土地规划的自然过程基础与大数据时代的方法探索

随着城市化与工业化程度不断加深,产业空间结构不断重组,导致土地供需矛盾日益突出,国土资源无序开发日益严重,因而优化国土资源空间格局,成为生态文明建设的首要任务。同时,科学合理配置土地资源对土地规划提出了更高要求,传统土地规划方法有待改革。在基于尊重自然、顺应自然的开发理念下,总结土地自然过程基础对土地规划的影响,实现“山水路林田生命共同体”的协调规划发展。其次,“大数据”时代的来临,云计算、空间数据整合、云分析等技术对土地规划方法提供新的技术支撑;最后,针对土地规划数据特殊性、移动用户终端的广泛性,提出应创建土地规划云服务平台,使土地规划实现数据集成管理和更新,从而提高土地规划质量。     

面向问题的空间应用表达与实现

讨论空间应用的一种面向问题的表达方法与实现机制。为解决空间应用的描述问题,在建立时空一体化空间数据模型基础上,定义了对SQL进行扩展的时空复合查询语言,实现了对空间应用问题的非过程化描述;研究复杂空间应用的表达问题,讨论时空复合查询语言的限制,并在语言中引入流机制,通过空间应用问题的组合实现更为复杂的空间应用,并支持空间数据分布式计算;最后给出若干空间应用实例及其面向问题的表达。     

Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.     

The granulometrical characteristics of a slowly-moving dust cloud

A torn-up road offered the opportunity to sample a dust cloud continuously at different heights during a time interval of 51 hours. In particular the granulometrical characteristics of the dust caught were investigated. It appears that if the air layer in the vicinity of a dust cloud is not too turbulent, the cloud will be clearly granulometrically stratified. The coarse material moves chiefly at the bottom of the cloud, whereas the fine material will occur both at the bottom and at the top. The experiment also shows that the higher the dust in the cloud, the worse it is sorted. Above a critical height, however, the degree of sorting increases again. The variation of the mean dust diameter d₅₀, as a function of the height z, can be expressed in a simple semi-logarithmic equation. The variation of the dust quantity G, as a function of the height z, can also be expressed in a semi-logarithmic form but the correlation is higher when a power equation is used. The ratio of fine silt to coarse silt seems to vary parabolically with height. One can only speak of an optimal transport height in the case of particles > 16 μm. For finer particles, the turbulence of a normal air stream is usually high enough to carry the particles anywhere in the dust cloud, so that one can no longer speak of an optimal transport height. The granulometrical border between aeolian transport in saltation and aeolian transport in suspension lies, according to the results of the experiment, at a diameter of about 63 μm.     

Maximum likelihood environmental calibration and the compute program WACALIB a correction

A recently discovered error in the part of the computer program WACALIB that implements maximum likelihood (ML) calibration has been discovered and corrected. The new version of WACALIB has been re-run with all the data-sets from which results based on the earlier version of WACALIB had been published. The new results suggest that ML regression and calibration perform as well or even better than weighted averaging (WA), at least when judged by the apparent root mean squared error. Further work involving cross-validation is required to evaluate more fully the relative performance of WA and ML approaches.     

遥感数据用户需求融合处理技术

从遥感数据需求文本中获取时间要素并进行语义计算是实现遥感数据需求文本可理解的关键步骤之一。通过对遥感数据需求文本时间要素及其构成形式的分析,建立了融合时间形式表达与语义计算一体的时间本体,并在此基础上给出了遥感数据需求文本时间信息抽取及其语义计算方法。实验表明,该方法对于遥感数据需求文本的时间要素具有较好的解析与推理效率,有助于提升自然语言获取遥感数据的效率。     

