Mapping ambivalence: Exploring the geographies of community change and rails-to-trails development using photo-based Q method and PPGIS

As the literature on trail development suggests, recreational trail projects can generate conflicts and controversies, particularly when built on abandoned rail corridors through developed areas. These conflicts are often understood as “not in my back yard” (NIMBY) reactions, suggesting a spatial proximity to conflict which increases as one draws closer to the proposed trail. This research seeks to understand local residents’ perceptions and reactions to recreational trail development in the City of Delaware (Ohio, USA). It addresses two spatially infused questions: Does the potential for conflict related to trail development increase as people live closer to a potential trail (the NIMBY factor)? Can important qualitative factors about favorable and unfavorable land uses including potential recreational trail sites be defined using a participatory methodology and then represented in GIS? The study used a mixed-method approach to collect and analyze qualitative data from a group of local residents. Each participant was interviewed and asked to sort 19 pictures related to trail development. After each of the sorts, participants were asked to explain why they ranked the pictures the way they did. Results of the picture sorts were then analyzed using Q method and mapped with GIS. The results show that spatial proximity matters in the context of trail development and potential NIMBY reactions to trails. Significant differences were found in the picture sorts that reveal the importance of proximity and location, although in a manner contrary to the assumptions in the writings on rails-to-trails. Through combining qualitative methods, Q analysis and PPGIS analysis, the research shows that qualitative place-based studies are capable of generating insights about the complexities of situated geographic change such as recreational trail development.     

Contribution of the SISCam Web-based GIS to the seismotectonic study of Campania (Southern Apennines): an example of application to the Sannio-area

In this article the implementation and potential of the Seismotectonic Information System of the Campania Region (SISCam) are described, in particular an application of this Web-based GIS system to the seismotectonic analysis of the Sannio area (Southern Apennines) is performed. WEB-GIS technologies greatly contribute to both the environmental monitoring and the disaster management of areas affected by high natural risks. Specifically the SISCam system has been developed with the aim of providing easy access and fast diffusion, through Internet technology, of the most significant geological, geophysical, and territorial data relative to the Campania Region. The Sannio area has been selected as our application example because it is among the most active seismic regions in Italy. This portion of the Southern Apennines which was hit by the June 5, 1688 strong earthquake (M _W = 6.7, CPTI 1999) and by some low- and moderate-energy seismic sequences (1990–1992, 1997), is characterized by a complex inherited tectonic setting and low-tectonic deformation rates that hide the seismogenic sources position. Since this case study turned out to be complicated, the use of the SIScam WEB-GIS has become indispensable because it allowed us to visualize, integrate and analyze all the data available, in order to obtain an accurate and direct picture of the seismotectonic setting of the area. Moreover, a different approach of data analysis was necessary, due to the lack of up-to-date neotectonic and structural data; therefore, the operation of this GIS system enabled us to process and generate some original informative layers, through image analysis, such as new structural lineaments represented on a map of the potential active faults of the area, which has been the final result of our application, as a contribution to new knowledge about the local seismic risk parameters.     

Identifying China’s leading world city: a network approach

This paper reports our research on China’s world cities. Formal network analysis of air passenger linkages for recent years among China’s most populous cities and among many of the world’s largest cities allows us to identify the country’s leading world city from among the leading Mainland candidates, Beijing, Shanghai and Guangzhou. We theorize our findings about China’s world cities in relation to both global forces (and China’s increasing entanglement with them) and the policies and actions of the national state. We examine the national and global urban network through a longitudinal, two-level analysis of airline passenger travel for four time points between about 1990 and 2005. We show that Beijing was China’s leading world city at the beginning of the time period, a status it lost nationally in as early as 1995, and then globally 10 years later. On the other hand Shanghai became China’s leading world city, and it acquired this status first nationally in 2000, and then globally in 2005. The changing status of the Chinese capital corresponds to the country’s increasing involvement with the capitalist world economy. Shanghai’s ascendance as the leading world city in China may indicate that global forces have come to play an increasingly important role relative to that of the developmental state.

Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

Soil erosion susceptibility assessment and validation using a geostatistical multivariate approach: a test in Southern Sicily

A certain number of studies have been carried out in recent years that aim at developing and applying a model capable of assessing water erosion of soil. Some of these have tried to quantitatively evaluate the volumes of soil loss, while others have focused their efforts on the recognition of the areas most prone to water erosion processes. This article presents the results of a research whose objective was that of evaluating water erosion susceptibility in a Sicilian watershed: the Naro river basin. A geomorphological study was carried out to recognize the water erosion landforms and define a set of parameters expressing both the intensity of hydraulic forces and the resistance of rocks/soils. The landforms were mapped and classified according to the dominant process in landsurfaces affected by diffuse or linear water erosion. A GIS layer was obtained by combining six determining factors (bedrock lithology, land use, soil texture, plan curvature, stream power index and slope-length factor) in unique conditions units. A geostatistical multivariate approach was applied by analysing the relationships between the spatial distributions of the erosion landforms and the unique condition units. Particularly, the density of eroded area for each combination of determining factors has been calculated: such function corresponds, in fact, to the conditional probability of erosion landforms to develop, under the same geoenvironmental conditions. In light of the obtained results, a general geomorphologic model for water erosion in the Naro river basin can be depicted: cultivated areas in clayey slopes, having fine-medium soil texture, are the most prone to be eroded; linear or diffuse water erosion processes dominate where the topography is favourable to a convergent or divergent runoff, respectively. For each of the two erosion process types, a susceptibility map was produced and submitted to a validation procedure based on a spatial random partition strategy. Both the success of the validation procedure of the susceptibility models and the geomorphological coherence of the relationships between factors and process that such models suggest, confirm the reliability of the method and the goodness of the predictions.     

陕西白河县月儿潭绿松石与次生磷钙铝矾研究

对陕西省白河县月儿潭风化严重的绿松石样品进行了岩石薄片观察、化学成分测试、X射线粉晶衍射和红外吸收光谱分析等研究.结果表明,绿松石风化分解由天蓝色退色成黄绿色,最后变成白色,结构也由致密细腻变得松散多孔,主要原因是发生了硫酸根对磷酸根的交代作用,最终的交代产物主要是磷钙铝矾.     

Re-Os同位素对峨眉山大火成岩省成因制约的探讨

峨眉山大火成岩省（ELIP）主要由玄武岩、玄武质火山碎屑岩及少量的苦橄岩（包括越南的科马提岩）、长英质岩石以及层状岩体和岩墙组成,其物质来源直接关系到其成因是否与地幔柱活动有关。Re-Os同位素体系是地核、地幔和地壳物质的最佳示踪剂。前人对ELIP内的Re-Os同位素研究表明,低Ti玄武岩的Os含量为0．006×10^-9-0．40010^-9,^187Os／^188Os初始值为0．1371～1．403,并提出其与地幔柱活动有关;而高Ti玄武岩的Os含量为0．00410^-9～0．56010^-9,^187Os／^188Os初始值为0．1271～5．19,认为起源于大陆岩石圈地幔或地幔柱上升过程中受到大量岩石圈地幔“混染”（xu JF et al．,2007）;科马提岩的0s含量为1．2410^-9～7．0010^-9,^187Os／^188Os初始值为0．1251～0．1261,苦橄岩的Os含量为0．3210^-9～2．32910^-9,^187Os／^188Os初始值为0．1233～0．1266,指示苦橄岩和科马提岩均来自亏损地幔源区（Hanski et al．,2004;陈雷等,2007）。本文利用Os含量最低、^187Os／^188Os最高的高Ti玄武岩作为地壳端员,用铁质陨石、原始上地幔（PUM）和亏损地幔（DMM）作为地核和各种地幔端员,分别做二元混合计算,结果显示绝大多数玄武岩和所有苦橄岩及科马提岩均落在地壳和DMM混合曲线附近,并且邻区特提斯洋地幔岩与DMM具有相近的Os含量和^187Os／^188Os组成,据此推测峨眉山火成岩的形成与特提斯洋的活动有关,主要受控于地壳和亏损地幔的相互作用。     

基于Web＆GIS的洪水预报技术概述

洪水预报技术涉及专业技术和实现技术两个方面,洪水预报实现技术的发展制约着洪水预报的整体水平.基于GIS及Web的洪水预报应用技术,代表了洪水预报技术发展的一个新的方向,主要体现在三个方面:构件化应用开发的洪水预报系统;建立分布式洪水预报模型;交互式洪水预报调度决策应用模式.技术关键在于洪水预报中间件和相应应用中间件标准,其次是规范构件化应用;三是推进应用级服务体系,支持行业应用的构件化软件开发.