Quanyi Huang

The importance of spatial-temporal issues for case-based reasoning in disaster management

A disaster brings huge damages to both infrastructure and human beings. The rapid and efficient disaster management is critical for reducing the negative effects by the disasters. A widely accepted approach to assist disaster management is to find and learn the experiences from the similar cases in history. Thus, to record the whole procedure of each disaster, a digital disaster case structure is offered in this paper. The importance of spatial and temporal information for a digital disaster case is focused through the experiences of disaster management. Then a simplified case based reasoning method with the considering of spatial-temporal information is proposed. Comparing with the traditional cased based reasoning methods, it is simple to use and can handle the attributes with basic geospatial dimensions. The proposed method can be integrated to the widely constructed emergency platform as a part of functions of the disaster case repository for assisting the disaster management.

A Model of Spatial Data Integration Interoperability on Oracle Spatial

An Open GIS Consortium (OGC) white paper said that the future vision for sharing data might look like this: Each of the smaller counties or towns hosts its own online GIS. Each uses software and a data model selected to best meet its local needs, which is the objective of this paper studies to close with. This paper gives a model based on Oracle Spatial, within a local government or enterprise the spatial data is centralized storage, and with metadata interoperability, which enables organizations to use the right tool for the job while eliminating complicated data transfers and multiple copies of the same data throughout the enterprise or department. This paper has realized MapInfo and ArcGIS work together under the same oracle spatial database use trigger and storage process. And at another hand, with the situation of between the departments or enterprises this paper gives a three-tier structure solution: spatial data server, application server and application client. The application server is a mediation system, this model uses oracle application server as the mediation system, and through the application server the application client sends WMS or WFS request and get the map server for background application. The three-tier structure model exposes a GIS portal which is an online GIS for outside of the department. Any client can request the server if it accords with WMS or WFS specification.

A model of spatial data interoperability on Oracle Spatial

It has been acclaimed that the future vision for GIS data sharing might look like this: each of small counties or towns hosts its own online GIS; and each uses software and a data model selected to best meet its own needs. This paper gives a model based on Oracle Spatial, within a local government or enterprise the spatial data is in centralized storage, and with metadata interoperability, which enables the organizations to use the proper tool for the job while eliminating complicated data transfers and duplications throughout the enterprise or different departments. The MapInfo and ArcGIS software have been made to work together under the same oracle spatial database use trigger and storage process. On another hand, with the situation of between the departments or enterprises, a three-tier structure solution is given: spatial data server, application server and application client. The application server is a mediation system, this model uses oracle application server as the mediation system, and through the application server the application client sends WMS or WFS request and get the map server for background application. The three-tier structure model exposes a GIS portal which is an online GIS for external applications. Any client can request the server if it accords with WMS or WFS specification.

The application of GIS and RS for epidemics: a case study of the spread of highly pathogenic avian influenza in China in 2004-2005

Because of their inherent advantages, Geographic Information System (GIS) and Remote Sensing (RS) are extremely useful for dealing with geographically referenced information. In the study of epidemics, most data are geographically referenced, which makes GIS and RS the perfect even necessary tools for processing, analysis, representation of epidemic data. Comprehensively considering the data requirements in the study of highly pathogenic avian influenza (HPAI) coupled with the quality of the existing remotely sensed data in terms of the resolution of space, time and spectra, the data sensed by MODIS are chosen and the relevant methods and procedures of data processing from RS and GIS for some environmental factors are proposed. Through using spatial analysis functions and Exploratory Spatial Data Analysis (ESDA) of GIS, some results of relationship between HPAI occurrences and these potential factors are presented. The role played by bird migration is also preliminarily illustrated with some operations such as visualization, overlapping etc. provided by GIS. Through the work of this paper, we conclude: Firstly, the migration of birds causes the spread of HPAI all over the country in 2004-2005. Secondly, the migration of birds is the reason why the spread of HPAI is perturbed. That is, for some classic communicable diseases, their spread exhibits obvious spatial diffusion process. However, the spread of HPAI breaks this general rule. We think leap diffusion and time lag are the probable reasons for this kind of phenomena. Potential distribution of HPAI viruses (corresponding to the distribution of flyways and putative risk sources) is not completely consistent with the occurrences of HPAI. For this phenomenon, we think, in addition to the flyways of birds, all kinds of geographical, climatic factors also have important effect on the occurrences of HPAI. Through the case study of HPAI, we can see that GIS and RS can play very important roles in the study of epidemics.

