长江中游沿岸过江大桥工程建设适宜性评价与地学建议

基于长江中游沿岸地质环境条件及过江大桥场地建设基本要求,优选地形地貌、工程地质条件及区域稳定性3个评价因素,运用层次分析法开展长江中游沿岸过江大桥工程场地建设适宜性评价,将长江中游沿岸过江大桥工程分为适宜开发岸线、较适宜开发岸线、一般适宜开发岸线及非优先开发岸线4个等级。长江中游沿岸地区以较适宜开发岸线和一般适宜开发岸线为主,长度分别为625.19 km和598.99 km,分别占岸线总长度的31.35%和30.04%。针对长江中游不同等级岸线的地质特征,提出了相应的地学建议,为长江中游沿岸过江大桥优化选址提供地学指导,进一步促进长江经济带国土资源空间规划与岸线资源保护利用工作的开展。     

Mapping and assessing crop diversity in the irrigated Fergana Valley,Uzbekistan

Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.     

Generating urban road intersection models from low-frequency GPS trajectory data

Detailed real-time road data are an important prerequisite for navigation and intelligent transportation systems. As accident-prone areas, road intersections play a critical role in route guidance and traffic management. Ubiquitous trajectory data have led to a recent surge in road map reconstruction. However, it is still challenging to automatically generate detailed structural models for road intersections, especially from low-frequency trajectory data. We propose a novel three-step approach to extract the structural and semantic information of road intersections from low-frequency trajectories. The spatial coverage of road intersections is first detected based on hotspot analysis and triangulation-based point clustering. Next, an improved hierarchical trajectory clustering algorithm is designed to adaptively extract the turning modes and traffic rules of road intersections. Finally, structural models are generated via K-segment fitting and common subsequence merging. Experimental results demonstrate that the proposed method can efficiently handle low-frequency, unstable trajectory data and accurately extract the structural and semantic features of road intersections. Therefore, the proposed method provides a promising solution for enriching and updating routable road data.     

基于灰色关联度的AHP权重矩阵构建方法改进及在农地评价中的应用

合理确定评价指标的权重是准确测度农业土地资源可持续利用能力的关键所在。本文依据灰色关联度对层次分析法(AHP)中判断矩阵的构建方法进行了改进,并获取各项评价指标的权重。在此基础上,分别采用多目标线性加权函数综合评价模型和障碍因子诊断模型,对2001-2012年湖北省枣阳市的农业土地资源可持续利用水平及其制约因素进行评估和辨析。结果显示：基于灰色关联分析法(GRA)改进后的AHP方法在确定指标权重时不仅能有效降低主观赋权的影响,也可避免熵值法等客观赋权法所存在的弊端;地均农业生产总值、人均耕地面积、化肥使用强度、有效灌溉面积、年降水量、人均GDP和农村居民家庭人均纯收入是制约枣阳市农业土地资源可持续利用的最主要因素,但在不同年份各因素的阻碍度表现不一。2001年以来,枣阳市农业土地资源利用的社会经济可持续性水平较高,综合可持续利用水平指数整体上呈增加的态势;但在生态可持续方面,2006年之后不仅明显低于之前年份,而且也显著低于同时期的社会经济可持续性。     

非物质文化遗产资源旅游开发价值评价体系与应用——以苏州市为例

旅游开发提高非物质文化遗产的自我生存能力,使其摆脱濒危的困境,是非物质文化遗产保护与利用的重要方式。本文对非物质文化遗产资源旅游开发研究进行梳理,在此基础上,构建了非物质文化遗产资源旅游开发价值评价指标体系,即由资源禀赋条件、可展示与体验性、遗产地旅游发展条件3个方面的要素组成,并以非物质文化遗产资源富集的苏州为例,对省级以上非物质文化遗产进行了评价,共评出三级旅游资源3项、二级旅游资源16项、一级旅游资源29项。主要结论为：产品衍生性、展示适宜性、是否具备可观赏性、遗产保护情况决定了非物质文化遗产资源是否能够成为旅游资源;可展示与体验性决定了非物质文化遗产旅游资源的旅游开发价值水平高低。手工艺类、民俗类非物质文化遗产具有较高的旅游开发价值,民间文学、传统体育游艺与杂技和传统医药的旅游可开发性较差。本文构建的非物质文化遗产旅游开发价值评价体系可为旅游地进行非物质文化遗产资源筛选和旅游开发提供科学依据。     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

