语言差异、城市信度与省际贸易间关系的实证研究

本文利用铁路货运量作为省际贸易的代理变量,考察语言差异对中国省际贸易的影响作用,并引入城市信度这一变量,考察其对语言差异与省际贸易之间关系的调节作用。实证研究结果表明,语言差异对省际贸易有着显著的负向作用,即语言差异越大,地区间贸易量越小。本文进一步按南北划分地区,结果发现相较于语言较为统一的北方地区,南方地区之间、南方与北方地区之间的语言差异较大,因而贸易量也相应减少。城市信度则能够减弱两者之间的负相关关系,也就是说,城市信度能够削弱语言差异对省际间贸易往来的阻碍作用。

Spatial Agglomeration of Exhibition Enterprises on a Regional Scale in China

During the past two decades, the exhibition industry in China has been developing rapidly and has become an important part of the modern service industry, particularly the agglomeration characteristics of exhibition enterprises highlighted on the regional scale. Although the development of theoretical research on the western exhibition industry has taken place over time, the spatial perspective has not been at the centre of attention so far. This paper aims to fill this gap and report on the agglomeration characteristics of exhibition enterprises and their influential factors. Based on data about exhibition enterprises in the Pearl River Delta(PRD) during 1991–2013, using the Ripley K function analysis and kernel density estimation, this research identifies that: 1) the exhibition enterprise on the regional scale is significantly characterized by spatial agglomeration, and the agglomeration density and scale are continuously increasing; 2) the spatial pattern of agglomeration has developed from a single-center to multi-center form. Meanwhile, this paper profiles the factors influencing the spatial agglomeration of exhibition enterprises by selecting the panel data of nine cities in the PRD in 1999, 2002, 2006 and 2013. The results show that market capacity, urban informatization level and exhibition venues significantly influence the location choice of exhibition enterprises. Among them, the market capacity is a variable that exerts a far greater impact than other factors do.

A GIS-based Spatial Analysis of Housing Price and Road Density in Proximity to Urban Lakes in Wuhan City, China

As one of the essential urban open spaces, lakes usually contribute immensely to the quality of residents′ daily lives. Different from hedonic approach employed in existing researches on urban open spaces in China, this paper integrates housing price surface with road density to analyze the spatial characteristics in proximity to urban lakes in Wuhan City, China. With the expansion of Wuhan City, urban lakes became polluted, they shrunk or even disappeared, leading to unfavorable conditions for sustainable development of the city. To better understand the spatial relationship between the city and lakes, we classify the urban lakes in Wuhan central area into ′lakes in the urban center′ and ′lakes in urban fringe′. Based on housing price surface we explore the spatial characteristics in proximity to different lakes and differences between the lakes. We also use Geographic Information System(GIS) tool to calculate road density as a supplementary indicator to reflect the accessibility in proximity to urban lakes. The results indicate that relative independence exists between different towns, and the spatial characteristics are different depending on scales and locations. In most of cases, the road density is lower where closer to the lakeshore while the housing price exhibits an opposite pattern. We conclude that city governments and urban planners should give more considerations to these spatial differences, somewhere should be better planned and protected as an important waterfront and somewhere the control of unreasonable real estate development nearby should be strengthened.

A BP neural network based information fusion method for urban traffic speed estimation

Obtaining comprehensive and accurate information is very important in intelligent tragic system （ITS）. In ITS, the GPS floating car system is an important approach for traffic data acquisition. However, in this system, the GPS blind areas caused by tall buildings or tunnels could affect the acquisition of tragic information and depress the system performance. Aiming at this problem, a novel method employing a back propagation （BP） neural network is developed to estimate the traffic speed in the GPS blind areas. When the speed of one road section is lost, the speed of its related road sections can be used to estimate its speed. The complete historical data of these road sections are used to train the neural network, using Levenberg-Marquardt learning algorithm. Then, the current speed of the related roads is used by the trained neural network to get the speed of the road section without GPS signal. We compare the speed of the road section estimated by our method with the real speed of this road section, and the experimental results show that the proposed method of traffic speed estimation is very effective.

Groundwater Quality Assessment for an Indian Urban Habitat： A GIS Approach

Groundwater is an essential source of drinking water for many Indian urban habitats. Large numbers of people consume ground water instead of municipal tap water due to contamination of tap water. Groundwater is extracted from thousands of bore wells, and used for potable purpose without proper testing and treatment. This paper describes a groundwater quality monitoring strategy and database model developed for Gulbarga city, located in Karnataka, India. Sampling wells are selected one each in 55 wards of the city corporation having easy access for regular sampling. Various attributes of sampling wells including their spatial coordinates, location address and a photograph are registered for ready recognition on site. Water samples are collected and analyzed for various physico-chemical parameters. Spatial coordinates and levels of sampling points are measured on site using a hand held GPS instrument. Gulbarga city map is digitized. A GIS database of the measured spatial and water quality data is developed using ArcGIS Desktop 9.3, and ground water quality maps are prepared which may serve as useful tools for developing policy, and regulatory mechanism for sustainable groundwater use.