An intelligent decision support system for management of petroleum-contaminated sites

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers.     

土地利用/土地覆盖遥感变化检测方法新进展

土地利用/土地覆盖变化检测是资源环境研究中的一个重要方面,准确、及时的变化信息为人类资源环境的生产和管理提供了决策支持。遥感技术具有实时、快速、覆盖范围广、多光谱、周期性等特点,给土地利用/土地覆盖变化检测提供了理想的数据基础。人类社会的发展对土地利用/土地覆盖变化检测的精度与效率不断提出新的要求,这也使得一些新技术、新方法引入到变化检测中。这些新技术新方法提高了土地利用/土地覆盖变化检测的精度,但在效率方面有待进一步研究。     

Characterising performance of environmental models

In order to use environmental models effectively for management and decision-making, it is vital to establish an appropriate level of confidence in their performance. This paper reviews techniques available across various fields for characterising the performance of environmental models with focus on numerical, graphical and qualitative methods. General classes of direct value comparison, coupling real and modelled values, preserving data patterns, indirect metrics based on parameter values, and data transformations are discussed. In practice environmental modelling requires the use and implementation of workflows that combine several methods, tailored to the model purpose and dependent upon the data and information available. A five-step procedure for performance evaluation of models is suggested, with the key elements including: (i) (re)assessment of the model's aim, scale and scope; (ii) characterisation of the data for calibration and testing; (iii) visual and other analysis to detect under- or non-modelled behaviour and to gain an overview of overall performance; (iv) selection of basic performance criteria; and (v) consideration of more advanced methods to handle problems such as systematic divergence between modelled and observed values.     

空间观测技术在油棕研究中的应用

油棕是一种重要的热带经济作物,在热带地区种植面积迅速扩张,已经成为全球最大的植物油来源。油棕扩张在带来经济效益的同时,也在不断侵占全球现有的森林、耕地和泥炭地,造成严重的生态环境问题。空间观测技术（RS、GIS、GNSS,3S技术）是空间信息收集、分析和管理的有效工具,在优化土地利用类型空间布局和可持续发展规划中发挥着重要作用。通过文献综述和文献计量学的方法,分析3S技术在油棕研究中的应用进展,并探讨影响油棕制图精度的关键因素。研究发现：该领域的论文主要以土地覆被变化研究为知识基础,来自马来西亚、美国、中国、印度尼西亚和英国的科研机构和研究人员是最主要参与者;目前3S技术在油棕研究中的应用包括油棕制图、油棕变化监测、油棕树计数、树龄估算、地上生物量与碳储量估算、适宜性评估、产量估算、病虫害监测、种植园管理等;制图精度与论文发表时间并没有明显相关性,与遥感数据源、分类方法具有相关性;目前油棕研究中的3S技术以RS为主导,RS应用于油棕研究的各个关键方向,GIS技术主要应用于油棕变化制图、适宜性评估、种植园管理、病虫害监测等,GNSS主要作为辅助工具,应用于病虫害监测和种植园管理等。     

The implications of complexity for integrated resources management

Integrated environmental resources management is a purposeful activity with the goal to maintain and improve the state of an environmental resource affected by human activities. In many cases different goals are in conflict and the notion “integrated” clearly indicates that resources management should be approached from a broad perspective taking all potential trade-offs and different scales in space and time into account. However, we are yet far from putting into practice integrated resources management fully taking into account the complexity of human-technology-environment systems. The tradition of resources management and of dealing with environmental problems is characterized by a command and control approach. The increasing awareness for the complexity of environmental problems and of human-technology-environment systems has triggered the development of new management approaches. The paper discusses the importance of focusing on the transition to new management paradigms based on the insight that the systems to be managed are complex adaptive systems. It provides arguments for the role of social learning processes and the need to develop methods combining approaches from hard and soft systems analysis. Soft systems analysis focuses on the importance of subjective perceptions and socially constructed reality. Soft systems methods and group model building techniques are quite common in management science where the prime target of management has always been the social system. Resources management is still quite slow to take up such innovations that should follow as a logical consequence of adopting an integrated management approach. Integrated water resources management is used as example to provide evidence for the need to implement participatory and adaptive management approaches that are able to cope with increasing uncertainties arising from fast changing socio-economic conditions and global and climate change. Promising developments and future research directions are discussed. The paper concludes with pointing out the need for changes in the scientific community to improve the conditions for interdisciplinary, system-oriented and trans-disciplinary research.     

