线形工程中GPS高程拟合方法的探讨

介绍了多项式曲线拟合法和三次样条拟合法用于GPS水准联测点按线状或带状布设的情况,并通过实例简要分析了其优缺点。     

地理信息科学方法论的理论体系研究

地理信息科学是地理学的一个分支,其方法论研究受到科学哲学和地理学方法论的指导,同时也从大量的该学科研究成果、工程项目和软硬件产品中提炼的案例中总结和归纳而来。本文在本学科的时代需求和国家前瞻布局的背景下开展研究。首先阐述了地理信息科学方法论的哲学观和实用观,提出了研究中应该处理好的六个关系;其次,建立了方法论的结构体系,由地理信息本体论、六个科学方法和七个技术方法组成;再次,分析和论证了地理信息的本体特征及其与方法论的关系,最后讨论了地理信息科学方法论的创新机制和策略。     

TIN DEM线性内插不确定性的随机过程模型

基于随机过程模型导出了TIN DEM线性内插的随机过程模型,给出了不规则随机空间三角形的不确定性描述,讨论了TIN节点误差在线性内插中的传播问题。通过理论推导和实际算例,得到了TIN DEM线性内插点的点位方差和误差椭球半轴的解析表达式、线性内插精度最高点坐标的解析表达式,该结论与三角形的形状无关;对DEM线性外推导致精度急剧下降的必然性结论进行了理论证明;得到TIN线性内插的平均点位方差解析式,从理论上说明了本文结论的有效性。     

辽宁省基础地理信息数据库系统关键模块的优化

随着数字中国地理空间框架建设的加速推进,国家提出了对全国1∶10 000基础地理信息数据进行整合与数据库升级的要求。辽宁省响应国家号召,依托海量的测试数据,从生产实际出发,对数据库系统进行优化。本文重点阐述对数据库系统中质检功能、制图功能的优化处理以及针对新修订的数据字典系统内相应模块的升级,同时对优化过程中系统内部处理不了的问题,进行关键功能模块的补充开发。     

GIS支持下森林火场蔓延的空间模拟

林火扩展具有时间和空间特征。对火场模拟必须建立在空间背景数据库之上，即在地理信息系统和遥感技术的辅助下完成。森林火灾的发生发展有内在和外在因素的影响，内在因素包括了可燃物类型、可燃物湿度、地形，考虑这些因素形成了像元尺度植被燃烧基本历时图；外在因素主要是气候的影响，文中利用生成的植被起火概率图控制像元是否起火。在火场扩展中将Ｒｏｔｈｅｒｍｅｌ模型和经验模型结合使用，并考虑了坡度和风向带方向的因素的影响。最后利用迷宫算法在计算机上实现了火场在地理信息系统支持下的空间蔓延动态模拟。     

地球空间信息技术在新一轮国土资源大调查中的应用探讨

从分析全球变化和社会可持续发展研究的要求出发,提出地球空间信息技术的形成背景和应用基础。针对新一轮国土资源大调查的性质和任务,探讨了地球空间信息技术在新一轮国土资源大调查中的应用。     

运用社交网络分析淹水空间信息之关联性

随着社交网络的普遍发展,大量的讯息透过智能手机发布在个人的微博或其他社交网站。台湾地区的社交网站以脸书(Facebook)的使用量最大,平均每天有近千万笔的讯息量,大多数的讯息多以食衣住行或个人讯息为主,但从本研究所撷取自2010年至2015年的数据中显示,公众在社交网站所分享的信息中具有降雨、淹水或相关灾情的讯息,而这些讯息具有极高比例的正确性。由于社交网站无法提供私人讯息,故本研究将从社交信息中,以地点为单位撷取大量的数据信息再辅以语意关键词萃取出有关可作为淹水预判的讯息数据。为检核资料的可性度,本研究透过历史台风数据FLO-2D仿真重建淹水之空间信息进行检核。从研究比对分析中发现,经萃取后的公众信息其与灾害的关联性及正确性相当显着,故透过社交网站中大量的非结构讯息,透过语意及空间的转换,可萃取转化为防灾信息,对广域的都市治理而言,此一讯息将可作为预判区域淹水或防救灾情报之有效参考。     

Remote sensing and information value (IV) model for regional mapping of fluvial channels and topographic wetness in the Saudi Arabia

This study aims to map regions of near surface fluvial channels, mega-basins and topographic wetness in Saudi Arabia using remote sensing data and an information value (IV) model, which is a modified approach of weight of evidence. We used the new version of the Shuttle Radar Topographic Mission (SRTM) to delineate the fluvial channels, mega-basin, and slope. These hydrological parameters were used to index the topographic wetness of each mega-basin in the region based on IV in a Geographic Information System. We validated our method using the Space Imaging Radar-C and Landsat 8 images and compared the textural features (fluvial channels) evident from SRTM digital elevation model and to determine whether these patterns were different. Our results revealed that the region is drained by nine tributaries and that the Err Rub Al Khali and Sahba mega-basins have the highest value of the IV and topographic wetness values; the Arran and coastal mega-basins have the lowest value of the IV and topographic wetness values. An integrated approach is timely and economically effective and can be applied throughout the arid and semi-arid regions to help hydrologists and urban developers.     

Temporal replication of the national land cover database using active machine learning

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.     

On predicting and improving the quality of Volunteer Geographic Information projects

Initiatives that rely upon the contributions of volunteers to reach a specific goal are growing more and more with the success of Web 2.0–interactive applications. Also scientific projects are testing and exploiting volunteers' collaboration, but the quality of information obtained with this approach is often puzzling. This paper offers a rich overview of many scientific projects where geographic contributions are committed to volunteers, to the aim of defining strategies to improve information quality. By describing real examples of Volunteer Geographic Information (VGI), the contribution establishes a categorization based on the characteristics of the information, tasks, and scopes of the projects. After a discussion on the relationships of categories and VGI quality, the paper analyses techniques to improve the quality of volunteered information according to the moment of its assessment (i.e., ex ante, ex post, or both with respect to information creation). The paper outlines the main limitations of the different approaches and indicates some guidelines for future developments.