MATLAB辅助GIS空间分析建模实验设计与应用

根据地理信息系统GIS的特点和空间分析实验的特点,提出利用MATLAB软件进行GIS空间分析实验设计,并结合一个实例,给出了MATLAB空间分析建模实验应用的主要内容和方法。此实验设计应用有助于学生较快地理解GIS空间分析实验原理,学会利用MATLAB软件分析解决GIS地学实际问题。     

Design and implementation of a GIS system for planning

Geographic information system (GIS) provides a flexible and efficient general platform for planning and analysis, especially when large amounts of ever changing spatial information is dealt with. It helps managing the change in an economical and sustainable way. We decided to build a GIS to help in data management and in the dynamic planning process of our developing university, Al-Balqa' Applied University (BAU). In this paper, we present the GIS system, which we built for the campus of BAU and the customization of the needed software to help in decision-making and planning processes. Moreover, the output of our project is web enabled so that it can be used in the web site of Al-Balqa' Applied University as a web GIS application.     

利用地统计分析及GIS技术实现流域面雨量预报

根据地统计学及地理信息系统(GIS)的空间建模原理,采用工业标准的、开放的、统一的ArcObjects嵌入式组件开发方法,利用多模数值预报,研制并构建精细化的流域面雨量集合预报模型及雨涝区划单元定量降水应用组件,将其动态、无缝地嵌入到GIS应用系统中,自动生成子流域及雨涝区划面雨量预报指导产品.     

物流配送问题的知识表示及其在GIS中的映射研究

针对电子商务物流配送实时监控与调度问题,以提高物流配送实时优化调度的智能性和科学性为突破口,引入人工智能和知识工程的知识表示理论．提出一种基于知识的物流配送问题的树状表示法,给出了基于GIS的物流配送问题知识表示的系统模型以及物流配送知识在GIS中的映射方案．该方案通过XML关系映射文档,保持了知识库和空间数据库的一致性．仿真研究表明．所进行的工作有利于深化基于GIS的物流配送实时决策和智能调度系统的研究．     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.