Designing and building real environmental decision support systems

The complexity of environmental problems makes necessary the development and application of new tools capable of processing not only numerical aspects, but also experience from experts and wide public participation, which are all needed in decision-making processes. Environmental decision support systems (EDSSs) are among the most promising approaches to confront this complexity. The fact that different tools (artificial intelligence techniques, statistical/numerical methods, geographical information systems, and environmental ontologies) can be integrated under different architectures confers EDSSs the ability to confront complex problems, and the capability to support learning and decision-making processes. In this paper, we present our experience, obtained over the last 10 years, in designing and building two real EDSSs, one for wastewater plant supervision, and one for the selection of wastewater treatment systems for communities with less than 2000 inhabitants. The flow diagram followed to build the EDSS is presented for each of the systems, together with a discussion of the tasks involved in each step (problem analysis, data collection and knowledge acquisition, model selection, model implementation, and EDSS validation). In addition, the architecture used is presented, showing how the five levels on which it is based (data gathering, diagnosis, decision support, plans, and actions) have been implemented. Finally, we present our opinion on the research issues that need to be addressed in order to improve the ability of EDSSs to cope with complexity in environmental problems (integration of data and knowledge, improvement of knowledge acquisition methods, new protocols to share and reuse knowledge, development of benchmarks, involvement of end-users), thus increasing our understanding of the environment and contributing to the sustainable development of society.     

土壤侵蚀调查中的遥感应用综述

土壤侵蚀引起土壤肥力下降、土地退化及荒漠化和生态环境恶化等一系列区域性和世界性的重大环境问题。中国是土壤侵蚀最严重的国家之一。遥感是进行环境和灾害动态监测的有效技术手段。自从20世纪70年代以来．人们就开始应用遥感技术进行土壤侵蚀的调查。对遥感技术在土壤侵蚀调查中的应用方法进行概括和汇总，分别是影像判读法、指数提取法、图像分类法、光谱分解和正射影像DEM提法等方法，分析不同方法之间的优缺点以及它们各自的适用范围，并结合当前研究的热点问题，指出未来研究的重点及趋势。     

Suitability evaluation of urban construction land based on geo-environmental factors of Hangzhou, China

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management. With the support of Geographic Information Systems (GIS), grid analysis, and geo-spatial analysis techniques, four factor groups comprising nine separate subfactors of geo-environmental attributes were selected to be used in the evaluation of the suitability level for construction land in Hangzhou. This was based on K-means clustering and back-propagation (BP) neural network methods due to their advantages in fast computing, unique adaptive capacity, and self-organization. Simultaneously, the evaluation results based on K-means clustering and BP neural network were compared and analyzed, and the accuracy evaluation was set. The results showed that the geo-environmental suitability evaluation results of construction land based on K-means clustering and BP neural network were similar in terms of the distribution and scale of construction land suitability level. At the same time, the results of the two evaluation methods were consistent with the variability in suitability level, engineering geology, and hydrogeology of Hangzhou. The results also showed that the real advantage of the methods proposed in this paper lies in their capacity to streamline the mapping process and to ensure that the results are consistent throughout. The suitability level of the urban construction land based on the geo-environment in Hangzhou was divided into four construction sites: land for building super high-rise and high-rise buildings, land for building multistorey buildings, land for low-rise buildings, and nonbuilding land. The results of the suitability evaluation for each category will provide a scientific basis for decision-making in urban development in Hangzhou.     

河湖水环境治理支撑系统设计及应用构想

为提高水环境治理水平、改善水环境质量提供服务和支撑,针对水环境治理信息化支撑不足的现状, 探讨信息化支撑系统设计思路、实现技术和应用场景。基于 GIS 技术构建水环境治理数据库,利用支撑系统融合应用 GIS、数据库、环境模拟和绩效评价等技术,对不同要素集成管理,供各子系统调用,结合水环境模型、 绩效评价等实现治理效果的模拟、预测和评估。支撑系统可以实现水环境信息管理、治理技术检索与查询、辅助决策、绩效评估和可视化呈现等功能,为水环境治理提供规划、设计、管理及评估咨询和服务。提出的基于 GIS、融合环境和绩效评估技术的水环境治理支撑系统,适用于水环境综合信息管理、规划及决策管理和工程绩效评估,实现对水环境治理的信息化支撑。     

高校财务数据仓库的设计与实现

高校的信息化工作已从管理系统发展到决策支持系统,数据仓库是决策支持系统的核心。该文分析高校财务预算系统的现状和存在的问题设计实现一个数据仓库系统,利用OLAP技术进行数据分析。系统通过在某高校的实际应用,取得了良好效果。     

Distance-based intuitionistic multiplicative multiple criteria decision-making methods for healthcare management in West China Hospital

