Multidimensional visualisation of degrees of relevance of geographic data

The ever‐increasing number of spatial data sets accessible through spatial data clearinghouses continues to make geographic information retrieval and spatial data discovery major challenges. Such challenges have been addressed in the discipline of Information Retrieval through ranking of data according to inferred degrees of relevance. Spatial data, however, present an additional challenge as they are characteristically made up of geometry, attribute and, optionally, temporal components. As these components are mutually independent of one another, this paper suggests that they be ranked independently of one another. The representation of the results of the independent ranking of these three components of spatial data suggests that representation of the results of the ranking process requires an alternative approach to currently used textual ranked lists: visualisation of relevance in a three‐dimensional visualisation environment. To illustrate the possible application of such an approach, a prototype browser is presented.     

The design and implementation of SPIRIT: a spatially aware search engine for information retrieval on the Internet

Much of the information stored on the web contains geographical context, but current search engines treat such context in the same way as all other content. In this paper we describe the design, implementation and evaluation of a spatially aware search engine which is capable of handling queries in the form of the triplet of ?theme??spatial relationship??location?. The process of identifying geographic references in documents and assigning appropriate footprints to documents, to be stored together with document terms in an appropriate indexing structure allowing real‐time search, is described. Methods allowing users to query and explore results which have been relevance‐ranked in terms of both thematic and spatial relevance have been implanted and a usability study indicates that users are happy with the range of spatial relationships available and intuitively understand how to use such a search engine. Normalised precision for 38 queries, containing four types of spatial relationships, is significantly higher (p<0.001) for searches exploiting spatial information than pure text search.     

Gauss Krüger projection for areas of wide longitudinal extent

This paper describes a new algorithm for calculating all equations (direct and inverse transformation, convergence of meridians, linear distortion, calculus of surfaces, and arc‐to‐chord correction) for the Gauss–Krüger projection. Instead of using different equations for each problem, all the calculi are based on the equations used to obtain the direct transformation. These equations are also more accurate than previous ones and can be extended to an arbitrary width. This paper also explains how the Gauss–Krüger projection may satisfy the needs and requirements of civil engineers as well as Geographical Information Systems (GIS) users, particularly if extended beyond its usual 4° longitudinal range, and therefore can be used as a global reference system for GIS.     

Landslide susceptibility evaluation based on BPNN and GIS: a case of Guojiaba in the Three Gorges Reservoir Area

A landslide susceptibility evaluation is vital for disaster management and development planning in the Yangtze River Three Gorges Reservoir Area. In this study, with the support of remote sensing and Geographic Information System, 4 factor groups comprising 10 separate subfactors of landslide-related data layers were selected to establish a susceptibility evaluation model based on the back-propagation neural network including slope, aspect, plan curvature, strata and lithology, distance to faults, land use/land cover, Normalized Difference Vegetation Index, Normalized Difference Water Index, distance from roads, and effect of rivers. During model development, a three-layered interconnected neural network structure of 10 (input layer) × 20 (hidden layer) × 1 (output layer) was used for evaluating the landslide susceptibility in Guojiaba. At the same time, a back-propagation algorithm was applied to calculate the weights between the input layer and the hidden layer and between the hidden layer and the output layer. The results showed that the effect of slope has the highest weight value (0.2051), which is more than two times that of the other factors, followed by strata and lithology (0.1213) and then the effect of rivers (0.1201). At the end of the susceptibility evaluation, the area was divided into four zones such as very high, high, moderate and low susceptibility. For verification, the receiver operating characteristic curve for the back-propagation neural network-derived landslide susceptibility evaluation model was drawn, and the results showed that the area under the receiver operating characteristic curve was 0.8790 and the prediction accuracy was 88%. Furthermore, the results obtained from this article were then verified by comparing with the existing landslide historical data and multiple field-verified results. Lastly, the landslide susceptibility map will help decision makers in risk management, site selection, site planning, and the design of control engineering.     

Time-series analysis of monthly rainfall data for the Mahanadi River Basin, India

Time series analysis has two goals, modeling random mechanisms and predicting future series using historical data. In the present work, a uni-variate time series autoregressive integrated moving average (ARIMA) model has been developed for (a) simulating and forecasting mean rainfall, obtained using Theissen weights; over the Mahanadi River Basin in India, and (b) simulating and forecasting mean rainfall at 38 rain-gauge stations in district towns across the basin. For the analysis, monthly rainfall data of each district town for the years 1901-2002 (102 years) were used. Theissen weights were obtained over the basin and mean monthly rainfall was estimated. The trend and seasonality observed in ACF and PACF plots of rainfall data were removed using power transformation (α=0.5) and first order seasonal differencing prior to the development of the ARIMA model. Interestingly, the ARIMA model (1,0,0)(0,1,1) 12 developed here was found to be most suitable for simulating and forecasting mean rainfall over the Mahanadi River Basin and for all 38 district town rain-gauge stations, separately. The Akaike Information Criterion (AIC), goodness of fit (Chi-square), R 2 (coefficient of determination), MSE (mean square error) and MAE (mea absolute error) were used to test the validity and applicability of the developed ARIMA model at different stages. This model is considered appropriate to forecast the monthly rainfall for the upcoming 12 years in each district town to assist decision makers and policy makers establish priorities for water demand, storage, distribution, and disaster management.     

On the role of visualisation in fisheries management

Environmental change has focused the attention of scientists, policy makers and the wider public on the uncertainty inherent in interactions between people and the environment. Governance in fisheries is required to involve stakeholder participation and to be more inclusive in its remit, which is no longer limited to ensuring a maximum sustainable yield from a single stock but considers species and habitat interactions, as well as social and economic issues. The increase in scope, complexity and awareness of uncertainty in fisheries management has brought methodological and institutional changes throughout the world. Progress towards comprehensive, explicit and participatory risk management in fisheries depends on effective communication. Graphic design and data visualisation have been underused in fisheries for communicating science to a wider range of stakeholders. In this paper, some of the general aspects of designing visualisations of modelling results are discussed and illustrated with examples from the EU funded MYFISH project. These infographics were tested in stakeholder workshops, and improved through feedback from that process. It is desirable to convey not just modelling results but a sense of how reliable various models are. A survey was developed to judge reliability of different components of fisheries modelling: the quality of data, the quality of knowledge, model validation efforts, and robustness to key uncertainties. The results of these surveys were visualized for ten different models, and presented alongside the main case study.     

公安行业警用地理信息平台建设思路及进展

从地理信息技术发展和公安行业对警用地理信息共享应用需求出发,介绍了开展全国警用地理信息平台建设背景和必要性,并重点就警用地理信息平台的概念及其体系结构组成、全国警用地理信息平台建设思路、建设进展和后续发展规划等进行了系统论述。     

浅析GIS空间数据库

空间数据库是GIS的核心。GIS所涉及的主要是空间数据,所以对于GIS数据库的大量研究都跟空间数据结构和管理模式相关。该文分析了GIS空间数据的特征及其对数据库管理系统的要求,探讨了几种GIS空间数据的管理模式。     

陕西省明长城资源管理信息系统的设计与实现

陕西省明长城调查成果涉及大量的数据,为了科学合理地对这些数据进行管理,构建了陕西省明长城资源管理信息系统。本文介绍了基于GIS技术构建该系统的主要技术和方法。系统采用了两层架构设计方法,在ArcGIS Explorer平台上,利用Visual Studio进行插件式开发,实现了陕西省明长城资源管理信息系统的建设。该系统的建设提高了数据的管理水平,为长城保护工作提供了更加科学的决策支持。