3维数字地球快速缓冲区分析算法

提出一种应用在3维数字地球中的通过图形处理器(GPU)快速实现矢量数据缓冲区分析的算法。使用一张4通道的纹理图作为容器将地理实体的矢量数据传入GPU,利用GPU的高效并行特性,将目标缓冲区纹理中的每个像素所对应的矢量坐标与原实体进行距离量算,在一次渲染中得到缓冲区纹理,最后提取出缓冲区纹理的边界。选择中国的流域和湖泊矢量数据,将本文算法与两种传统的CPU算法进行了缓冲区分析计算、测试和对比。结果显示,本文算法相对于传统矢量算法效率提高了9—16倍,相对于传统栅格算法效率提高11—20倍。实验证明,该算法计算简单,效果明显,特别是随着数据量增大,缓冲区计算速度显著优于传统算法,并能有效解决传统矢量法缓冲区分析中的数据自相交问题。     

基于ArcGIS Server的医院网络地理信息服务系统

为解决目前医院地理信息服务系统在信息共享、空间分析等方面的不足,采用ArcGIS Server组件、C#编程语言、SQL Server数据库研发了医院网络地理信息服务系统。该系统以天地图作为基础地理数据,融合医院空间与医疗信息,并部署到互联网环境中。除具有医疗专题信息的网络浏览与查询外,系统还实现了诸多空间分析、地学统计等功能,既可为市民就医提供更全面的信息查询,又可为医疗事故的突发与应急提供技术支撑。     

Small target extraction based on independent component analysis for hyperspectral imagery

A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target information hided in high-dimensional data and projects them into low-dimensional space. Secondly, the feature images are selected with kurtosis. At last, small targets are extracted with histogram image segmentation which has been labeled by skewness.     

Spatio-temporal data model based on relational database system

In this paper, the entity-relation data model for integrating spatio-temporal data is designed. In the design, spatio-temporal data can be effectively stored and spatiao-temporal analysis can be easily realized.     

Surface description for urban climate studies: A gis based methodology

In order to understand the nature of the urban climate, predict the effects of urbanization, or attempt to ameliorate some of the negative hydroclimatic effects of urbanization, it is necessary to have a good understanding of the role and significance of the urban surface. This paper presents a methodology which uses GIS to represent the characteristics and morphology of the urban surface, which can be used to describe a site objectively, model fluxes, or ensure spatial consistency between measured and modelled data, all of which can vary through time. The methodology is illustrated with respect to Chicago, Illinois. Surface data collected at three spatial scales were used to construct a georeferenced database which was linked to an objective, dynamic accessing system. Spatial variability of surface cover, derived hydroclimatic attributes, and modelled fluxes associated with changes in the urban environment are used to illustrate potential applications of the approach.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

A new approach for finding an appropriate combination of texture parameters for classification

This article is an attempt to suggest a new approach for eliminating the lengthy process of selecting various parameters for extracting texture features and to quantify the relative importance of the parameters affecting textural classification. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyse the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. Results of the classification of an Indian urban environment using spatial property (texture) have also been reported. It was observed that the classification incorporating texture features using grey level co-occurrence matrix and wavelet-based approach improves the overall accuracy in a statistically significant manner in comparison to pure spectral classification.     

Characterizing wetland dynamics: a post-classification change detection analysis of the East Kolkata Wetlands using open source satellite data

The East Kolkata Wetlands is a unique resource recovery system. The Ramsar Convention recognized it as a ‘Wetland of International Importance’ in August 2002. However, the long-term resource exploitation and land use changes in the dynamic ecosystem have resulted in non-linear environmental responses. This is an attempt using open source remote sensing datasets to capture the spatio-temporal transformation of the wetland resulting from various anthropogenic activities. Landsat MSS and TM imageries of 1973, 1980, 1989, 2001 and 2010 were classified using Maximum Likelihood Classifier to monitor the wetland change; however, to study wetland dynamics, the post-classification wetland change detection maps have been generated for two temporal phases, i.e. 1973–1989 and 1989–2010. This study finds that the area under wetlands has reduced comprehensively in the past 40 years due to the conversion of wetlands into various other uses such as urban expansion of the Kolkata metropolitan city.     

Models for analyzing the driving force of cultivated land supply change

This paper focuses on a series of quantitative analysis models, such as grey relational analysis model, hierarchical cluster analysis model, principal component analysis model, linear regression model and elastic coefficient model. These models are used to analyze the comprehensive function and effect of driving forces systemically, including analysis on features, analysis for differentiating the primary and the secondary, analysis on comprehensive effects, analysis of elasticity, analysis of prediction. The primary and characteristic factors can be extracted by analysis of features and analysis for differentiating the primary and the secondary. Analysis on prediction and elasticity can predict the area of cultivated land in the future and find out which factors exert great influence on the cultivated land supply.     

The design and composition of persuasive maps

Persuasive maps are ubiquitous in society, yet cartographers have largely neglected to conduct serious, holistic research on them. Persuasive maps represent a form of visual communication that differs markedly from scientific geovisualization. First, many of these maps' communicative goals are anathema to those of scientific representation. Second, many persuasive maps ignore and defy established cartographic conventions. This article argues two things. First, the cartographic discipline can gain insight about how maps communicate information from the longitudinal and holistic analysis of persuasive maps. By comparing the differences and similarities of persuasive maps to scientific geovisualizations, researchers can begin to understand how persuasive maps communicate differently than scientific ones. Second, breaking persuasive maps down into composite parts may make it possible to identify persuasive map norms (i.e., methods of design that are embraced by producers of persuasive maps). The results of a content analysis of 256 persuasive maps are discussed. The article concludes that it may be possible to take the most statistically significant results from this study to begin identifying different rhetorical styles of persuasive maps.