辽宁省地质灾害遥感调查电子地图的制作

通过辽宁省地质构造解译图和辽宁省地质灾害遥感解译图这两个电子地图的制作，说明了电子地图制作的工具选择、制作方法、关键技术以及地图应用等。体现了地理信息系统这一现代化科技手段在防灾、减灾和地质环境的整治与保护方面的价值。     

Some requirements of an interactive software tool for life cycle analysis

This paper briefly presents the current practice for carrying out life cycle inventories, and mentions some advantages and drawbacks of a few dedicated software tools that are commercially available. A list is presented of some features that we think should be present in an ‘ideal’ life cycle analysis (LCA) software tool, after the specifications made at Ecobilan for the development of a specific tool for LCA. Some consideration is given to the technical difficulties involved, and the benefits that could be expected from the implementation of such features.     

变截面门式刚架结构极限承载力分析

采用变截面薄腹构件是门式刚架结构轻型化的主要措施之一。如何利用变截面薄腹构件的腹板屈曲后强度并同时保证构件乃至结构的安全度始终是门式刚架结构工程设计的重要内容。根据有效宽度法的基本思想,提出了相关屈曲系数概念,在变截面H钢构件双重非线性数值分析基础上获得的局部屈曲荷载拟合公式,应用于变宽度楔形腹板的有效宽度简化计算公式当中。应用改进后的有效宽度法,进行了变截面门式刚架结构考虑构件局部屈曲影响的极限承载力分析,探讨了腹板平均宽厚比、腹板楔率对结构极限承载力的影响,提出了对变截面门式刚架结构优化设计的工程建议,并具有工程指导意义。     

基于可解释机器学习的青藏高原草地物候变化多因素影响分析

气候变化背景下,青藏高原植被物候发生显著改变.然而,影响物候的水热因素众多,目前较少有研究关注多因素对青藏高原物候的影响效应,导致对青藏高原物候变化机制认识不足.为此,研究通过遥感数据解译,在对2002~2021年青藏高原草地物候时空变化特征分析的基础上,聚焦降水、气温、海拔和土壤等多方面,利用可解释机器学习方法（SHAP）揭示物候变化的主导因素,并量化分析多因素对物候的交互影响.结果表明:①青藏高原分别有56.32 %、67.65 %和65.50 %的草地表现出生长季开始时间（SOS）提前、生长季结束时间（EOS）延迟和生长季长度（LOS）延长趋势;②青藏高原草地SOS和LOS主要受水分条件影响,3月0~10 cm土壤水分对SOS提前和LOS延长起促进作用的范围分别在10~25 kg·m^-2和15~25 kg·m^-2之间,峰值分别在20 kg·m^-2和18 kg·m^-2左右;EOS则主要受温度影响,9月和10月温度越高对EOS延迟促进作用越强,并分别在高于8 ℃和-0.5 ℃时达到峰值;③水热等因素对物候的影响存在非线性交互效应,3月0~10 cm土壤水分达到20 kg·m^-2后,更有利于低降水和低海拔地区SOS提前;10月温度高于0 ℃后较好的水分条件更有利于EOS延迟;3月0~10 cm土壤水分在12~22 kg·m^-2之间时,高降水地区LOS更长.研究表明,可解释机器学习方法可为物候变化的多因素影响定量分析提供一种新的方法.     

Assessing agricultural vulnerability to climate change in the Nordic countries – an interactive geovisualization approach

Nordic agriculture must adapt to climate change to reduce vulnerability and exploit potential opportunities. Integrated assessments can identify and quantify vulnerability in order to recognize these adaptation needs. This study presents a geographic visualization approach to support the interactive assessment of agricultural vulnerability to climate change. We have identified requirements for increased transparency and reflexivity in vulnerability assessments, arguing that these can be met by geographic visualization. A conceptual framework to support the integration of geographic visualization for vulnerability assessments has been designed and applied for the development of AgroExplore, an interactive tool for assessing agricultural vulnerability to climate change in Sweden. To open up the black box of composite vulnerability indices, AgroExplore enables the user to select, weight, and classify relevant indicators into sub-indices of exposure, sensitivity, and adaptive capacity. This enables the exploration of underlying indicators and factors determining vulnerability in Nordic agriculture.     

