Simulating urban expansion by coupling a stochastic cellular automata model and socioeconomic indicators

Urbanization is one of the most important anthropogenic activities that create extensive environmental implications at both local and global scales. Dynamic urban expansion models are useful tools to understand the urbanization process, project its spatiotemporal dynamics and provide useful information for assessing the environmental implications of urbanization. A hybrid urban expansion model (NNSCA model) was proposed to simulate rapid urban growth in a typical industrial city, Dongying, China, by coupling a artificial-neural-network-based stochastic cellular automata model and several socioeconomic indictors, i.e., the per capita income of the rural population, the per capita income of the urban population, population and gross domestic products of the city. Good conformity between simulated and actual urban patterns suggested that the NNSCA model was able to effectively simulate historic urban growth and to generate realistic urban patterns. A series of scenario analyses suggested that the expanding urban would threaten the ecosystem health of coastal wetlands in the city unless environmental protection actions are taken in the future. The NNSCA model provides abilities to assess future urban growth under various planning and management scenarios, and can be integrated into ecological or environmental process models to evaluate urbanization’s environmental implications.     

副高强度短时期演变的诊断分析

一、前言 西太平洋副热带高压(以下简称副高)是影响我国夏季天气的主要天气系统之一。六十年代以来,我国气象工作者探索了它的活动规律,取得了许多研究成果。本文是对于具有一定特点的两次副高个例作的诊断分析。这两次不同日期的副高,它们在500毫巴图上看起来很相类似,似乎都强盛,但是它们的短时期演变却显然不同。其中1971年5