东湖污染物来源的智能识别方法

为识别东湖污染物来源,建立排污口与主要致污因子之间的对应关系,提出了污染物来源智能识别方法;该方法巧妙耦合了对应分析、模糊C-均值聚类及聚类有效性函数等方法,并用加速遗传算法有效解决了这一复杂问题。使用该方法于东湖污染物来源识别,快速得出了排污口与污染物之间的6类对应关系,为东湖污染综合治理提供了合理的决策依据。该方法在排污口众多、污染物来源复杂的城市水体污染治理中,具有一定的推广应用价值。     

基于有序聚类法的风化岩体定量分带研究

应用有序聚类法对辽宁省锦凌水库坝基的风化岩体进行定量分带,得出结果与地质观察方法、规范法等所得出的结果进行比较。并应用岩体风化差异系数计算各种方法下的各风化带的风化差异系数,综合分析,给出各最终推荐结果,按照有序聚类方法分析所得的结果进行风化岩体分带。     

基于密度的小生境粒子群算法在空间信息服务选择中的应用

针对现有空间信息服务选择技术的不足,提出了一种基于粒子群优化算法的多目标优化策略,通过同时优化多个QoS参数,产生一组满足约束条件的Pareto最优解。针对多峰函数的多目标优化问题,采用基于改进密度聚类的小生境技术,保证了解的多样性。构建了模拟试验环境,验证了算法的可行性和效率。     

出租车轨迹数据的南京人群出行模式挖掘

针对现有出租车轨迹数据挖掘中时间序列邻近度量方法存在的问题,提出一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,进而研究城市人群出行行为的时空差异。以南京市为例,结合电子地图对出行模式的空间分布特征进行分析,证明了本文所提出的方法的有效性。实验结果表明:在空间分布上,工作日出租车出行模式按照平均出行频次由高到低排序,从城市中心向四周扩散,呈中心环状分布,出行模式区域界限较为明显,同类出行模式分布区域对应相似的功能。提出了一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,有效地分析城市人群出行行为的时空差异。     

On the spatial distribution of buildings for map generalization

Information on spatial distribution of buildings must be explored as part of the process of map generalization. A new approach is proposed in this article, which combines building classification and clustering to enable the detection of class differences within a pattern, as well as patterns within a class. To do this, an analysis of existing parameters describing building characteristics is performed via principal component analysis (PCA), and four major parameters (i.e. convex hull area, IPQ compactness, number of edges, and smallest minimum bounding rectangle orientation) are selected for further classification based on similarities between building characteristics. A building clustering method based on minimum spanning tree (MST) considering rivers and roads is then applied. Theory and experiments show that use of a relative neighbor graph (RNG) is more effective in detecting linear building patterns than either a nearest neighbor graph (NNG), an MST, or a Gabriel graph (GssG). Building classification and clustering are therefore conducted separately using experimental data extracted from OpenStreetMap (OSM), and linear patterns are then recognized within resultant clusters. Experimental results show that the approach proposed in this article is both reasonable and efficient for mining information on the spatial distribution of buildings for map generalization.     

机载激光雷达及高光谱的森林乔木物种多样性遥感监测

利用机载LiDAR和高光谱数据并结合37个地面调查样本数据,基于结构差异与光谱变异理论,通过相关分析法分别筛选了3个最优林冠结构参数和6个最优光谱指数,在单木尺度上利用自适应C均值模糊聚类算法,在神农架国家自然保护区开展森林乔木物种多样性监测,实现了森林乔木物种多样性的区域成图。研究结果表明,(1)基于结合形态学冠层控制的分水岭算法可以获得较高精度的单木分割结果(R~2=0.88,RMSE=13.17,P0.001);(2)基于LiDAR数据提取的9个结构参数中,95%百分位高度、冠层盖度和植被穿透率为最优结构参数,与Shannon-Wiener指数的相关性达到R~2=0.39—0.42(P0.01);(3)基于机载高光谱数据筛选的16个常用的植被指数中,CRI、OSAVI、Narrow band NDVI、SR、Vogelmann index1、PRI与Shannon-Wiener指数的相关性最高(R~2=0.37—0.45,P0.01);(4)在研究区,利用以30 m×30 m为窗口的自适应模糊C均值聚类算法可预测的最大森林乔木物种数为20,物种丰富度的预测精度为R~2=0.69,RMSE=3.11,Shannon-Wiener指数的预测精度为R~2=0.70,RMSE=0.32。该研究在亚热带森林开展乔木物种多样性监测,是在区域尺度上进行物种多样性成图的重要实践,可有效补充森林生物多样性本底数据的调查手段,有助于实现生物多样性的长期动态监测及科学分析森林物种多样性的现状和变化趋势。     

黑龙江省新林-塔源地区地球化学特征及成矿远景预测

通过对黑龙江省新林-塔源地区1∶5万水系沉积物测量数据的统计分析,结合多学科知识,对研究区Au、Ag、As、Sb、Bi、Cu、Pb、Zn、Mo、W、Cr、Ni、Hg 13种元素的平均值、标准离差、变异系数、相关性和元素空间分布情况等各项地球化学参数特征进行因子分析及聚类分析,总结出各元素的地球化学分布特征及地质意义。通过对研究区典型矿床的综合研究,总结出区域成矿地质和地球化学条件,结合单元素异常和组合异常的解释评价,最终认为矿集区北部有找到表生铅锌多金属矿的可能,而南部是寻找隐伏铅锌多金属矿的有利地段。     

胶东半岛小震丛集特征研究

以最邻近事件距离算法为基础,结合混合概率密度分布对胶东半岛地区的小震丛集特征进行分析。结果表明：1）该地区存在明显的地震成丛现象,且近年来丛集率显著提高;2）乳山震群和莱州地震前,半岛地区均存在b值降低和丛集率升高的现象。分析认为,低b值异常配合高丛集率可能是该区域地震活动较好的预测指标。     

BDS-3多频信号最优线性组合及特性分析

围绕BDS-3多频模糊度解算中的最优组合观测量选取问题,采用模糊聚类分析法分别实现不同基线长度下三频、四频及五频最优组合观测量的选取及特性分析。结果表明,随着频率数的增加,高质量线性组合数目急剧增多;相比于三频、四频,五频更有利于形成总噪声水平小的组合观测量、长基线模糊度的单历元快速固定及实现实时精密定位。     

Objective array design for three-dimensional temperature and salinity observation: Application to the South China Sea

In this study, a moored array optimization tool (MAOT) was developed and applied to the South China Sea (SCS) with a focus on three-dimensional temperature and salinity observations. Application of the MAOT involves two steps: (1) deriving a set of optimal arrays that are independent of each other for different variables at different depths based on an empirical orthogonal function method, and (2) consolidating these arrays using a K-center clustering algorithm. Compared with the assumed initial array consisting of 17 mooring sites located on a 3°×3° horizontal grid, the consolidated array improved the observing ability for three-dimensional temperature and salinity in the SCS with optimization efficiencies of 19.03% and 21.38%, respectively. Experiments with an increased number of moored sites showed that the most cost-effective option is a total of 20 moorings, improving the observing ability with optimization efficiencies up to 26.54% for temperature and 27.25% for salinity. The design of an objective array relies on the ocean phenomenon of interest and its spatial and temporal scales. In this study, we focus on basin-scale variations in temperature and salinity in the SCS, and thus our consolidated array may not well resolve mesoscale processes. The MAOT can be extended to include other variables and multi-scale variability and can be applied to other regions.