Intuitionistic multiplicative sets use an asymmetric, unbalanced scale to express information from positive, negative, and indeterminate information. They have been found capable of comprehensively and objectively representing a person's intuitive understanding and hence have attracted much attention. Distance techniques are widely used to measure the degree to which arguments deviate from one another. Several fuzzy set extensions have been developed, but little research has been conducted on measures of distance between intuitionistic multiplicative sets. In this paper, we start by presenting a variety of measures of the distance between intuitionistic multiplicative sets, including Hausdorff distance measures, weighted distance measures, ordered weighted distance measures, and continuous weighted distance measures. We then develop a distance-based intuitionistic multiplicative-technique for order preference by similarity to ideal solution method and a distance-based intuitionistic multiplicative-Vlsekriterijumska Optimizacija I Kompromisno Resenje method for handling multiple criteria decision-making problems with intuitionistic multiplicative evaluation information. To demonstrate the practical application of these distance measures and the proposed methods, we provide a case study of hospital management of inpatient admission. The paper ends with comparative analyses of the two methods and some concluding remarks.     

Satellite remote sensing of deforestation in the Sungai Buloh Forest Reserve,Peninsular Malaysia

Deforestation has been a very critical environmental problem during the past few decades. Monitoring the Earth's surface conditions and their changes are essential to the management of this global environmental problem. Remote sensing can provide an effective 1001 for monitoring environmental changes on a global scale. This has focused attention on developing more effective and efficient techniques for the management and survey of forest areas. This study was designed to assess the feasibility of utilizing Landsat TM data in monitoring deforestation in the Sungai Buloh Forest Reserve. Detection of land cover change due to urbanization was performed using rnulti-tempora! data taken in 1988and 1991. An IDRISI image processing system was used to analyse the satellite data. Multi-temporal images were registered and spectral signatures of each point were directly compared. Correlation analysis was used to evaluate the similarity of two spectral signatures. A false colour composite image of bands 4, 5 and 3 (Red-Green-Blue) was used in unsupervised classification. For detection of land cover change, both multi-temporal images were overlaid and the area was calculated. The study revealed that the rate of deforestation in the Sungai Buloh Forest Reserve is about 182ha yr^-1 with an accuracy of 90·0 per cent.     

基于KPI体系和主题模型的火力发电企业辅助决策系统的实现

针对火力发电企业的生产、经营、燃料和环保的关键绩效指标（KPI）,分别应用同环比分析、趋势分析、杜邦分析、量本利分析、对标分析等模型和方法,采用主题模型的设计思想,实现了火力发电企业辅助决策系统,在电量分析、安全生产、费用监控、节能减排等方面为发电企业提供分析和决策依据,从而在更高层次上提升其生产和经营的管理水平。     

基于WebGIS的成都市基准地价信息系统的构建

以ASP.NET2.0为开发工具,GeoMedia WebMap 6.0为GIS平台,针对决策层、土地管理工作者、社会公众对基准地价信息的需求,设计并开发了成都市中心城区基准地价信息系统,该系统提供了成都市基准地价信息的查询、统计与分析、制图等功能一体化的网络地理信息服务,从而为管理、决策提供服务和参考,以及为公众提供成都市基准地价信息的查询、浏览服务。     

MCE-RISK: integrating multicriteria evaluation and GIS for risk decision-making in natural hazards

During the past two decades there have been a wide range of applications for decision-making linking multicriteria evaluation (MCE) and geographic information systems (GIS). However, limited literature reports the development of MCE-GIS software, and the comparison of various MCE-GIS approaches. This paper introduces an MCE-GIS program called MCE-RISK for risk-based decision-making. It consists of a series of modules for data standardisation, weighting, MCE-GIS methods, and sensitivity analysis. The program incorporates different MCE-GIS methods, including weighted linear combination (WLC), the technique for order preference by similarity to ideal solution (TOPSIS), and compromise programming (CP), enabling comparisons between different methods for the same decision problem to be made. An example of decision-making for determining priority areas for a bushfire hazard reduction burning is examined. After implementing the alternative MCE-GIS methods, and comparing final outputs and the computational difficulty involved in the analysis, WLC is recommended. Some caveats on using MCE-GIS methods are also discussed. Although the development of MCE-RISK and its application reported in this paper are specific to risk-based decision-making in natural hazards, the program can be used for other environmental decision applications, such as environmental impact assessment and land-use planning.     

