Multiscale advanced raster map analysis system: Definition, design and development

This paper brings together a multidisciplinary initiative to develop advanced statistical and computational techniques for analyzing, assessing, and extracting information from raster maps. This information will provide a rigorous foundation to address a wide range of applications including disease mapping, emerging infectious diseases, landscape ecological assessment, land cover trends and change detection, watershed assessment, and map accuracy assessment. It will develop an advanced map analysis system that integrates these techniques with an advanced visualization toolbox, and use the system to conduct large case studies using rich sets of raster data, primarily from remotely sensed imagery. As a result, it will be possible to study and evaluate raster maps of societal, ecological, and environmental variables to facilitate quantitative characterization and comparative analysis of geospatial trends, patterns, and phenomena. In addition to environmental and ecological studies, these techniques and tools can be used for policy decisions at national, state, and local levels, crisis management, and protection of infrastructure. Geospatial data form the foundation of an information-based society. Remote sensing has been a vastly under-utilized resource involving a multi-million dollar investment at the national levels. Even when utilized, the credibility has been at stake, largely because of lack of tools that can assess, visualize, and communicate accuracy and reliability in timely manner and at desired confidence levels. Consider an imminent 21st century scenario: What message does a multi-categorical map have about the large landscape it represents? And at what scale, and at what level of detail? Does the spatial pattern of the map reveal any societal, ecological, environmental condition of the landscape? And therefore can it be an indicator of change? How do you automate the assessment of the spatial structure and behavior of change to discover critical areas, hot spots, and their corridors? Is the map accurate? How accurate is it? How do you assess the accuracy of the map? How do we evaluate a temporal change map for change detection? What are the implications of the kind and amount of change and accuracy on what matters, whether climate change, carbon emission, water resources, urban sprawl, biodiversity, indicator species, human health, or early warning? And with what confidence? The proposed research initiative is expected to find answers to these questions and a few more that involve multi-categorical raster maps based on remote sensing and other geospatial data. It includes the development of techniques for map modeling and analysis using Markov Random Fields, geospatial statistics, accuracy assessment and change detection, upper echelons of surfaces, advanced computational techniques for geospatial data mining, and advanced visualization techniques.     

Statistical evaluation of the attainment of interim cleanup standards at hazardous waste sites

Cleanup standards at hazardous waste sites include (i) numeric standards (often risk-based), (ii) background standards in which the remediated site is compared with data from a supposedly clean region, and (iii) interim standards in which the remediated site is compared with preremediation data from the same site. The latter are especially appropriate for verifying progress when an innovative, but unproven, technology is used for remediation. Standards of type (i) require one-sample statistical tests, while those of type (ii) and type (iii) call for two-sample tests. This paper considers two-sample tests with an emphasis upon the type (iii) scenario. Both parametric (likelihood ratio) and nonparametric (linear rank) protocols are examined. The methods are illustrated with preremediation data from a site on the National Priorities List. The results indicate that nonparametric procedures can be quite competitive (in terms of power) with distributional modelling provided a near optimal rank test is selected. Suggestions are given for identifying such rank tests. The results also confirm the importance of sound baseline sampling; no amount of post-remediation sampling can overcome baseline deficiencies.This paper has been prepared with partial support from the United States Environmental Protection Agency under a Cooperative Agreement Number CR-815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.     

PREDICTABILITY OF SURFACE WATER POLLUTION LOADING IN PENNSYLVANIA USING WATERSHED‐BASED LANDSCAPE MEASUREMENTS1

ABSTRACT: We formally evaluated the relationship between landscape characteristics and surface water quality in the state of Pennsylvania (USA) by regressing two different types of pollutant responses on landscape variables that were measured for whole watersheds. One response was the monthly exported mass of nitrogen estimated from field measurements, while the other response was a GIS‐modeled pollution potential index. Regression models were built by the stepwise selection protocol, choosing an optimal set of landscape predictors. After factoring out the effect of physiography, the dominant predictors were the proportion of “annual herbaceous” land and “total herbaceous” land for the nitrogen loading and pollution potential index, respectively. The strength of these single predictors is encouraging because the marginal land cover proportions are the simplest landscape measurements to obtain once a land cover map is in hand; however, the optimal set of predictors also included several measurements of spatial pattern. Thus, for watersheds at this general hierarchical scale, gross landscape pattern may be an important influence on instream pollution loading. Overall, there is strong evidence that using landscape measurements alone, obtained solely from remotely sensed data, can explain most of the water quality variability (R²= approx. 0.75) within these watersheds.     

R/S法的土石坝施工期沉降规律及预警标准研究

为提高施工期土石坝沉降安全性,研究其具有复杂非线性特征的施工期沉降规律和相应的预警标准。基于国内某在建高土石坝的沉降数据,采用R/S法分析坝体不同高程测点、同高程测点和同测点不同时期沉降数据的Hurst指数及分形维数,提出评价坝体施工期沉降安全性的预警标准。结果表明:各测点的Hurst指数最小值为0.763,坝内各处沉降仍处于快速增长阶段;坝体下部比上部、中部比下游堆石区沉降能更快趋于稳定,且坝体下部的沉降速率已经渐趋平缓。     

民营企业安全文化模型及其实证分析

针对民营企业特点,基于交互安全文化模型,建立民营企业安全文化模型并辨识 关键元素,以赛轮金宇股份有限公司为例进行实证分析。在广泛参考国内外相关研究的 基础上,设计调查问卷,运用粗糙集ROSETTA软件对测量结果进行属性简约,最终确定 15个安全文化元素;借助MATLAB,采用熵权法确定各元素权重,然后进行可拓综合评价 。评价结果表明该企业的“高层管理者重视”一项得分为4.82,水平较高,整体文化等 级属于“良”,级别特征变量j*=3.138 1。“创造安全舒适的工作环境”、“建立合理 的奖惩制度”、“定期进行应急演练”3个方面得分偏低,是安全文化建设需要重点加 强的方面。     

Photocatalytic degradation of methyl orange using ZnO nanorods

Nanosized ZnO rods were synthesized using a microwave-assisted aqueous method. High molecular weight polyvinyl alcohol was used as a stabilizing agent. Size, surface morphology, and structure were investigated using transmission electron microscopy (TEM), scanning electron microscopy (SEM), and X-ray diffraction (XRD). SEM and TEM images show that ZnO nanorods have diameters of about 50?nm and lengths of a few micrometers. The XRD pattern reveals that ZnO nanorods are of hexagonal wurtzite structure. The average crystallite size calculated from Scherrer's relation was found to be 40?nm. The effects of catalyst loading, pH value, and initial concentration of methyl orange on the photocatalytic degradation efficiency using ZnO nanorods as photocatalyst were discussed. The results revealed that ZnO nanorods with a diameter of 50?nm showed the highest photocatalytic activity at a surface density of 0.2?g?dm^?3.     

Effectiveness of ionic liquid-supported membranes for carbon dioxide capture: a review

Environmental Science and Pollution Research - The world’s population explosion creates a need for natural resources for energy, which will become a significant contributor to global climate...     

Biomarker-assisted assessment of aquatic health using the cosmopolitan common carp,Cyprinus carpio (L): a case study of bisphenol-A exposures

Environmental Science and Pollution Research - Monitoring aquatic health from environmental pollutants is critical, none more so than bisphenol-A (BPA), a ubiquitous endocrine-disrupting chemical...