基于Agent的网络地图服务聚合模型

为了给用户提供智能化、一体化的网络地图服务,提出基于Agent的地图服务聚合模型。设计基于Agent的服务搜索、注册、集成和交互模式,介绍面向角色的Agent功能模块,根据相应规则实现智能化处理。实验结果表明,该模型能够提高地图服务的自动聚合和交互能力,为用户使用带来便利。     

基于Hadoop的Web日志挖掘

基于单一节点的数据挖掘系统在挖掘Web海量数据源时存在计算瓶颈,针对该问题,利用云计算的分布式处理和虚拟化技术的优势,设计一种基于云计算的Hadoop集群框架的Web日志分析平台,提出一种能够在云计算环境中进行分布式处理的混合算法。为进一步验证该平台的高效性,在该平台上利用改进后的算法挖掘Web日志中用户的偏爱访问路径。实验结果表明,在集群中运用分布式算法处理大量的Web日志文件,可以明显提高Web数据挖掘的效率。     

A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality

Managing service quality is vital to retain customer satisfaction and augment revenues for any business organization. Often it is difficult to assess service quality due to lack of quantifiable measures and limited data. In this paper, we present a hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating service quality of urban transportation systems. The proposed approach consists of three steps. The first step involves development of a SERVQUAL based questionnaire to collect data for measuring transportation service quality. The participants provide linguistic assessments to rate the service quality criteria and the alternatives. In step 2, the linguistic ratings are combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the decision making process.The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. An application of the proposed approach for evaluation of service quality of metro in Montreal is provided.     

基于Jena的城市交通领域本体推理和查询方法

通过对城市交通信息进行抽象和分析,建立了城市交通领域本体库,并持久化存储到关系数据库。对比分析了基于Jena的语义推理机制及其所涉及的问题。构造交通信息的推理规则并在Jena平台下实现该领域基于语义的检索和路径查询功能,得出潜在的语义查询结果,给出了实现算法的描述和实验结果。为交通领域提高信息检索的查准率和查全率提供了一个有效的方法。     

Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data

Driven by a constantly accelerating increase of urban population in recent decades urban sprawl has become one of the most dynamic processes in the context of global land use transformations. The expansion of urban agglomerations is closely associated with a substantial increase of impervious surface. In Europe, methods for an accurate, fast and cost-effective mapping and assessment of impervious surface on a state-wide or national scale have not been established so far. This study presents an approach for estimating the impervious surface based on a combined analysis of single-date Landsat images and road network and railway vector data using Support Vector Machines and functionalities of geographic information processing. The modeling aims at the provision of data on the impervious surface for the total of residential, industrial and transportation-related areas. The derived information is provided for the administrative units of communities. The output of the procedure is a vector data file providing the ‘percent impervious surface of built-up areas’ (PIS_B) and the ‘percent impervious surface of the total of built-up and transportation-related areas’ (PIS_BT) for the administrative units of communities. The developed method is tested for a study area covering almost one third of the German territory. The results prove the suitability of the approach for a widely automated and area-wide mapping of impervious surfaces. Using reference data sets of three cities (Leipzig, Ludwigshafen, Passau) we realized a mean absolute error of 19.8% and an average error of 6.4% for the percent impervious surface modeled on the basis of the Landsat images. The final product resulting from a combination of the imperviousness raster derived from the satellite images with the transportation-related vector information showed a mean difference of 1% to 4% compared to corresponding reference data and results of previous studies. For the year 2000 our research shows that 45.3% of the area occupied by settlements and transport infrastructure in the German federal state of Bavaria, 44.6% in the state of Baden-Württemberg and 42.6% in the state of Saxony was covered by impervious surface.     

A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection

DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually.The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.     

A Reducing Saturation Method for DMSP/OLS Nighttime Light Image Combining Landsat Data

Defense Meteorological Satellite Program/Operational Linescan System(DMSP/OLS)is one of the data sources,which can effectively reflect human activities of earth surfaces.During the past decade,DMSP/OLS had been extensively applied in urban extraction and extension study.In the recent year,the Vegetation Adjusted NTL Urban Index(VANUI)has been proposed and had proven to be a simple,convenient and high precision desaturation index to extract urban area.In VANUI method,negative values of imagery were directly eliminated to remove water body,which not only removed the bridge over the river and building but also extracted the aquaculture areas along the coast,thus,this method reduced the extraction accuracy.This paper proposed a new index\|RwNTLI,combining DMSP/OLS nighttime light data and the vegetation index (NDVI)and water index (MNDWI)which were constructed by Landsat data.In this study,Guangzhou was taken as experimental area.By comparing the VANUI index with the ability to identify ground objects as well as the ability to alleviate saturation regions,the result showed RwNTLI index could effectively solve the problem of VANUI as well as eliminate saturation effect of nighttime light imagery.Among them,the correlation between RwNTLI index and RCNTL is better than that of VANUI index and RCNTL.Therefore,RwNTLI index is a simple and effective index of luminous desaturation,which has more advantages than VANUI index in describing the characteristics of night lights of urban areas and will have higher application value in urban built\|up areas in the future.     

IBI and CA Model based Extraction of Urban Built\|up Areaand Its Application：A Case Study in Shanghai

At present,the automatic extraction of urban built\|up area is still a problem.Taking Shanghai city as an example,this research uses the binary image,which was derived from an IBI(index\|based built\|up index)image,as the geographical cellular automaton initial input data.This was then imported to the extended cellular automata model for further processing.After a series of processing such as thresholding,corrosion and connectivity test,the urban built\|up area was simulated and can be extracted.Based on this method,the urban built\|up area of Shanghai in five different years between 1987 and 2015 was extracted using multi\|temporal Landsat images of Shanghai.In addition,the urban growth intensity index,the concentric buffers analysis and radar chart analysis were calculated and used to analysis spatiotemporal pattern of Shanghai urban expansion in the 28 study years.The result shows that the built\|up area of Shanghai was expanded from 195 km² in 1987 to 1759 km² in 2015,which is eight times as large as that in 1987.In the period between 1987 and 2002,the urban built\|up area expanded mainly along the North\|South axis of the Huangpu River.However,after 2002 the expansion rate was increased more quickly,and the direction of the expansion was shifted to an east to west direction.Generally speaking,Shanghai has experienced a rapid urban expansion in the recent three decades.     

Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures

The term urban heat island describes the phenomenon of altered temperatures in urban areas compared to their rural hinterlands. A surface urban heat island encompasses the patterns of land surface temperatures in urban areas. The classical indicator to describe a surface urban heat island is the difference between urban and rural surface temperatures. However, several other indicators for this purpose have been suggested in the literature. In this study, we compared the eleven different indicators for quantifying surface urban heat islands that were most frequently used in recent publications on remote sensing-based urban heat island assessments. The dataset used here consists of 263 European cities with monthly mean temperatures from MODIS data products for July 2002, January 2003 and July 2003. We found that (i) the indicators individually reveal diurnal and seasonal patterns but show rather low correlations over time, and (ii) for single points in time, the different indicators show only weak correlations, although they are supposed to quantify the same phenomenon. Differentiating cities according to thermal climate zones increased the relationships between the indicators. Thus, we can identify temporal aspects and indicator selection as important factors determining the estimation of urban heat islands. We conclude that research should take into account the differences and instabilities of the indicators chosen for quantifying surface urban heat islands and should use several indicators in parallel for describing the surface urban heat island of a city.