自适应差分进化的遥感影像自动模糊聚类方法     

张帅  钟燕飞  张良培 《测绘学报》2013,42(2):239-246

遥感影像模糊聚类方法可以在无需样本分布信息的情况下获取比硬聚类方法更高的分类精度,但其仍依赖先验知识来确定影像地物的类别数。本文提出了一种基于自适应差分进化的遥感影像自动模糊聚类方法,该方法利用差分进化搜索速度快、计算简单、稳定性高的优点,以Xie-Beni指数为优化的适应度函数,在无需先验类别信息的情况下自动判定图像的类别数,并结合局部搜索算子对遥感影像进行最优化聚类。通过模拟影像以及两幅真实遥感图像的分类实验表明,本文方法不仅可以正确地自动获取地物类别数,而且能够获得比K均值、ISODATA以及模糊K均值方法更高的分类精度。  相似文献   

沉管隧道工程海水密度精确测量     

丁建华 《江苏测绘》2013,(5):30-31

沉管隧道沉放施工过程中,出于结构安全及施工定位的需要,必须在现场精确测量沉放各阶段的海水密度值.文章结合在某大型跨海沉管隧道工程沉放作业过程中实际操作,提出了快捷、准确的海水密度现场测量方法,可供相似工程作业参考.  相似文献   

基于密度的加权K-Means算法     

万广通  王行风 《测绘科学》2013,38(4):146-148

K-Means算法是比较流行的局域聚类算法,但由于其存在需要输入聚类数目以及对初始聚类中心敏感等缺陷,本文提出了一种基于密度的加权K-Means聚类算法来初始化聚类中心。该算法定义了点的密度函数和聚类中心函数,通过一定评价函数获取聚类中心。该方法获取的聚类中心不仅周围密度比较大,而且各个聚类中心之间相关性比较小,从而有效的减少了聚类时间,提高算法效率。  相似文献   

An accurate selectivity estimation method for window queries and an implementation thereof     

Changxiu Cheng  Jing Yang  Xiaomei Song  Shanli Yang  Lijun Wang 《地球空间信息科学学报》2013,16(2-3):81-89

Spatial selectivity estimation is crucial to choose the cheapest execution plan for a given query in a query optimizer. This article proposes an accurate spatial selectivity estimation method based on the cumulative density (CD) histograms, which can deal with any arbitrary spatial query window. In this method, the selectivity can be estimated in original logic of the CD histogram, after the four corner values of a query window have been accurately interpolated on the continuous surface of the elevation histogram. For the interpolation of any corner points, we first identify the cells that can affect the value of point (x, y) in the CD histogram. These cells can be categorized into two classes: ones within the range from (0, 0) to (x, y) and the other overlapping the range from (0, 0) to (x, y). The values of the former class can be used directly, whereas we revise the values of any cells falling in the latter class by the number of vertices in the corresponding cell and the area ratio covered by the range from (0, 0) to (x, y). This revision makes the estimation method more accurate. The CD histograms and estimation method have been implemented in INGRES. Experiment results show that the method can accurately estimate the selectivity of arbitrary query windows and can help the optimizer choose a cheaper query plan.  相似文献   

Geo-scape,a granularity depended spatialization tool for visualizing multidimensional data sets     

Kontaxaki Sofia  Kokla Margarita  Kavouras Marinos 《地球空间信息科学学报》2013,16(4):275-284

Recently, the expertise accumulated in the field of geovisualization has found application in the visualization of abstract multidimensional data, on the basis of methods called spatialization methods. Spatialization methods aim at visualizing multidimensional data into low-dimensional representational spaces by making use of spatial metaphors and applying dimension reduction techniques. Spatial metaphors are able to provide a metaphoric framework for the visualization of information at different levels of granularity. The present paper makes an investigation on how the issue of granularity is handled in the context of representative examples of spatialization methods. Furthermore, this paper introduces the prototyping tool Geo-Scape, which provides an interactive spatialization environment for representing and exploring multidimensional data at different levels of granularity, by making use of a kernel density estimation technique and on the landscape “smoothness” metaphor. A demonstration scenario is presented next to show how Geo-Scape helps to discover knowledge into a large set of data, by grouping them into meaningful clusters on the basis of a similarity measure and organizing them at different levels of granularity.  相似文献   

GIS-based stratification of malaria risk zones for Zimbabwe     

Isaiah Gwitira  Amon Murwira  Mhosisi Masocha  Fadzai M. Zengeya  Munyaradzi Davis Shekede  Joconiah Chirenda 《国际地球制图》2013,28(11):1163-1176

