Web-based spatiotemporal visualization of marine environment data

With long-term marine surveys and research,and especially with the development of new marine environment monitoring technologies,prodigious amounts of complex marine environmental data are generated,and continuously increase rapidly.Features of these data include massive volume,widespread distribution,multiple-sources,heterogeneous,multi-dimensional and dynamic in structure and time.The present study recommends an integrative visualization solution for these data,to enhance the visual display of data and data archives,and to develop a joint use of these data distributed among different organizations or communities.This study also analyses the web services technologies and defines the concept of the marine information gird,then focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method.We discuss how marine environmental data can be organized based on the spatiotemporal visualization method,and how organized data are represented for use with web services and stored in a reusable fashion.In addition,we provide an original visualization architecture that is integrative and based on the explored technologies.In the end,we propose a prototype system of marine environmental data of the South China Sea for visualizations of Argo floats,sea surface temperature fields,sea current fields,salinity,in-situ investigation data,and ocean stations.An integration visualization architecture is illustrated on the prototype system,which highlights the process-oriented temporal visualization method and demonstrates the benefit of the architecture and the methods described in this study.

Environmental Data Acquisition, Elaboration and Integration： Preliminary Application to a Vulnerable Mountain Landscape and Village （Novalesa, NW Italy）

Climate conditions play a crucial role in the survival of mountain communities, whose survival already critically depends on socioeconomic factors. In the case of montane areas that are prone to natural haz-ards, such as alpine slope failure and debris flows, climatic factors exert a major influence that should be considered when creating appropriate sustainable scenarios. In fact, it has been shown that climate change alters the availability of ecosystem services （ES）, thus increasing the risks of declining soil fertility and reduced water availability, as well as the loss of grassland, potential shifts in regulatory services （e.g., protection from natural hazards）, and cultural services. This study offers a preliminary discussion on a case study of a region in the Italian Alps that is experiencing increased extreme precipitation and erosion, and where an isolated and historically resilient community directly depends on a natural resource econ- omy. Preliminary results show that economic factors have influenced past population trends of the Novalesa community in the Piemonte Region in northwest Italy. However, the increasing number of rock fall and debris flow events, which are triggered by meteo-climatic factors, may further influence the livelihood and weflbeing of this community, and of other similar communities around the world, Therefore, environmental monitoring and data analysis will be important means of detecting trends in landscape and climate change and choosing appropriate planning options. Such analysis, in turn, would ensure the survival of about 10% of the global population, and would also represent a possibility for future economic development in critical areas prone to poverty conditions.

Influence of environmental data of different sources on marine species habitat modeling:A case study for Ommastrephes bartramii in the Northwest Pacific Ocean

The quality of environmental data and its possible impact on the marine species habitat modelling are often overlooked while the sources for these data are increasing.This study selected sea surface temperature(SST)from two commonly used sources,the NOAA Ocean Watch and IRI/LDEO Climate Data Library,and then constructed habitat suitability index model to evaluate the influences of SST from the two sources on the outcomes of Ommastrephes bartramii habitat models for the months of July–October in the Northwest Pacific Ocean during 1996–2012.This study examined the differences in the amount of estimated unfavourable/favourable habitat area when the SST used for model building and inference were the same or different.Dynamics in suitable habitat area calculated from SST was insensitive to the two different SST products.In the fishing season of O.bartramii,the changes of magnitude and trend of monthly suitable habitat area in August and September were similar over time,whereas there were large differences for July and October.Importantly,there is a substantial lack of consistency in the O.bartramii habitat distribution based on SST of two sources.This study considered the sources of environmental data for habitat modelling and then inferred species habitat distribution whether by the same or different data source.

Research on the Mass structured Data Storage and Sorting Algorithm and Methodology for SQL Database under the Big Data Environment

In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and centering on the server, the data will store model to data- centric data storage model. Storage is considered from the start, just keep a series of data, for the management system and storage device rarely consider the intrinsic value of the stored data. The prosperity of the Internet has changed the world data storage, and with the emergence of many new applications. Theoretically, the proposed algorithm has the ability of dealing with massive data and numerically, the algorithm could enhance the processing accuracy and speed which will be meaningful.

Effect of FDI on China's environmental pollution: Evidence based on spatial panel data

It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.

Frame Work of Data Envelopment Analysis—A Model to Evaluate the Environmental Efficiency of China'S Industrial Sectors

Objective To evaluate the environmental and technical efficiencies of China＇s industrial sectors and provide appropriate advice for policy makers in the context of rapid economic growth and concurrent serious environmental damages caused by industrial pollutants. Methods A data of envelopment analysis （DEA） framework crediting both reduction of pollution outputs and expansion of good outputs was designed as a model to compute environmental efficiency of China＇s regional industrial systems. Results As shown by the geometric mean of environmental efficiency, if other inputs were made constant and good outputs were not to be improved, the air pollution outputs would have the potential to be decreased by about 60% in the whole China. Conclusion Both environmental and technical efficiencies have the potential to be greatly improved in China, which may provide some advice for policy-makers.

Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization

This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.

Employment effect of China's environmental regulation: Evidence based on spatial panel data

This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.

Environmental Information Governance Reform in the Era of Big Data--From Information Disclosure to Public Service

The development of environmental information governance includes three phases: providing for oneself,information disclosure,and public service. And then China is in the transition and transformation of environmental information disclosure to the environmental information public service. The core of the transformation is public participation,in the whole procedure of environmental information supply decision making,production,and quality supervision and evaluation,etc. The target path of the environmental information governance reform includes five parts: improvement of public satisfaction,optimizing information disclosure,information quality control,integration of information resources,and multiple supply.

基于Panel Data和SEA的环境Kuznets曲线分析——与马树才、李国柱两位先生探讨

针对当前学者研究中国环境Kuznets曲线存在的问题,本文使用了面板数据模型和空间计量模型,以克服使用时间序列模型时样本数量偏少和使用截面数据时易引起空间自相关性等问题。结果表明中国有部分环境指标满足环境Kuznets曲线的倒U型特征。

基于环境质量指数的塔里木河下游生态输水效益评估

环境质量指数(EQI)是由气候/气象、水资源、土壤、地形地貌和生物多样性等方面的环境要素组成的,能够快速全方位定量评估自然环境总体质量的工具。基于遥感、实地监测、文献等多源数据,用熵值法、主成分分析和层次分析等方法计算EQI,对2000、2010年和2020年塔里木河下游自然环境质量进行综合评价。结果表明:(1)在生态输水作用下,2000—2020年塔里木河下游自然环境质量有显著改善。其中,EQI相对较高的区域主要分布在近河道两岸和湖盆周边。(2)2000—2010年环境质量改善(改善面积为15620 km^(2))较2010—2020年(改善面积为13831 km^(2))明显。(3)环境质量较差及以下(EQI<0.4)和较好(EQI≥0.8)等级的EQI的增加最为明显,而环境质量差(0.4≤EQI<0.5)和良好(0.6≤EQI<0.8)等级的EQI增加不显著。生态输水量的增加显著减少了EQI偏低和中等区域面积,促进了EQI偏高的区域面积增加,说明总体上生态输水改善了研究区环境质量。

Research and development of Chinese LCA database and LCA software

This paper detailed introduces the related work for building Chinese National Database, Sinocenter, of materials life cycle assessment (MLCA) and developing the environmental burden dataset of materials. The MLCA database was built in 2004, and the basic framework mainly includes LCA methodology, materials environmental dataset about energy consumption, resource input and environmental emissions. Nowadays, the database contains about fifty-thousand records of the main materials industries, such as cement, iron and steel, nonferrous metal, etc., and also includes the primary LCI data of fossil fuels and electricity grid in China. At the same time, the LCA method localization work is going on, for instance, calculated the resource characterization factors of 42 kinds of metal and 58 sorts of nonmetal, and also obtained some heavy metal impact factors in water. Based on the database, the iron and steel dataset has been developed with the data quality analysis, and some environmental burden data could be queried in our website, www.cnmlca.com, in the future. Lastly, according to the framework of the ISO14040 series standards, the antitype of Chinese LCA evaluation system was developed to support materials and products LCA evaluation in China.

An Overview of Big Data Industry in China

The year of 2011 is considered the first year of big data market in China.Compared with the global scale,China's big data growth will be faster than the global average growth rate,and China will usher in the rapid expansion of big data market in the next few years.This paper presents the overall big data development in China in terms of market scale and development stages,enterprise development in the industry chain,the technology standards,and industrial applications.The paper points out the issues and challenges facing big data development in China and proposes to make polices and create support approaches for big data transactions and personal privacy protection.

Addressing the Security Challenges of Big Data Analytics in Healthcare Research

Big data and associated analytics have the potential to revolutionize healthcare through the tools and techniques they offer to manage and exploit the large volumes of heterogeneous data being collected in the healthcare domain. The strict security and privacy constraints on this data, however, pose a major obstacle to the successful use of these tools and techniques. The paper first describes the security challenges associated with big data analytics in healthcare research from a unique perspective based on the big data analytics pipeline. The paper then examines the use of data safe havens as an approach to addressing the security challenges and argues for the approach by providing a detailed introduction to the security mechanisms implemented in a novel data safe haven. The CIMVHR Data Safe Haven (CDSH) was developed to support research into the health and well-being of Canadian military, Veterans, and their families. The CDSH is shown to overcome the security challenges presented in the different stages of the big data analytics pipeline.