利用点云检测室内导航元素的方法综述

根据建筑物室内墙壁的空间姿态特征, 建立了一种自动绘制室内平面图的点云向量追踪算法。首先截取一定厚度的室内墙体点云并将其投影至水平面, 在投影平面上建立正方形格网, 对投影后的平面点进行分割管理, 并通过八邻域算法对网格内点云进行聚类。然后采用网格重心法对聚类后的点云数据进行抽稀, 并根据邻域内点间距与连线向量夹角大小对抽稀后的点进行追踪排序, 建立追踪方向的向量序列, 结合向量序列中相邻值夹角的突变情况完成不同墙面的点云分割。最后采用最小二乘算法对分割得到的相同墙面点云进行直线拟合, 求取相邻墙体直线的交点, 建立房屋墙体平面投影线段及其空间连接关系, 依序输出墙体投影线段, 完成房屋平面图的绘制并导出DXF格式数据交换文件。通过对某小区建筑物室内扫描数据的分析, 对所提算法进行验证, 结果表明所提算法可准确快速地对室内三维激光扫描点云进行分析处理, 并完成室内建筑物平面图的绘制。     

基于云团特征的短时临近强降水预报技术

通过分析2005-2008年影响浙江的梅汛期强降水云团特征,将云团分为偏北型、居中型和偏南型,研究这三种类型云团云顶亮温与地面1小时强降水极值和10mm/h以上降水覆盖面积关系,结果表明偏南型和偏北型云团有较多相似特征,而居中型云团较其他两种云团则有较多相反特征.通过分析1小时强降水相对于云团中心移动路径的落区,指出梅汛期云顶1小时变温和亮温梯度与地面1小时强降水落区无明显配对模型.随后利用天气形势场资料,分析强降水云团与环境要素场的关系,指出云顶亮温的宏观特征与中高层的垂直速度、水汽通量密切相关,最后尝试建立三种类型强降水云团成熟阶段云顶亮温和地面降水人工神经网络预报方程,给预报员提供参考.     

景观指数的并行计算方法

随着地理信息科学和系统的发展,GIS数据的时空分辨率和数据量呈现爆炸式的增长趋势。传统的基于个人计算机的景观指数计算软件难以有效快速地完成海量数据的空间分析。针对该问题,本文提出了一个高效的景观指数并行计算方法。首先对原有的并查集连通域标记算法进行了2点改进：① 在第2次遍历数据时,增加了计算斑块面积、周长等斑块基本信息的功能,为景观指数的计算提供必要参数;② 在第2次遍历过程中,增加了重新标记连续序号的功能,减少了原有算法在合并操作后造成的序号不连续,需要重新遍历数据的开销。在此基础上,本文利用MPI并行编程库,采用数据分割和主从进程协同的并行计算模式实现了景观指数的并行计算。实验表明,在保证计算正确性的基础上,本文的并行算法大幅度提高了景观指数的计算性能,为快速分析大规模数据的景观形态和格局提供了有效手段。     

霰粒子下落速度对云系及降水发展影响的数值研究

云和降水的形成是动力过程与微物理过程相瓦作用的产物,云数值模式中的微物理过程参数化方案对云和降水发展过程有直接影响.在云数值模式中,粒子群体的下落速度都足用质量加权下落末速度公式来表达,而且不同的模式采用的公式存在差异,质量加权下落末速度中参数取值不同,引起的粒子下落末速度不同.为了了解粒子下落末速度变化对云系和降水发展的影响,对2004年8月12日一次冷锋降水过程,利用中尺度ARPS模式做模拟研究.在分析降水机制的基础上,对霰这一下落末速度较大的降水粒子,做下落末速度(Vg)的敏感性试验,从动力、热力、微物理的角度,通过数值模拟对比分析了霰下落末速度减小对降水分布和强度、云系的移动、云系的宏观热力和动力场的影响,并给出了影响的途径和机理.结果表明:Vg变化对云的厚度和含水量有影响,下落末速度减小对冰晶、雪、霰的含水量垂直分布及分布随时间变化影响较大,其中,霰的含水量显著减少,雪的含水量增加,并调整了云中水质粒的空间分布;Vg减小对地面累积总降水量的分布影响较小,但对降水强度的分布影响较大.Vg减小时,降水强度减小,降水时间延迟,因此,霰下落末速度变化将调整底层降水分布;对于云系的移动情况基本上没有影响,但对云中水质粒的空间分布有影响;霰下落末速度变化影响云中霰的融化和撞冻增长从而影响热力场.末速度减小时,霰和雪的融化罱明显减小,导致非绝热冷却率的减小,引起下沉气流的减小.