基于特征的空间态势一体化数据模型

针对空间态势数据多源异构、分布式的特点,在分析空间态势构成要素的基础上,采用基于特征的建模方法进行概念建模,并结合面向对象的方法进行逻辑模型设计,基于XML构建空间态势数据物理模型,最终完成空间态势一体化数据模型的构建。通过实例验证表明,文中提出的空间态势一体化数据模型,可对各类空间态势数据进行统一组织管理,并可实现各空间态势信息系统之间的互操作和空间态势信息共享,具有实用性和有效性。     

基于Snake模型的建筑物群移位算法改进研究

在对Snake模型研究的基础上,结合建筑物群在移位中的特点,从2个方面对Snake模型进行改进:首先,在Snake模型中加强对齐排列建筑物群这一重要空间特征的识别,以便保持对齐排列建筑物群在移位前后不变;其次,针对传统Snake模型有时无法解决两个建筑物空间冲突的缺点,对街区中的建筑物群实行分层次移位,先将有冲突的两个建筑物作为整体,与剩余其它建筑物利用Snake模型一起移位,然后再根据文中提出的建筑物间相互冲突的4种受力模型,进行建筑物间空间冲突的移位。最后利用改进的Snake模型进行移位实验和分析。     

《重庆历史地图集·第一卷古地图》设计与研制

文章介绍了该图集编制的背景及国内编纂情况,阐述了图集需遵循的设计原则和工艺流程,构思了图集每个版块的定位及内容组成。重点对图集在编纂过程中开本设计、结构设计、内容设计、排版和整饰设计等方面进行了剖析,并根据重庆本地历史文化展现的需要,进行了对应的设计。其中的结构编排设计、内容排版设计、图名设计、文字内容结构设计,及版式中使用的中华民族文化元素和重庆本地的文化元素的有机融合等方面,在同类作品中实现了多项创新。最后,分析总结了图集编纂中的问题和解决方法,为后续相关产品的设计与编制提供参考。     

物方多视影像密集匹配方法

针对多视影像由于遮挡导致的匹配不确定性问题,该文提出一种特征点和物方地面元相结合的多视影像密集匹配方法。该方法利用规则格网划分的空间平面作为基础,通过特征点匹配获取同名像点和高程赋值的格网平面,为后续匹配提供初始的DSM。在此基础上,利用铅垂线轨迹法对平面上规则分布的平面元进行匹配,加密特征点匹配结果。通过对某区域UCX影像的匹配实验表明,该文提出的算法能高效、准确地得到匹配结果,特别对较大影像计算快速,适用于实时处理。     

一种面向异常检测的高光谱图像降维算法

针对高光谱数据预处理中传统降维算法的不足,文章提出采用线性局部切空间排列(LLTSA)算法进行降维,并在低维空间中,以数据点到背景流形的最小距离为度量进行异常目标检测。面向异常目标检测问题的降维算法,需要考虑计算量和异常污染两个问题:为减少计算量,选择图像中一部分具有代表性的训练数据进行LLTSA降维并求取用于泛化的投影矩阵;为避免异常信息对背景特性的影响,应该选择不含异常的背景训练数据建立背景流形。背景训练点的选择基于递归多层分割算法,结合分割块的大小和分割块被近邻点重构的误差,去除分割结果中可能包含异常的区域并尽可能多地保留背景信息。实验结果表明LLTSA可以利用少数特征有效区分背景和异常,基于LLTSA的检测算法比经典RX和核RX算法具有更好的异常检测性能。     

Visualizing spatiotemporal trajectories of mobile social media users using space–time cube

The implementation of social network applications on mobile platforms has significantly elevated the activity of mobile social networking. Mobile social networking offers a channel for recording an individual’s spatiotemporal behaviors when location-detecting capabilities of devices are enabled. It also facilitates the study of time geography on an individual level, which has previously suffered from a scarcity of georeferenced movement data. In this paper, we report on the use of georeferenced tweets to display and analyze the spatiotemporal patterns of daily user trajectories. For georeferenced tweets having both location information in longitude and latitude values and recorded creation time, we apply a space–time cube approach for visualization. Compared to the traditional methodologies for time geography studies such as the travel diary-based approach, the analytics using social media data present challenges broadly associated with those of Big Data, including the characteristics of high velocity, large volume, and heterogeneity. For this study, a batch processing system has been developed for extracting spatiotemporal information from each tweet and then creating trajectories of each individual mobile Twitter user. Using social media data in time geographic research has the benefits of study area flexibility, continuous observation and non-involvement with contributors. For example, during every 30-minute cycle, we collected tweets created by about 50,000 Twitter users living in a geographic region covering New York City to Washington, DC. Each tweet can indicate the exact location of its creator when the tweet was posted. Thus, the linked tweets show a Twitter users’ movement trajectory in space and time. This study explores using data intensive computing for processing Twitter data to generate spatiotemporal information that can recreate the space–time trajectories of their creators.     