Effects of increasing fuzziness on analytic hierarchy process for spatial multicriteria decision analysis

Multicriteria decision analysis (MCDA) involves techniques which relatively recently have received great increase in interest for their capabilities of solving spatial decision problems. One of the most frequently used techniques of MCDA is Analytic Hierarchy Process (AHP). In the AHP, decision-makers make pairwise comparisons between different criteria to obtain values of their relative importance. The AHP initially only dealt with crisp numbers or exact values in the pairwise comparisons, but later it has been modified and adapted to also consider fuzzy values. It is necessary to empirically validate the ability of the fuzzified AHP for solving spatial problems. Further, the effects of different levels of fuzzification on the method have to be studied. In the context of a hypothetical GIS-based decision-making problem of locating a dam in Costa Rica using real-world data, this paper illustrates and compares the effects of increasing levels of uncertainty exemplified through different levels of fuzzification of the AHP. Practical comparison of the methods in this work, in accordance with the theoretical research, revealed that by increasing the level of uncertainty or fuzziness in the fuzzy AHP, differences between results of the conventional and fuzzy AHPs become more significant. These differences in the results of the methods may affect the final decisions in decision-making processes. This study concludes that the AHP is sensitive to the level of fuzzification and decision-makers should be aware of this sensitivity while using the fuzzy AHP. Furthermore, the methodology described may serve as a guideline on how to perform a sensitivity analysis in spatial MCDA. Depending on the character of criteria weights, i.e. the degree of fuzzification, and its impact on the results of a selected decision rule (e.g. AHP), the results from a fuzzy analysis may be used to produce sensitivity estimates for crisp AHP MCDA methods.     

Variation in the accuracy of thermal remote sensing

Thermal infrared (TIR) remote-sensing techniques have been used to estimate land surface temperatures (LSTs) and to study the relationship between land uses and LSTs. Remotely sensed thermal data provide a time-synchronized dense grid of temperature data, and there has been a growing interest on LSTs in various fields, such as urban climatology and global environmental change. It is also important for urban planning and management practices to maintain thermally efficient urban structures. This article focuses on differences between the estimated LSTs and the measured temperatures. Three different methods, the Black Body method, the normalized difference vegetation index (NDVI) Threshold method, and the US Geological Survey (USGS) method, are used to retrieve LSTs; how various land uses affect the accuracy of LSTs is also discussed. Landsat-5 data sets covering the Columbus Metropolitan Area (CMA) are used to obtain LSTs for six different dates between January 2005 and February 2006. The land-use map is derived from Landsat-5 data, dated 1 August 2005. Measured temperatures derived from the five measuring stations, located in or near the CMA, are used to compare with LSTs. The USGS method has the estimated temperatures that are close to the measured temperatures for most cases, and the LSTs in homogeneous areas, including green and agricultural areas, have temperatures closer to the measured temperatures. Statistical results of LSTs in six land uses for seven different dates are also displayed.     

Practical verification of decision-making in agent-based autonomous systems

We present a verification methodology for analysing the decision-making component in agent-based hybrid systems. Traditionally hybrid automata have been used to both implement and verify such systems, but hybrid automata based modelling, programming and verification techniques scale poorly as the complexity of discrete decision-making increases making them unattractive in situations where complex logical reasoning is required. In the programming of complex systems it has, therefore, become common to separate out logical decision-making into a separate, discrete, component. However, verification techniques have failed to keep pace with this development. We are exploring agent-based logical components and have developed a model checking technique for such components which can then be composed with a separate analysis of the continuous part of the hybrid system. Among other things this allows program model checkers to be used to verify the actual implementation of the decision-making in hybrid autonomous systems.     

Mapping nonnative plants using hyperspectral imagery

Nonnative plant species are causing enormous ecological and environmental impacts from local to global scale. Remote sensing images have had mixed success in providing spatial information on land cover characteristics to land managers that increase effective management of invasions into native habitats. However, there has been limited evaluation of the use of hyperspectral data and processing techniques for mapping specific invasive species based on their spectral characteristics. This research evaluated three different methods of processing hyperspectral imagery: minimum noise fraction (MNF), continuum removal, and band ratio indices for mapping iceplant (Carpobrotus edulis) and jubata grass (Cortaderia jubata) in California's coastal habitat. Validation with field sampling data showed high mapping accuracies for all methods for identifying presence or absence of iceplant (97%), with the MNF procedure producing the highest accuracy (55%) when the classes were divided into four different densities of iceplant.     

Forecasting market prices in a supply chain game

Predicting the uncertain and dynamic future of market conditions on the supply chain, as reflected in prices, is an essential component of effective operational decision-making. We present and evaluate methods used by our agent, Deep Maize, to forecast market prices in the trading agent competition supply chain management game (TAC/SCM). We employ a variety of machine learning and representational techniques to exploit as many types of information as possible, integrating well-known methods in novel ways. We evaluate these techniques through controlled experiments as well as performance in both the main TAC/SCM tournament and supplementary Prediction Challenge. Our prediction methods demonstrate strong performance in controlled experiments and achieved the best overall score in the Prediction Challenge.