关于生态环境地质的基本特点与技术分析

地球是一个生态系统,其包含了大气圈、水圈以及生物圈等。各个圈层之间存有的关联性十分密切,促进这些圈层的协调发展,才可以保障生态环境的和谐性。     

生态环境检测及环保技术的应用研究

本文以生态环境检测及环保技术的应用为研究对象,主要介绍了生态环境检测以及环保技术应用面临的主要问题,而且提出了生态环境检测及环保技术应用的有效措施,希望可以为相关工作人员提供参考意见。     

生态修复的环境法属性探讨

在环境法中,要了解生态修复的属性。目前,业界关于生态修复的研究还处于初级阶段,掌握生态修复的含义,了解生态修复与法律之间的关系,才能进一步探讨生态修复的环境法属性。在生态修复上,政府起到极其重要的作用,政府要加强对环境的保护,使生态修复能够真正落到实处,并严格依据环境法的要求及时追究侵害人的责任。     

基于大数据技术构建生态环境信息化体系及其重点应用研究

本文首先分析了生态环境信息化体系的主要构成要素,其后基于大数据技术的生态环境信息化体系重点领域应用进行了深入研究。     

基于改进的SPAR-H化工实验室人因可靠性分析

近年来化工实验室事故屡禁不止,其中人的不安全行为是导致事故发生的主要原因.为评估实验人员可靠性,进一步管控化工实验室人的不安全行为,基于标准化工厂人因可靠性分析(SPAR-H)方法,结合化工实验室人因失误的特点,确定了更加适用于化工实验室的人因可靠性分析方法.首先依据"S-O-P"认知模型对人因失误类型进行划分;然后基...     

BIM技术在钢结构建筑抗震减灾管理中的应用

为提高钢结构建筑抗震减灾性能,降低建筑坍塌风险,研究BIM技术在钢结构建筑抗震减灾管理中的应用方法是非常必要的.利用BIM技术在钢结构建筑整体建造中的动态建模、可视化、信息共享管理以及抗震减灾性能检测等优势,在建筑抗震减灾管理决策阶段,选出最优方案,针对方案中影响建筑抗震减灾性能风险制定管理策略;在设计阶段,创建三维建...     

A Simulation Study to Assess the Sensitivity of a Forest Health Monitoring Network to Outbreaks of Defoliating Insects

The sensitivity of the United States Forest Health Monitoring network to outbreaks of defoliating insects was examined by means of a simulation study. A model constructed specifically for the study was used to generate a wide variety of defoliation patterns in forested landscapes. Forest configuration was that of Minnesota, USA, as expressed by the GAP land cover classification. Combinations of model parameters were based on a Latin Hypercube sample. The relationship between the average number of plots defoliated and outbreak characteristics was then examined via multiple regression. Both theoretical and model results pointed to a strong, linear relationship between the average number of plots defoliated and outbreak size. Model results provided additional insight, suggesting a significant relationship between the average number of plots defoliated and other outbreak characteristics after outbreak size was taken into account.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Interaction Between the Environment and Animals in Urban Settings: Integrated and Participatory Planning

In urban ecosystems, the ecological system has become completely unbalanced; this, in turn, has led to an increase in well-known problems such as air pollution, ground pollution, and water pollution. This imbalance has also led to the growth and spread of pathogens harmful to man, animals, and plants. Urban sustainability indicators, both global and local, also “indicate” the percentage of population, but these refer only to the human population, not the animal population. Cities need good waste, water, and air management, effective traffic planning, and good zoning of businesses, crafts, and services; over and above these activities, cities also need for planning to take into account the existence of pets (dogs, cats, and etc.) and nonpet animals (insects, birds, mice, etc.). Cities tend to be designed around humans and “on a human scale,” without taking into account the fact that a huge animal population is living side by side with people. That explains why overcrowding tends to go hand in hand with urbanization; all these populations, including humans, need to adapt to new spaces and often need to drastically change their behavior. This is a fact that must be included when drafting sustainable city plans. The supposed strategy is that of “integrated-participatory” control of the interactions between the environment and animals in the cities. Strategy will focus on the development of integrated approaches and tools for environment and animal management in the context of urban settings. This will require such specific methods as ecological balance sheets and ecoplans for the planning, management, and control of the interrelation among environment, animal, and public health. The objective is to develop a better understanding of urban biodiversity and of urban ecosystem functioning, in order to understand and minimize the negative impacts of human activities on them. The research will focus on assessing and forecasting changes in urban biodiversity, structure, function, and dynamics of urban ecosystems, with relationships among society, economy, biodiversity, and habitats.     

TUGAI: An Integrated Simulation Tool for Ecological Assessment of Alternative Water Management Strategies in a Degraded River Delta

The development of ecologically sound water allocation strategies that account for the needs of riverine ecosystems is a pressing issue, especially in semiarid river basins. In the Aral Sea Basin, a search for strategies to mitigate ecological and socioeconomic deterioration has been in process since the early 1990s. The Geographic Information System–based simulation tool TUGAI has been developed to support the policy determination process by providing a simple, problem-oriented method to assess ecological effects of alternative water management strategies for the Amudarya River. It combines a multiobjective water allocation model with simple, spatially explicit statistical and rule-based models of landscape dynamics. Changes in environmental conditions are evaluated by a fuzzy habitat suitability index for Populus euphratica, which is the dominant species of the characteristic riverine Tugai forests. Water management scenarios can be developed by altering spatiotemporal water distribution in the delta area or the amount of water inflow into the delta. Outcomes of scenario analysis are qualitative comparisons of the ecological effects of different options for a time period of up to 28 years. The given approach utilizes different types of knowledge, from quantitative hydrological data to qualitative local expert knowledge. The main purpose of the tool is to integrate the knowledge in a comprehensive way to make it available for discussions on alternative policies in moderated workshops with stakeholders. In this article, the modules of the tool, their integration, and three hypothetical scenarios are presented. Based on the experience gained when developing the TUGAI tool, we propose that the general framework can be transferred to other areas where tradeoffs in water allocation between the environment and other water users are of major concern. The potential for a simulation tool to structure and inform a complex resource management situation by involving local experts and stakeholders in the development of possible future scenarios will become increasingly valuable for transparent and participatory resource management.