Abstract

Malaria burden has considerably declined in the last 15 years mainly due to large-scale vector control. The continued decline can be sustained through malaria risk stratification. Malaria stratification is the classification of geographical areas according to malaria risk. In this study, ecological niche modelling using the maximum entropy algorithm was applied to predict malaria vector habitat suitability in terms of bioclimatic and topographic variables. The output vector suitability map was integrated with malaria prevalence data in a GIS to stratify Zimbabwe into different malaria risk zones. Five improved and validated malaria risk zones were successfully delimited for Zimbabwe based on the World Health Organization classification scheme. These results suggest that the probability of occurrence of major vectors of malaria is a key determinant of malaria prevalence. The delimited malaria risk zones could be used by National Malaria Control programmes to plan and implement targeted malaria interventions based on vector control.  相似文献   

A graph-based approach to detecting tourist movement patterns using social media data     

Fei Hu  Chaowei Yang  Yongyao Jiang 《制图学和地理信息科学》2013,40(4):368-382

ABSTRACT

Understanding the characteristics of tourist movement is essential for tourist behavior studies since the characteristics underpin how the tourist industry management selects strategies for attraction planning to commercial product development. However, conventional tourism research methods are not either scalable or cost-efficient to discover underlying movement patterns due to the massive datasets. With advances in information and communication technology, social media platforms provide big data sets generated by millions of people from different countries, all of which can be harvested cost efficiently. This paper introduces a graph-based method to detect tourist movement patterns from Twitter data. First, collected tweets with geo-tags are cleaned to filter those not published by tourists. Second, a DBSCAN-based clustering method is adapted to construct tourist graphs consisting of the tourist attraction vertices and edges. Third, network analytical methods (e.g. betweenness centrality, Markov clustering algorithm) are applied to detect tourist movement patterns, including popular attractions, centric attractions, and popular tour routes. New York City in the United States is selected to demonstrate the utility of the proposed methodology. The detected tourist movement patterns assist business and government activities whose mission is tour product planning, transportation, and development of both shopping and accommodation centers.  相似文献   

基于GIS的重庆市人口空间分布研究     

李静  罗灵军  钱文进  刘建 《地理空间信息》2013,11(2):42-46

基于重庆市2006～2010年人口数据,运用GIS技术从人口密度、人口集中指数及人口集聚度3个方面对重庆市人口空间分布规律进行了分析;同时,从地理空间分析的角度出发,分析了重庆市人口空间分布与自然、经济及社会因素之间的关系。  相似文献   

A novel method for discovering spatio-temporal clusters of different sizes,shapes, and densities in the presence of noise     

《International Journal of Digital Earth》2013,6(2):138-157

The discovery of spatio-temporal clusters in complex spatio-temporal data-sets has been a challenging issue in the domain of spatio-temporal data mining and knowledge discovery. In this paper, a novel spatio-temporal clustering method based on spatio-temporal shared nearest neighbors (STSNN) is proposed to detect spatio-temporal clusters of different sizes, shapes, and densities in spatio-temporal databases with a large amount of noise. The concepts of windowed distance and shared nearest neighbor are utilized to define a novel spatio-temporal density for a spatio-temporal entity with definite mathematical meanings. Then, the density-based clustering strategy is employed to uncover spatio-temporal clusters. The spatio-temporal clustering algorithm developed in this paper is easily implemented and less sensitive to density variation among spatio-temporal entities. Experiments are undertaken on several simulated data-sets to demonstrate the effectiveness and advantage of the STSNN algorithm. Also, the real-world applications on two seismic databases show that the STSNN algorithm has the ability to uncover foreshocks and aftershocks effectively.  相似文献   

ParSymG: a parallel clustering approach for unsupervised classification of remotely sensed imagery     

《International Journal of Digital Earth》2013,6(5):471-489

ABSTRACT

Symmetry is a common feature in the real world. It may be used to improve a classification by using the point symmetry-based distance as a measure of clustering. However, it is time consuming to calculate the point symmetry-based distance. Although an efficient parallel point symmetry-based K-means algorithm (ParSym) has been propsed to overcome this limitation, ParSym may get stuck in sub-optimal solutions due to the K-means technique it used. In this study, we proposed a novel parallel point symmetry-based genetic clustering (ParSymG) algorithm for unsupervised classification. The genetic algorithm was introduced to overcome the sub-optimization problem caused by inappropriate selection of initial centroids in ParSym. A message passing interface (MPI) was used to implement the distributed master–slave paradigm. To make the algorithm more time-efficient, a three-phase speedup strategy was adopted for population initialization, image partition, and kd-tree structure-based nearest neighbor searching. The advantages of ParSymG over existing ParSym and parallel K-means (PKM) alogithms were demonstrated through case studies using three different types of remotely sensed images. Results in speedup and time gain proved the excellent scalability of the ParSymG algorithm.  相似文献