条带开采地表沉陷预计参数的确定

概率积分法是条带开采地表移动和变形预计常用的方法,而概率积分法预计的精度取决于其预计参数的确定。以国内大量的条带开采实测资料为基础,应用相似理论对条带开采地表沉陷的相似现象进行了模糊聚类分析,计算出了条带开采地表沉陷预计参数。根据所得条带开采地表沉陷相似现象的分类及其地表沉陷预计参数,应用模式识别对待求条带开采地表沉陷预计参数进行了求取。工程实例表明,用模糊优化确定的预计参数进行条带开采地表移动和变形预计,其预计结果更加可靠、准确。     

基于空间数据挖掘技术的农用地产能核算数据库的应用研究

为提高农用地产能核算数据库的利用效率,以空间关联规则为基础,在河北省土地产能核算数据库的应用中得到提高河北省农业用地普查结果的利用效率的几条知识规则。利用现有软件,使用GIS软件进行空间数据预处理及空间关系计算。属性数据使用access管理,而关联规则挖掘算法直接应用Clementine。通过数据选取、数据预处理、数据变换、数据挖掘算法实施以及模式解释与评估,从空间数据库中提取用户感兴趣的空间模式与特征、空间与非空间数据的普遍关系及其他一些隐含在数据中的普遍的数据特征,从而得到提高土地产能核算成果利用效率的规律。     

矿区简易CORS系统的建立及应用

针对当前GPS技术广泛应用于变形监测领域的趋势和矿区开采沉陷监测的特点,从适用性、经济性出发,阐述在矿区开采沉陷地表移动研究中CORS系统的建立,经过实践检验,为CORS系统的建立使用提出参考意见。     

GIS在采煤沉陷区生态价值评价中的应用

以淮南市在采煤沉陷区生态治理规划中对规划区的生态价值评价为例,探讨了运用GIS技术和多源信息复合原理对规划区进行生态要素单因子评价和生态价值综合评价,选取评价因子包括地形因子、生态基质因子、植被因子及水环境保护因子。采用遥感与地理信息系统相结合的技术,建立与评价相关的基于GIS的基础数据平台,运用GIS的空间分析功能对规划区的生态价值进行分析和评估。通过对规划区各类生态因子的评价,深入了解规划区内生态价值的特征与空间分布,提取重要生态节点;为挖掘规划区生态建设潜力,实施生态治理和建设提供依据。     

论地理国情监测的技术支撑

地理国情监测是新时期空间信息科学的重要使命。对地理国情监测的必要性和内容进行了讨论,逐一剖析了空天地一体化遥感技术、全球卫星导航定位技术、网格GIS技术、地理信息网络服务、多维时空数据挖掘技术、空间信息云计算技术等在地理国情监测中的地位和作用、面临的问题和发展建议,以期为全面实现地理国情的定期监测、日常监测和应急监测奠定技术基础。     

从激光扫描数据中进行建筑物特征提取研究

提出了一套基于建筑物几何特征的信息挖掘方案,并具体介绍了研究中采用的一些原理、方法与实用算法,从而可以直接从激光扫描数据中提取建筑物的平面外轮廓信息。利用本方案对车载激光扫描系统获取的城市建筑物试验数据进行了具体的处理,并给出了三维建模和可视化表达结果。     

Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery

Being able to quantify land cover changes due to mining and reclamation at a watershed scale is of critical importance in managing and assessing their potential impacts to the Earth system. In this study, a remote sensing-based methodology is proposed for quantifying the impact of surface mining activity and reclamation from a watershed to local scale. The method is based on a Support Vector Machines (SVMs) classifier combined with multi-temporal change detection of Landsat TM imagery. The performance of the technique was evaluated at selected open mining sites located in the island of Milos in Greece. Assessment of the mining impact in the studied areas was based on the confusion matrix statistics, supported by co-orbital QuickBird-2 very high spatial resolution imagery. Overall classification accuracy of the thematic land cover maps produced was reported over 90%. Our analysis showed expansion of mining activity throughout the whole 23-year study period, while the transition of mining areas to soil and vegetation was evident in varying rates. Our results evidenced the ability of the method under investigation in deriving highly and accurate land cover change maps, able to identify the mining areas as well as those in which excavation was replaced by natural vegetation. All in all, the proposed technique showed considerable promise towards the support of a sustainable environmental development and prudent resource management.     

Development of a data mining method for land control

Land resources are facing crises of being misused, especially for an intersection area between town and country, and land control has to be enforced. This paper presents a development of data mining method for land control. A vector-match method for the prerequisite of data mining i. e., data cleaning is proposed, which deals with both character and numeric data via vectorizing character-string and matching number. A minimal decision algorithm of rough set is used to discover the knowledge hidden in the data warehouse. In order to monitor land use dynamically and accurately, it is suggested to set up a real-time land control system based on GPS, digital photogrammetry and online data mining. Finally, the means is applied in the intersection area between town and country of Wuhan city, and a set of knowledge about land control is discovered.     

Assessing relevance of tweets for risk communication

ABSTRACT

Although Twitter is used for emergency management activities, the relevance of tweets during a hazard event is still open to debate. In this study, six different computational (i.e. Natural Language Processing) and spatiotemporal analytical approaches were implemented to assess the relevance of risk information extracted from tweets obtained during the 2013 Colorado flood event. Primarily, tweets containing information about the flooding events and its impacts were analysed. Examination of the relationships between tweet volume and its content with precipitation amount, damage extent, and official reports revealed that relevant tweets provided information about the event and its impacts rather than any other risk information that public expects to receive via alert messages. However, only 14% of the geo-tagged tweets and only 0.06% of the total fire hose tweets were found to be relevant to the event. By providing insight into the quality of social media data and its usefulness to emergency management activities, this study contributes to the literature on quality of big data. Future research in this area would focus on assessing the reliability of relevant tweets for disaster related situational awareness.     

采动区旧址文物类建筑物评价方法

针对采动区旧址文物类建(构)筑物的特殊性,文章提出采动影响下旧址文物类建(构)筑物损坏的多因素单一综合评价方法。以安源煤矿革命旧址建(构)筑物为研究对象,系统分析了革命旧址建(构)筑物的损坏原因,并确定相应的评价指标,采用加权平均法对建(构)筑物的损害进行综合评价分析。结果表明,评价结果与实际损坏程度相符,反映了革命旧址建(构)筑物不同于普通结构建筑物的特殊性,为采动区旧址文物类建(构)筑物损坏的评价方法提供新的途径。