻断事件以07:00—14:00为第一多发时段,16:00—20:00为次多发时段。公路积水阻断与前24h内的降水关系更为密切。区域不同,公路积水阻断随各强度降水变化的特点也不尽相同。经过开立方根处理后的降水因子与公路积水阻断发生的频次服从于高斯分布。其中,区域1公路积水阻断与处理后的1h最大降水因子关系密切,相关系数大于0.91;区域2和3公路积水阻断与处理后的6h最大降水因子关系密切,相关系数均在0.8以上;区域4公路积水阻断则与处理后的24h最大降水因子关系密切,相关系数在0.75左右。对于任何一个区域,诱发公路积水阻断的不同时效降水都处于一个较大的空间。对于给定的降水量只能判断公路积水阻断发生的可能性大小。     

基于MICAPS4的智能网格预报平台设计与实现

随着我国智能网格预报业务的开展,海量高分辨率客观数据需要便捷的分析显示及产品制作平台高效处理。该文基于MICAPS4（Meteorological Information Comprehensive Analysis and Processing System Version 4.0,人机交互气象信息处理和天气预报制作系统）设计并实现智能网格预报平台,采用MVVM（模型-视图-视图模型,model-view-viewmodel）设计模式,实现业务逻辑与视图的分离,通过对各子功能模块的划分,降低模块之间的耦合度,具有良好的可扩展性。平台实现了高分辨率网格预报数据的显示分析和产品输出,开发了基于等值线、网格、关键点等智能化预报制作工具,集成了降水时间拆分、温度极值订正等客观预报方法,开发了降水、温度、相对湿度等要素一致性处理方法,可有效帮助预报员提高工作效率,同时能够确保产品之间的一致性。平台继承MICAPS4的微内核组件服务、高性能渲染引擎和开放式插件扩展管理等优良特性,实现面向智能网格预报的业务编排、智能编辑和算法集成。目前,该平台已经实现业务应用,为全国智能网格预报业务提供重要支撑。     

1983—2015年湖南雨凇时空分布特征及影响因子

采用经验正交函数（EOF）并对1983—2015年湖南省95个地面气象站的雨凇观测资料以及与北半球海冰和西太平洋和东北印度洋海温资料的相关性进行分析。结果表明：湖南各站年均雨凇频次为219次,总体呈现北少南多、山区北侧少南侧多、平原地带少的分布特点;雨凇频次呈逐年下降趋势,且在湖南中北部地区下降趋势显著;湖南雨凇主要发生于相对湿度较大、极大风为偏北风且风速较小、最低气温在-3~0 ℃、最高气温在0~4 ℃的环境中。冬季同期（12月至次年2月）,北地群岛以东至白令海峡以北海域海冰密度和湖南雨凇频次的相关关系为显著正相关关系,而西北太平洋海温和湖南雨凇频次的显著负相关区域表现为C型分布。     

公路交通决策气象服务需求分析

采用问卷调查的方式,对气象、交通、公安等多部门公路交通决策气象服务关注的气象要素、产品类型和时段、服务改进方向等需求进行了调研。利用专家评分法对调查内容进行评估分析,并提出提升公路交通决策气象服务能力的相关建议。结果表明:专家对现有公路交通决策气象服务工作总体满意度较高,普遍认为公路交通决策气象服务在公路运输、运行调度、应急救援等方面发挥作用明显;行业领域不同需求的气象要素有所不同,交通部门专家对公路积雪、降雪、霾等要素给出的需求权重值明显高于气象部门专家给出的;不同类型的决策服务产品关注的气象要素和时效也有所不同,其中,监测类产品对低能见度、道路积雪要素最为关注;预报类产品对雨雪和大雾要素最为关注;预警类产品对大雾最为关注;而影响评估类产品对低能见度最为关注。监测类产品主要关注逐小时时段;预报和预警类产品重点关注未来3—12 h时段;而影响评估类产品主要关注日、月、季度时段。     

近30年来国外国家公园研究进展与启示

国家公园是自然保护和旅游研究领域的重要内容之一。本文以Web of Science数据库收录的近30年国外国家公园相关文献为基础,对筛选的451篇英文文献运用可视化软件CitespaceⅢ及系统综述的方法,从资源评估、环境影响、发展模式、规划、运营管理5个方面对国外国家公园研究主要内容进行述评,并对研究方法进行系统分析。最后,从国家公园立法、发展模式构建、管理内容与方法、社区参与模式与机制、环境监测与评估5个方面提出未来中国国家公园的研究方向。总体上看,国外有关国家公园的研究具有研究对象复杂、视角多元、方法综合的特征。在构建国家公园体制的大背景下,借鉴国际经验构建中国国家公园研究体系将对完善中国保护地相关研究、指导国家公园建设具有重要意义。     

广西区域经济极化时空格局研究

采用差异系数、极化指数并结合ESDA技术方法,对2004—2014年广西区域经济极化的演变趋势进行研究。11年中,广西整体经济极化程度呈增长趋势,以低水平极化为主;增长重心由东北部向中部移动,南宁、北海和柳州形成经济极化"三角区",经济落后区域从东南部转移到西北部,整体呈现"西低—中高—东低"的空间格局;大多数县域与周边区域的空间关联程度较小,离所倡导的区域化的经济发展模式还有一段距离。     

倾向性评分匹配法评估手术联合术中放疗在肝癌治疗中的安全性及有效性

目的 倾向性评分匹配法（Propensity Score Matching,PSM）评估手术联合术中放疗治疗原发性肝癌的安全性及疗效。方法 收集2009~2012年于笔者医院肝胆外科行手术联合术中放疗（intraoperative electron radiotherapy,IOERT）的18例原发性肝癌（primary liver cancer,PLC）患者的临床资料,其中16例经术后病理证实为肝细胞癌（hepatocellular carcinoma,HCC）,2例为肝内胆管细胞癌（intrahepatic cholangiocarcinomas,ICC）;采用倾向性评分匹配方法,按照1∶2比例从同期行单纯手术的原发性肝癌患者中筛选出36例做为对照组（32例HCC,4例ICC）,比较两组患者术中及术后并发症发生情况及HCC患者术后早期（2年内）复发率。结果 所有患者均获随访,随访率100%。两组患者术中出血量、术后3个月内肝功能、凝血功能、血常规及术后住院天数的比较,差异均无统计学意义（P>0.05）,仅在手术时长方面,联合IOERT组长于单纯手术组（P=0.000）。此外,联合IOERT组术后出现1例急性肾功能衰竭和1例胸腔积液,单纯手术组术后出现1例肝创面出血。在疗效方面,以两组48例HCC患者为研究对象,联合IOERT组的HCC患者为16例,其中6例在2年内复发,早期复发率为37.5%;单纯手术组的HCC患者为32例,20例在2年内复发,早期复发率为62.5%,两组早期复发率的比较,差异无统计学意义（P=0.101）。结论 手术联合术中放疗治疗原发性肝癌安全可行,尽管联合放疗组早期复发率低于单纯手术组,但差异并无统计学意义。