Location and Characterization of Emission Sources for Airborne Volatile Organic Compounds Inside a Refinery in Taiwan

This study aimed to locate VOC emission sources and characterized their emitted VOCs. To avoid interferences from vehicle exhaust, all sampling sites were positioned inside the refinery. Samples, taken with canisters, were analyzed by GC–MS according to TO-14 method. The survey period extended from Febrary 2004 to December 2004, sampling twice per season. To interpret a large number of VOC data was a rather difficult task. This study featured using ordinary application software, Excel and Surfer, instead of expensive one like GIS, to overcome it. Consolidating data into a database on Excel facilitated retrieval, statistical analysis and presentation in the form of either table or graph. The cross analysis of the data suggested that the abundant VOCs were alkanes, alkenes, aromatics and cyclic HCs. Emission sources were located by mapping the concentration distribution of these four types of VOCs in terms of contour maps on Surfer. During eight surveys, five emission sources were located and their VOCs were characterized.     

Toward knowledge structuring of sustainability science based on ontology engineering

In sustainability science (SS), it is difficult to identify what needs to be solved, and it is also not clear how to solve the problems that are identified. There has been no consensus on the underlying question of “What is structuring knowledge in SS?” This paper focuses on knowledge structuring accompanied by supporting of thinking. It addresses the key challenges associated with knowledge structuring in SS, identifies the requirements for the structuring of knowledge, proposes a reference model, and develops an ontology-based mapping tool as a solution to one layer of the reference model. First, we identify the important requirements for SS knowledge structuring. Second, we develop a reference model composed of five layers based on three of the requirements. Third, we develop an ontology-based mapping tool at Layer 2 of the reference model for meeting the two major challenges for SS, namely, identifying what problems should be addressed in SS itself and proposing solutions for those problems. The tool is designed to store and retrieve information regarding SS, to provide access to a prototype ontology for SS, and to create multiple maps of conceptual chains depending on a user’s interests and perspectives. Finally, we assess whether the developed tool successfully realizes the targeted part of the reference model for SS by examining the tool’s conformity to the reference model, as well as its usability, effectiveness, and constraints. Although several issues were identified in the prototype ontology and the mapping tool, the study concluded that the mapping tool is useful enough to facilitate the function of Layer 2. In particular, the mapping tool can support thinking about SS from the viewpoint of: (a) finding new potentials and risks of technological countermeasures studied in SS; (b) helping users to get a more comprehensive picture of problems and their potential solutions; and (c) providing an effective opportunity to come up with new ideas that might not be thought of without such a tool.     

Using Earth Observation to update a Natura 2000 habitat map for a wetland in Greece

The European Habitats Directive 92/43/EEC has defined the need for the conservation of habitats and species with the adoption of appropriate measures. Within the Natura 2000 ecological network of special areas of conservation, natural habitats will be monitored to ensure the maintenance or restoration of their composition, structure and extent. The European Space Agency's GlobWetland project has provided remotely sensed products for several Ramsar wetlands worldwide, such as detailed land cover-land use, water cycle and inundated vegetation maps. This paper presents the development and testing of an operational methodology for updating a wetland's habitat map using the GlobWetland products, and the evaluation of the extent to which GlobWetland products have contributed to the habitat map updating. The developed methodology incorporated both automated and analyst-supervised techniques to photo-interpret, delineate, refine, and evaluate the updated habitat polygons. The developed methodology was proven successful in its application to the wetland complex of the Axios-Loudias-Aliakmon delta (Greece). The resulting habitat map met the European and Greek national requirements. Results revealed that GlobWetland products were a valuable contribution, but source data (enhanced satellite images) were necessary to discriminate spectrally similar habitats. Finally, the developed methodology can be modified for original habitat mapping.     

鞍山市化学事故辅助决策系统的开发

以科学实用为出发点,对鞍山市化学事故辅助决策系统的建立和开发进行了研究。分析讨论了建立该辅助决策系统软件的背景及意义;根据GB6944—2005《危险货物品名表》,应用Access2003数据库和VB6.0语言进行编程,构建危险化学品资料查询数据库,实现模糊查询和精确查询功能;通过分析、比较扩散模型中应用较广泛的高斯模型、SLAB模型、ADMS模型,结合鞍山市当地的实际气象数据,确定ADMS模型为该软件所用扩散模型,并根据ADMS模型和毒负荷法建立危险区域划分标准;根据鞍山市的实际情况,在灵图2006和消防水源电子地图的共同支持下,实现救援车辆电子地图导航和现场实时水源显示功能。     

Characterization of humic substances of different origin by means of mass spectrometry and neural networks

Mass spectrometry fingerprinting of humic acids extracted from different soils has been carried out using laser desorption/ionization mass spectrometry (LDI-TOF MS). LDI-TOF MS provides characteristic mass spectra fingerprints for the humic acids of different origin. The information given in the fingerprints was evaluated for natural grouping trends in the samples by neural networks computing tools, such as self-organizing feature map (SOFM). This approach is efficient for recognizing patterns in the humic acids samples independently of their characteristic variability; variability characterizing natural products such as humic substances. The use of multi-layer perceptron artificial neural networks gave a successful classification of the samples.