密度聚类算法在连续分布点云去噪中的应用

在原始测量获取的点云数据中,除了目标数据外,还有大量的噪声数据。噪声往往无规律地分布在目标物体周围,难以用统一数学模型区分。基于密度的聚类算法将簇定义为密度相连的点的最大集合,能发现任意形状、大小的类簇,将该算法应用在点云去噪中,能将密度分布连续点进行聚类,从中提取出目标点云。     

集聚型空间点模式结构信息提取研究

空间点模式是一个2维离散点集,点集中的每一个元素代表地球表面一个点状目标的空间位置。当2维离散点集具有集聚特征时,称其为集聚型空间点模式,它与空间聚类、制图综合和空间分析的许多具体应用紧密相关。如何提取集聚型空间点模式的结构信息(集聚子群的个数和对应的集聚中心)是其中尚未彻底解决的问题。作者以几何概率为理论基础,提出测度正方形区域内2维离散点集分布特征的H函数并推导其解析表达式,运用H函数设计和实现了集聚型2维离散点集结构信息提取的通用算法。利用该算法处理一个由居民地坐标数据得到的具有集聚特征的空间点模式,提取出其结构信息并进行可视表达。分别以该空间点模式中的各离散点为顶点和发生元生成Delaunay三角网和Voronoi图,在Delaunay三角网中保留面积最小的前1/10、前1/100三角形的顶点,在Voronoi图中保留面积最小的前1/10、前1/100邻近多边形的发生元,将可视表达的点集结构信息分别与依据Delaunay三角网和Voronoi图得到的结果进行对比分析。结果表明,运用H函数能够有效地提取出集聚型空间点模式的全局性结构信息,而Delaunay三角网和Voronoi图虽然能够反映其局部密度,但在提取全局结构信息时存在局限性。     

公共医疗卫生服务的空间可达性研究——以广州市海珠区为例

本文以第5次人口普查以及医疗卫生机构相关数据为基础,运用空间相互作用理论和模型,得到广州市海珠区各街区的公共医疗卫生服务可达性空间分布,并详细分析了医院等级系数对可达性指数的影响,为医疗卫生事业的发展规划提供辅助决策支持。     

基于GIS的森林资源变化研究

以黑龙江省汤旺河林业局部分区域森林资源为研究对象,以1968年和2004年森林分布图、小班数据库和其他数据资料为基础,以地理信息系统为技术支持,分析林地资源的数量、种类、空间分布及其森林资源的结构变化,在此基础上,调整恢复合理的森林结构,实现森林资源的永续利用。研究结果表明:有林地和非林地面积增加;针叶林所占比例减少,阔叶林增加;森林资源的结构不太合理,中龄林和近熟林面积占据较大比例。     

一定分布模式下的最优Lp估计

观测数据在一定的分布模式下,需从理论上解决究竟用多大的ｐ值进行Ｌｐ估计（最优ｐ值的确定）,本文基于渐近方差整体最小的原则,给出了最优Ｌｐ估计的定义。观测数据中含有粗差（异常值）的扰动,其误差分布可视为污染分布,作者分析了最优ｐ值的大小,结果表明,若观测数据中含有不同大小、数量的粗差,为使Ｌｐ估计差最小,则ｐ将取［１．２,１．５］中的某一定值,Ｌｐ估计结果最优,此结论对测量数据处理具有一定的参考价值     

Modeling the risk of spread and establishment for Asian longhorned beetle (Anoplophora glabripennis) in Massachusetts from 2008-2009

Land managers responsible for invasive species removal in the USA require tools to prevent the Asian longhorned beetle (Anoplophora glabripennis) (ALB) from decimating the maple-dominant hardwood forests of Massachusetts and New England. Species distribution models (SDMs) and spread models have been applied individually to predict the invasion distribution and rate of spread, but the combination of both models can increase the accuracy of predictions of species spread over time when habitat suitability is heterogeneous across landscapes. First, a SDM was fit to 2008 ALB presence-only locations. Then, a stratified spread model was generated to measure the probability of spread due to natural and human causes. Finally, the SDM and spread models were combined to evaluate the risk of ALB spread in Central Massachusetts in 2008–2009. The SDM predicted many urban locations in Central Massachusetts as having suitable environments for species establishment. The combined model shows the greatest risk of spread and establishment in suitable locations immediately surrounding the epicentre of the ALB outbreak in Northern Worcester with lower risk areas in suitable locations only accessible through long-range dispersal from access to human transportation networks. The risk map achieved an accuracy of 67% using 2009 ALB locations for model validation. This model framework can effectively provide risk managers with valuable information concerning the timing and spatial extent of spread/establishment risk of ALB and potential strategies needed for effective future risk management efforts.     

SOE技术在测绘成果网络分发服务系统中的应用研究

作为测绘信息化的重要组成部分,测绘成果网络分发服务系统的建设提升了测绘成果信息化管理水平,促进了测绘成果的推广应用。本文在总结福建省测绘成果网络分发服务系统建设成果的基础上,基于SOE技术解决其在推广应用过程中存在问题,提高了测绘成果的公共服务能力与水平。     

一种曲线拟合圆心坐标算法及精度分析

针对在工程应用中,经常需要根据某些圆形物体上的离散点求取其圆心坐标,而采用何种算法简单易行,其精度又与哪些因素有关的相关研究较少的问题,该文提出一种利用曲线拟合求取圆心坐标的简洁算法,并编程实现。然后采用模拟仿真结合统计分析的方法评估了该算法在不同条件下的拟合精度,得出测点误差越大,拟合精度越低;测点个数越多,分布越均匀,拟合精度越高;圆半径对拟合精度影响甚小等结论。在某工程项目中使用该算法得到的结果精度较高,验证了其有效可行,且与采用其他方法得到的坐标值较为接近,说明了该算法的可靠性高。     

干旱区地下水位降幅空间分布特性研究

基于GIS和地理统计学的理论、方法对所取观测井地下水位降幅数据进行空间分布特征分析。结果表明:数据服从正态分布,结构符合球状模型,空间数据存在东西方向和南北方向的二价函数趋势;地下水位降幅由北向南呈环状递减,最深降幅达30m,绿洲群大部分居于20～30m降幅之间,为地下水开采密集区,大于10m降幅的面积约69300hm2。利用Kriging最优内插法生成等值线图,可以更准确和直观地展示整个研究区的地下水资源状况、生态环境可能发生退化的区域及未来发展方向。     

Detecting patterns of climate change in long-term forecasts of marine environmental parameters

ABSTRACT

Forecasting environmental parameters in the distant future requires complex modelling and large computational resources. Due to the sensitivity and complexity of forecast models, long-term parameter forecasts (e.g. up to 2100) are uncommon and only produced by a few organisations, in heterogeneous formats and based on different assumptions of greenhouse gases emissions. However, data mining techniques can be used to coerce the data to a uniform time and spatial representation, which facilitates their use in many applications. In this paper, streams of big data coming from AquaMaps and NASA collections of 126 long-term forecasts of nine types of environmental parameters are processed through a cloud computing platform in order to (i) standardise and harmonise the data representations, (ii) produce intermediate scenarios and new informative parameters, and (iii) align all sets on a common time and spatial resolution. Time series cross-correlation applied to these aligned datasets reveals patterns of climate change and similarities between parameter trends in 10 marine areas. Our results highlight that (i) the Mediterranean Sea may have a standalone ‘response’ to climate change with respect to other areas, (ii) the Poles are most representative of global forecasted change, and (iii) the trends are generally alarming for most oceans.