Exploring the link between urban form and work related transportation using combined satellite image and census information: Case of the Great lakes region

Aspects of urban transportation have significant implications for resource consumption and environmental quality. The level of travel activity, the viability of various modes of transportation and hence the level of transportation-related emissions are influenced by the structure of cities, i.e., their urban forms. While it is widely recognized that satellite remote sensing can provide spatial information on urban land cover and land use, its effective use for understanding impacts of urban form on issues such as transportation requires that this information be integrated with relevant demographic information. A comprehensive bi-national urban database, the Great Lakes Urban Survey (GLUS), comprising all cities with populations in excess of 200,000 has been created from Landsat imagery and national census and transportation survey information from Canada and the United States. A suite of analysis tools are proposed to utilize information sets such as GLUS to investigate the link between urban form and work-related travel. A new indicator, the Employment Deficit Measure (EDM), is proposed to quantify the balance between employment and worker availability at different transit horizons and hence to assess the viability of alternate modes of transportation. It is argued that the high degree of residential and commercial/industrial land uses greatly impact travel to work mode options as well as commute distance. A spatial interaction model is developed and found to accurately predict travel distance aggregated at the census tract level. We argue that this model could also be used to explore the relative levels of travel activity associated with different urban forms.     

Uncertainty Analysis of the Parameters of the Temperature-index Method: A Case Study of Shiyi Glacier in Qilian Mountains

In order to assess the performance of the common temperature-index melt model at both spatial and temporal scale in Qilian Mountains, we performed the sensitivity and uncertainty analysis on the parameters of a common temperature-index method and evaluated the glacier mass balance on a small alpine glacier, which is separated into two relatively independent branches, with the daily mass balance and the meteorological data in the summer of 2011 and 2012. Sensitivity analysis was conducted by perturbation analysis and uncertainty analysis was carried out by Generalized Likelihood Uncertainty Estimation (GLUE) for different conditions. The results showed that the temperature-index method could properly capture the diurnal variability of the glacier mass balance. But strong equifinality of model parameter existsed in model calibration due to the uncertainty in the parameters. The model was very sensitive to changes in the value of K_ice, followed by the K_snow and T_s. It was also found that the GLUE approaches could estimate and derive the posterior distributions of 3 parameters properly. Moreover, there existed an acceptable range, which ensured high precision under different conditions.     

科技量值的品质评定—校准、测样两阶段矢量合成法计算测量不确定度

实现单位统一、量值准确可靠的检测,是科技工作成功的前提,务必使用法定计量单位,在硬件、软件受控满足法制计量要求条件下,获取优质可溯源的量值 R_opt±u(R_opt )=(R ?-?R)±√(u_j^2 (R)+u_i^2 (R) ) 由此导出校准j、测量i两阶段、矢量合成简化计算测量不确定度的方法。特别有利于有多种标样的实验室,以标样做加密质控样,随机插入批样中,由管理者对n (≥11)批质控样结果统计的系统误差?R和标准测量不确定度u(R),同时完成签发检测报告,考核检验员素质和常态化提供测量不确定度三大使命,履行对客户的检测值品质的承诺。     

Drivers of future fluvial flood risk change for residential buildings in Europe

Flooding is the most costly natural hazard in Europe. Climatic and socioeconomic change are expected to further increase the amount of loss in the future. To counteract this development, policymaking, and adaptation planning need reliable large-scale risk assessments and an improved understanding of potential risk drivers.In this study, recent datasets for hazard and flood protection standards are combined with high resolution exposure projections and attributes of vulnerability derived from open data sources. The independent and combined influence of exposure change and climate scenarios rcp45 and rcp85 on fluvial flood risk are evaluated for three future periods centered around 2025, 2055 and 2085. Scenarios with improved and neglected private precaution are examined for their influence on flood risk using a probabilistic, multivariable flood loss model — BN-FLEMOps — to estimate fluvial flood losses for residential buildings in Europe.The results on NUTS-3 level reveal that urban centers and their surrounding regions are the hotspots of flood risk in Europe. Flood risk is projected to increase in the British Isles and Central Europe throughout the 21st century, while risk in many regions of Scandinavia and the Mediterranean will stagnate or decline. Under the combined effects of exposure change and climate scenarios rcp45, rcp85, fluvial flood risk in Europe is estimated to increase seven-fold and ten-fold respectively until the end of the century. Our results confirm the dominance of socioeconomic change over climate change on increasing risk. Improved private precautionary measures would reduce flood risk in Europe on an average by 15%. The quantification of future flood risk in Europe by integrating climate, socioeconomic and private precaution scenarios provides an overview of risk drivers, trends, and hotspots. This large-scale comprehensive assessment at a regional level resolution is valuable for multi-scale risk-based adaptation planning.     

Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields

A method of combining 3D Kriging for geotechnical sampling schemes with an existing random field generator is presented and validated. Conditional random fields of soil heterogeneity are then linked with finite elements, within a Monte Carlo framework, to investigate optimum sampling locations and the cost-effective design of a slope. The results clearly demonstrate the potential of 3D conditional simulation in directing exploration programmes and designing cost-saving structures; that is, by reducing uncertainty and improving the confidence in a project’s success. Moreover, for the problems analysed, an optimal sampling distance of half the horizontal scale of fluctuation was identified.     

Probabilistic risk and uncertainty analysis for bioremediation of four chlorinated ethenes in groundwater

Groundwater contamination risk assessment for health-threatening compounds should benefit from a stochastic environmental risk assessment which considers the effects of biological, chemical, human behavioral, and physiological processes that involve elements of biotic and abiotic aquifer uncertainty, and human population variability. This paper couples a complex model of chemical degradation and transformation with movement in an aquifer undergoing bioremediation to generate a health risk analysis for different population cohorts in the community. A two-stage Monte Carlo simulation has separate stages for population variability and aquifer uncertainty yielding a computationally efficient and conceptually attractive algorithm. A hypothetical example illustrates how risk variance analysis can be conducted to determine the distribution of risk, and the relative impact of uncertainty and variability in different sets of parameters upon the variation of risk values for adults, adolescents, and children. The groundwater example considers a community water supply contaminated with chlorinated ethenes. Biodegradation pathways are enhanced by addition of butyrate. The results showed that the contribution of uncertainty to the risk variance is comparable to that of variability. Among the uncertain parameters considered, transmissivity accounted for the major part of the output variance. Children were the most susceptible and vulnerable population cohort.     

A two-phase grey fuzzy optimization approach for water quality management of a river system

An extension of the Grey Fuzzy Waste Load Allocation Model (GFWLAM) developed in an earlier work is presented here to address the problem of multiple solutions. Formulation of GFWLAM is based on the approach for solving fuzzy multiple objective optimization problems with max–min as the operator, which usually may not result in a unique solution. The multiple solutions of fuzzy multiobjective optimization model should be obtained as parametric equations or equations that represent a subspace. A two-phase optimization technique, two-phase GFWLAM, is developed to capture all alternative or multiple solutions of GFWLAM. The optimization model in Phase 1 is exactly same as the optimization model described in GFWLAM. The optimization model in Phase 2 maximizes the upper bounds of fractional removal levels of pollutants and minimizes the lower bounds of fractional removal levels of pollutants keeping the value of goal fulfillment level same as obtained from Phase 1. The widths of the interval-valued fractional removal levels play an important role in decision-making as these can be adjusted within their intervals by the decision-maker considering technical and economic feasibility in the final decision scheme. Two-phase GFWLAM widens the widths of interval-valued removal levels of pollutants, thus enhancing the flexibility in decision-making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.     

基于元数据扩展的空间数据质量管理方法

空间数据质量问题是GIS系统建设成功与否的关键。首先对GIS中空间数据质量问题的引起原因和表现方式进行分析，并通过对元数据方法的分析和扩充，试图探寻一种能对数据质量进行有效管理的方法，以提高GIS空间数据库质量问题的可靠性和可控性。     

矿床地球化学模型的建立及其找矿效果探讨——以团结沟金矿为例

当今矿床学研究中的热点问题之一是矿床模型研究。矿床建模的理论与方法,矿床模型的定量化是目前矿床模型研究中亟待解决和完善的问题。从典型矿床研究入手,首先建立易于实现定量化的矿床地球化学模型,将有助于打破矿床模型研究的僵局。团结沟金矿床地球化学模型的建立是一个初步尝试。矿床地球化学模型能迅速转化为找矿模型,为找矿预测提供简捷有效的途径。