Socio-economic vulnerability due to climate change: Deriving indicators for fishing communities in Mumbai

This paper assessed the socio-economic implications of climate change and vulnerability of fishing communities known as “Koli” living in Mumbai, India. The vulnerability indicators are derived from sustainable livelihood literature and use of multi-criteria analyses and are validated with expert opinions. A survey of two hundred fishermen from five fishing villages in Mumbai was conducted to collect data. The results demonstrate that vulnerability perpetuates due to physical and financial resource constraints among the fishing community. Fishermen from Madh and Worli villages are observed to be more vulnerable and less adaptive due to their inability to use efficient mechanized boats and advanced fishing implements, such as fish finders and GPS (Global Positioning System). The divergence in the vulnerability scores among fishing villages is attributed to the coping strategies, resource availability, knowledge and the benefit derived from the local government. Fishermen have been observing the negative impacts of climate change on their fishing livelihoods. Adaptation strategies to maximize fish catch are observed in such practices as targeting different species and fishing intensively for several days. However, these practices are leading to an imbalance in the common resource pool and biased resource sharing among different groups of fishermen.     

知识不确定条件下的海外保障基地自然风险情景模拟评估

针对海外保障基地面临的自然风险,在风险辨识基础上,构建了风险评价指标体系和海外保障基地自然风险的贝叶斯网络评估模型,并进行了情景模拟下的量化实验评估。针对目前贝叶斯网络评估过程中的群决策和决策偏好问题,引入了犹豫层次分析思想来优化计算指标风险隶属度,改进了评估过程中的客观性和适用性。     

基于粗糙集与犹豫层次分析的北极东北航道风险评估

运用风险分析理论和方法,以北极东北航道6个关键海峡为研究目标,构建东北航道自然环境风险评价指标体系;针对全球气候变暖以及海冰融化背景下北极东北航道航行安全问题,引入犹豫层次分析方法确定指标主观权重、采用粗糙集思想来确定客观权重,集成得到组合权重。基于所建风险分析模型,对其中3个关键海峡的自然环境风险进行了量化评估和时空特征分析,同时计算了2013年8月份6个关键海峡的风险度,模拟了一条最优通航线路并与同时期永盛号轮船的实际航行线路进行了比对。研究表明:(1)2000-2014年东北航道3个关键海峡自然环境风险均呈现减小趋势,红军海峡自然环境风险减小趋势最大;(2)对比3个海峡海峡自然环境风险度,德朗海峡最低,维利基茨基海峡次之,二者均适合通航;红军海峡风险度最高,且不适宜通航;(3)模型模拟路线与实际航线较吻合,对实时航行路线的选择有参考意义。     

Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi‐type sensory systems

In this paper, a Bayesian sequential sensor placement algorithm, based on the robust information entropy, is proposed for multi‐type of sensors. The presented methodology has two salient features. It is a holistic approach such that the overall performance of various types of sensors at different locations is assessed. Therefore, it provides a rational and effective strategy to design the sensor configuration, which optimizes the use of various available resources. This sequential algorithm is very efficient due to its Bayesian nature, in which prior distribution can be incorporated. Therefore, it avoids the possible unidentifiability problem encountered in a sequential process, which starts with small number of sensors. The proposed algorithm is demonstrated using a shear building and a lattice tower with consideration of up to four types of sensors. Copyright © 2014 John Wiley & Sons, Ltd.