环境病原微生物研究数据库及数据挖掘方法

环境生物安全与社会稳定、人类健康及国防安全等多个关键领域密切相关。鉴于气候变化以及人类活动对生态系统不断加大的压力,未知病原体从环境中溢出的风险显著增加。当前的研究方法多集中于已知病原体的检测与分析,然而,组学技术及其相关生物信息学技术的快速发展与应用,为识别未知环境病原体及预警潜在的环境健康风险提供了新的机遇与解决方案。这些技术的发展不仅促进了对微生物与动物、人类以及环境之间相互作用关系的理解,更是实现“同一健康(One Health)”理念的重要组成部分。本文概述了全球变化对环境病原体逸出的影响及其引发的健康风险,从数据存储、数据分析到数据挖掘三个维度对生物信息学在环境病原体研究中的应用与进展进行了深入探讨,对当前领域内存在的问题进行了剖析,并对未来利用大数据进行环境病原体检测与风险评估的应用前景进行了展望。

环境规制、数据要素配置水平与产业结构调整

文章基于数字经济、绿色经济发展深刻影响产业结构转型升级进程这一背景,首先在理论分析的基础上构建了数据要素配置水平综合评价指标体系;然后采用Dagum基尼系数对数据要素配置水平的空间差异及主要来源进行分解测算;最后,基于2012—2019年省级面板数据探讨了环境规制的结构调整红利及数据要素有效配置的渠道效应。研究结果显示,我国数据要素配置水平总体空间差异明显,且区域间差异为主要来源,区域内差异次之。环境规制对产业结构升级存在先促进后抑制的“倒U”型影响,数据要素配置也有显著促进作用。动态边际效应结果显示,在研究期内环境规制所带来的产业结构“调整红利”正在逐渐弱化,数据要素优化配置可充当环境规制促进产业结构升级的有效路径,且从子维度来看,数据传播共享的渠道效应最为显著。数据要素配置的网络外部性特征对环境规制和产业结构优化的调节作用在不同地区所呈现的阶段性特征不同。

中国海洋环境数据及其资产价值评估体系的现状

海洋环境数据是人类认识海洋、保护和开发利用海洋的重要战略资源。随着数字经济和科学技术的迅猛发展,海洋环境数据成为新的重要的生产要素。海洋环境数据资产作为一种新的资产形式,如何对其进行价值评估成为一个新的难题。通过对国内海洋数据资产价值评估的深入调查和研究,得出传统的成本法和收益法及其二者组合的方法是目前海洋环境数据价值评估的基础,发现新时期海洋环境数据的价值评估的方法具有复杂性、灵活性和多维度等的评价方式,对海洋经济发展和海洋科学研究可持续性具有非常重要的经济价值。

海洋环境数据交易定价的关键基础与相关机制

海洋环境数据作为发展海洋经济的重要基础性要素,其市场化机制的相关理论与实践均处于探索起步阶段。数据交易定价是在交易过程中对数据资源及其通过加工形成的数据产品和服务进行定价,作为数据交易开展的重点和前提,数据交易定价是数据要素市场化的关键环节。文章基于海洋环境数据特征分析了其交易定价的部分关键基础,包括相关的基本概念、数据确权和价值评估,进而讨论了交易定价的相关机制,包括定价主体、定价方法以及定价策略,最后基于上述分析在海洋环境数据的权益分配和交易平台建设等方面提出了建议。

环境分权与企业生产率--来自“国控源环境数据直报”政策的经验证据

环境分权是中央政府和地方政府对于环境事权的分配,而“国控源环境数据直报”政策本质上是一次调整环境分权化水平的改革。将该政策视为一个准自然实验,构建双重差分模型,考察其对企业生产率的影响。研究发现,该政策在短期内会显著抑制国家重点监控企业的生产率提升,但随着时间的推移,这种抑制作用会逐渐消失。结合环境分权理论进一步阐释和验证该政策对企业生产率的潜在影响机制,发现该政策主要通过挤出企业研发投入、抑制企业寻租行为和激励企业自愿规制环境行为等机制抑制企业生产率。进一步分析表明,企业所有制、行业污染密集程度和地区市场化水平等特征会对环境分权与企业生产率之间的关系产生异质性影响。环境分权与微观企业行为之间因果关系的揭示,可以为政府健全“国控源环境数据直报”政策的长效机制提供决策参考。

基于红外成像技术的城乡局部环境监测与分析研究

结合红外探测成像技术在复杂环境监测中的独特优势,研制了基于连续变焦中波红外成像技术的城乡局部环境监测系统,对城乡局部地区燃煤情况开展实时监测,并完成数据处理分析,为研究城乡地区燃煤趋势和特点、实施监控管理提供有力技术和数据支撑。经过在某市城乡结合地区开展的实地监测试验验证,证明该系统运行稳定、成像清晰,可实现对燃煤地区全局和重点位置的全天候在线监测,数据处理准确有效,该系统具有良好的工程应用价值。