Precipitation Interpolation by Multivariate Bayesian Maximum Entropy Based on Meteorological Data in Yun- Gui-Guang region, Mainland China

Precipitation interpolation has been a hot area of research for many years. It had close relation to meteorological factors. In this paper, precipitation from 91 meteorological stations located in and around Yunnan, Guizhou and Guangxi Zhuang provinces (or autonomous region), Mainland China was taken into consideration for spatial interpolation. Multivariate Bayesian maximum entropy (BME) method with auxiliary variables, including mean relative humidity, water vapour pressure, mean temperature, mean wind speed and terrain elevation, was used to get more accurate regional distribution of annual precipitation. The means, standard deviations, skewness and kurtosis of meteorological factors were calculated. Variogram and cross- variogram were fitted between precipitation and auxiliary variables. The results showed that the multivariate BME method was precise with hard and soft data, probability density function. Annual mean precipitation was positively correlated with mean relative humidity, mean water vapour pressure, mean temperature and mean wind speed, negatively correlated with terrain elevation. The results are supposed to provide substantial reference for research of drought and waterlog in the region.

Spatial Estimation of Mean Annual Precipitation (1951–2012) in Mainland China Based on Collaborative Kriging Interpolation

Spatially explicit distribution of mean annual precipitation are required in the quantitative research on several water-related issues. The difference of distribution of precipitation has complicated reasons, one of them being the spatial correlation between multivariate meteorological factors. In this study, collaborative kriging interpolation (CKI) was used to estimate the spatial distribution of mean annual precipitation in China. Precipitation data from 756 meteorological stations were used, and spatial correlations between seven meteorological factors were analyzed, including annual precipitation, average barometric pressure, average wind speed, average temperature, average water pressure, average relative humidity, and annual average sunshine hours. The estimation results were assessed by means of cross-validation with the mean error (ME), mean absolute error (MAE), and root mean square error (RMSE). The results indicated that adding the spatial correlation analysis between multivariate meteorological factors can help improve the prediction performance.

Research on Key Technologies for Jail Incident Prevention and Response System

For the purpose of the administrators’ capability enhancement of prison security prevention and response, and the implementation of emergency collaborative management, the paper points out the importance of building Jail Incident Prevention and Response System (JIPRS), and specifically describes the architecture and functions of the JIPRS, as well as puts forward interoperability emergency response system consisting of national, regional, prison three-level command centers. JIPRS includes emergency duty, resource management, forecasting and early-warning, event disposal, simulation exercise, and other functions. The critical technologies required in the JIPRS are expounded, including criminal risk recognizing and quantification, emergency analysis and decision, three-dimensional simulation and exercise, etc. These studies provide strong support for the JIPRS building at home and abroad.

Emergency Case Retrieval Based on Fuzzy Sets and Text Mining

Emergency management is such a domain where experiential knowledge could be easily collected, and is quite suitable for the application of case based reasoning. However, in practice there are two problems limiting the effectiveness of case based reasoning (CBR), the unstructured information and changing situation. This paper proposed an approach based on fuzzy sets and text mining to solve those two problems, which contains three steps: (a) representing the case based on fuzzy sets and text mining, (b) retrieving the similar case based on text classification, and (c) establishing connections of attributes and solutions based on Hownet. This approach could not only retrieve the most similar case, but also extract specific solutions from several cases.

Study on Scene-Driven Emergency Drill Method

Based on the analysis of traditional emergency drills and simulated emergency drill characteristics, the construction and express method of structured scene model was proposed, including the emergency scene classification, the setting of evolution and development conditions and the structured expression of emergency scene. The scene-driven key technology and model was described, such as the evolutionary relationship of scenes, the reasoning model of scene chain and transition model of scene. On the basis, the emergency drill model of scene-driven was proposed. The model is dynamic and has high similarity with the real emergencies, which plays an important role to improve the effect of emergency drills.

Pre-evaluation of Contingency Plans for Meteorological Disasters Based on LINMAP Method

As the guidelines of dealing with meteorological disasters, whether contingency plans are perfect or not will affect the efficiency of the emergency response directly. In this paper, the process of pre-evaluation of contingency plans is expounded in detail: Firstly, this process is based on multi-attribute decision-making (MADM) method, which is to find a best solution from all feasible plans assessed on multiple attributes; secondly, the linear programming technique for multi-dimensional analysis of preference (LINMAP) method is used to develop decision analysis and generates the best alternative as the solution; thirdly, the typical evaluation indexes are selected and a numerical example is presented to demonstrate the validity and applicability of the proposed method. Finally, because the pre-evaluation results are difficult to verify, Copeland rule is used to colligate the ranking orders of different decision departments.