试论新世纪地理信息科学的发展

本文重点分析了当前国内外地理信息科学的形成与发展趋势和地理信息科学不断发展的历程 ,提出近期发展的前沿 ,以及当前地理信息产业化面临的一些重要问题。最后提出对地理信息科学发展的意见。     

城市化进程中土地资源配置的认识误区

按照经济学的观点，城市化就是人口在地理上的集中，一是城市人口的增多，在总人口中的比重上升，二是城市建设规模的扩大，是一个从农村经济转变为具有基本对立特征的城市经济变化过程。这种变化既是人口、市场、企业、基础设施在地理上的集中过程，也是工业化发展引起经济发展的一个必然现象。在这种现象的背后，即工业化各种因素的“集中”特点，最直接的效果就是对土地资源的再配置提出了紧迫的要求。作为认识问题，尤其是对于国家土地资源管理部门来说，消除城市化进程中土地资源配置的认识误区，显得尤为重要。     

BRINGING FORWARD OF THE CONCEPT OF COGIS AND ITS ARCHITECUTRE RESEARCH

Based on the analysis of the development of GIS technology and application,this paper brought forward the concept of GoGIS,namely Cooperative GIS ,CoGIS is GIS facing group-users and supporting human-human interaction,which makes it differ from the former GISs,Then,the characteristics of general Computer Spport Cooperative Work (CSCW)applications and the complexity of Geographic Information Science were analyzed,and the conclusion the CoGIS was not a simple GIS layer on CSCW was reached,Further,this paper gaver the hierarchical architecture of CoGIS,and analyzed the coperative platform in detail from the following:1)basic elements;2) collaboration patterns;3) cooperation control mechanism;4) synchronization mechanism;5) security and 6) group communication and so on.With those,the problems about GIS applications are discussed,such as 1)distributed multi-source GIS information and knowledge sharing platform;2)the fusion and visualization of GIS information;3)virtual reality cooperative modeling;4) dymamic simulation;5)expert system and 6) decision-making.Finally,this paper analyzed CoGIS application mode in brief.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

有限元法与伪谱法混合求解弹性波动方程

在地震波场数值模拟中,有限差分法、有限元法和伪谱法都是常用的基本方法,但它们各有不同的适应性和优缺点,如有限差分法、有限元法都存在减弱网格频散和提高计算效率的矛盾,而伪谱法的网格频散小且计算效率高.有限差分法和伪谱法在处理地表结构复杂或地表剧烈起伏以及地下结构复杂的情况时存在较大的难度,而有限元法可较为理想地拟合起伏地表和任意弯曲界面,且可方便地处理自由边界条件和界面边界条件.尝试将有限元法和伪谱法相结合,形成地震波场数值模拟的一种混合方法,利用二者的优点,克服二者的缺点,达到既减弱网格频散又提高计算精度和效率的目的.并采用所谓的‘过度区域‘技术解决两种不同算法的衔接问题.模拟实例表明,给出的混合模拟方法不失为弹性波场数值模拟的一种有效方法.     

HD 82943行星系统的2:1共振与稳定性

用直接数值积分方法通过模拟不同的行星构型探讨了HD82943行星系统(由两颗共振的巨行星组成)的长期动力演化,同时,还研究了在相空间的轨道运动.在对系统长达107年数值积分中,发现所有的稳定轨道均与2:1共振相关联.典型地,在相同的时标内,两个共振幅角θ1和θ2同时(或其中之一)存在秤动.由于共振幅角在一定范围内的秤动,因而使两颗行星轨道半长径被约束而表现为规则运动模式.另外,利用分析模型(包含了外行星偏心率e2的因素),还讨论了对于不同取值的e2和相对近星点经度θ时,内行星在相空间的运动,并发现2:1轨道共振对于相对较小的e2以及当θ=0°时易于保持.此外,适中的e2将导致系统的两颗行星进入深度共振状态.再者,分析模型和数值计算的结果吻合得很好,两者都揭示了行星系统的2:1共振结构.