Combining geographic information systems and ethnography to better understand and plan ocean space use

Agencies in the US with oversight for marine renewable energy development idealistically have sought space where this new use might proceed unhindered by other uses. Despite experiential evidence of spatial overlap among existing ocean uses, a lack of documentation made the identification of potential space-use conflicts, communication between existing and potential ocean users, and the design of mitigation exceedingly challenging.We conducted a study along the US Atlantic and Pacific coasts to gather and document available spatial information on existing use through a compilation and organization of geographic information system (GIS) data. Stakeholder group meetings were used to vet the collected spatial data, and ethnographic interviews were conducted to gather knowledge and cultural perspectives. Results show extensive coverage and overlap of existing ocean space uses and provide a visualization of the social and cultural landscape of the ocean that managers can use to determine which stakeholders to engage.Marine resource managers are encouraged to recognize that marine space use is dynamic and multi-dimensional and as such research thereof requires a balance between the efficiency of GIS and the stories captured and told by ethnographic research. There are important linkages within and across fisheries and other uses, communities and interests, and across the land–sea interface. Therefore, it is important to use techniques demonstrated in this research that (1) integrate ethnographic and geospatial data collection and analysis; (2) engage stakeholders throughout the process; and (3) recognize the unique qualities of each geographic location and user group to support sound decision-making.     

Monitoring land changes in an urban area using satellite imagery,GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.     

City of the Spectacle: White Night Melbourne and the politics of public space

Public policy frequently is utilised as a medium to facilitate or restrict access to public space, and to privilege economic priorities. In this context urban arts festivals are used as a means to generate dominant narratives of place and use of public space. Urban arts festivals generate spaces of spectacle and wonder, and are often used as marketing strategies to revitalise urban economies and differentiate cities one from another on the global stage, engendering a commodification of place. The present paper explores this tension through an examination of the role of urban arts festivals in spatial politics. White Night Melbourne is the first Australian iteration of the Nuit Blanche International, an international network of all-night arts festivals. It is used as a case study to explore the impact of an urban arts festival on the spatial politics of Melbourne. A theoretical basis is established using the frame of Guy Debord's ([1967] 1994) The Society of the Spectacle, as well as the concepts of ‘assemblage’ and ‘expressivity’.     

中国能源生态效率的空间格局与空间效应

能源生态效率兼顾能源利用中的生态效益与经济效益,是对能源—环境—经济3E系统效率的度量。基于考虑非期望产出的SBM模型对中国1997-2012年省际能源生态效率进行测度,从空间格局规模、格局强度与格局纹理三个方面分析能源生态效率的空间分布特征和演变规律,运用空间计量模型验证中国省际能源生态效率的空间溢出效应及其影响因素。研究表明:1中国能源生态效率整体偏低,低效率省份约占40%,广东、海南、福建位于能源生态效率值的最前沿,宁夏、甘肃、青海、新疆为主要的低能效地区。全国能源生态效率总体上呈U型演变格局,局部地区主要有增长型、波动型、突变型和平稳型等4种演变类型;2中国能源生态效率在省际尺度上表现出显著的全局与局部空间集聚特征,高高集聚区主要分布在东部沿海和南部沿海地区,低低集聚区主要分布在西北地区和黄河中游地区。空间格局的变化主要发生在高低集聚区与低高集聚区,其中又以京津冀地区的集聚类型演变最为显著;3中国能源生态效率存在着明显的空间效应,某一地区的能源生态效率对相邻地区的空间溢出程度均强于相邻地区的误差冲击对该地区的影响程度;在影响能源生态效率空间效应的诸多因素中,产业结构的影响最大。