Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

Indoor Routing for Individuals with Special Needs and Preferences

Recently much research has been focused on developing techniques and systems for providing routes within buildings. While outdoor routing is based on criteria such as shortest, fastest and least turns, indoor routing is primarily based on accessibility and safety criteria, and while outdoor routing could adversely be impacted by weather and traffic, among other conditions, such conditions do not affect indoor routing. However, developing techniques that meet user's indoor routing preferences, especially those with special needs, is a challenging task. An example is development of a set of techniques that avoids a hallway with a protruding object to allow safe passage by the visually impaired or that avoids stairs for the mobility impaired. In this article, we present and analyze new techniques based on the Americans with Disabilities Act (ADA) standards that provide routes within buildings and meet user's special needs and preferences.     

Intelligent Visualisation and Information Presentation for Civil Crisis Management

This paper describes an ongoing research work on developing methods for effective visualisation support for situation analysis, decision making, and communication in the course of disaster management. The major goals are to reduce the information load of the analyst, decision maker, or information recipient without omission of anything important and to ensure quick and accurate comprehending of the information. The work embraces the issues of selection of the relevant information and defining the appropriate level of detail, data preparation (aggregation and other transformations), and selection of the appropriate methods for visual representation depending on the user's tasks or communication goals, recipient's profile, and the target presentation medium. A practical outcome from the research will be a knowledge base that can be used to support analysis, decision making, and information communication in emergency situations. A great part of the knowledge, specifically, knowledge on data transformation and representation, is generic and can be used for different applications.     

Interpreting map usage patterns using geovisual analytics and spatio-temporal clustering

Extracting meaningful information from the growing quantity of spatial data is a challenge. The issues are particularly evident with spatio-temporal data describing movement. Such data typically corresponds to movement of humans, animals and machines in the physical environment. This article considers a special form of movement data generated through human–computer interactions with online web maps. As a user interacts with a web map using a mouse as a pointing tool, invisible trajectories are generated. By examining the spatial features on the map where the mouse cursor visits, a user's interests and experience can be detected. To analyse this valuable information, we have developed a geovisual analysis tool which provides a rich insight into such user behaviour. The focus of this paper is on a clustering technique which we apply to mouse trajectories to group trajectories with similar behavioural properties. Our experiments reveal that it is possible to identify experienced and novice users of web mapping environments using an incremental clustering approach. The results can be used to provide personalised map interfaces to users and provide appropriate interventions for completing spatial tasks.     

Land Cover Mapping for Namdapha National Park (Arunachal Pradesh), India Using Harmonized Land Cover Legends

Since last few decades RS-GIS is playing vital role in studying and mapping spatiotemporal responses of land cover, however, as a matter of fact, the mapping outputs largely depend on the expert's/user's preferences because location specific and people specific land cover classification systems are adopted autonomously for image classification in GIS. This may actually lead to an ambiguous definition of a particular land cover type when such different maps are compared at global level. In 1993, FAO and UNEP started efforts for development of a software tool know as LCCS which is a comprehensive standardized tool capable of providing land cover characterization to all possible land cover types in the world regardless of spatial relevance, mapping scale, data collection method etc. Adding to the global efforts of land cover legend harmonization and mapping, this study presents development of harmonized land cover legends for Namdapha National Park located in north-eastern Indian Himalayan region using LCCS and subsequent mapping. The potential of Remote Sensing (RS) and Geographical Information Systems (GIS) in forest/land cover mapping is very well recognized. Therefore, adopting the developed harmonized legends for the study area, land cover mapping was done using RS-GIS approach.     

Sparse representation-based correlation analysis of non-stationary spatiotemporal big data

As the basic data of digital city and smart city research, Spatiotemporal series data contain rich geographic information. Alongside the accumulation of spatial time-series data, we are also encountering new challenges related to analyzing and mining the correlations among the data. Because the traditional methods of analysis also have their own suitable condition restrictions for the new features, we propose a new analytical framework based on sparse representation to describe the time, space, and spatial-time correlation. First, before analyzing the correlation, we discuss sparse representation based on the K-singular value decomposition (K-SVD) algorithm to ensure that the sparse coefficients are in the same sparse domain. We then present new computing methods to calculate the time, spatial, and spatial-time correlation coefficients in the sparse domain; we then discuss the functions' properties. Finally, we discuss change regulations for the gross domestic product (GDP), population, and Normalized Difference Vegetation Index (NDVI) spatial time-series data in China's Jing-Jin-Ji region to confirm the effectiveness and adaptability of the new methods.     

Ontological Engineering for Interpreting Geospatial Queries

Despite advancements in geographic information system (GIS) technology, the efficient and effective utilization of GIS to solve geospatial problems is a daunting process requiring specialized knowledge and skills. Two of the most important and burdensome tasks in this process are interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. With the current state of GIS, there exists a gap between the knowledge user's possess and the knowledge and skills they need to utilize GIS for solving problems. Currently, users resort to training and practice on GIS technology or involving GIS experts. Neither of these options is optimal and there is a need for a new approach that automates geoprocessing tasks using GIS technology. This paper presents an ontological engineering methodology that uses multiple ontologies and the mappings among them to automate certain tasks related to interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. The presented methodology includes conceptualization of geospatial queries, knowledge representation for queries, techniques for relating elements in different ontologies, and an algorithm that uses ontologies to map queries to geoprocessing operations.     

中国大陆岩石GPS平台Geo TransGIS的设计与实现

在中国大陆岩石圈地理信息系统研究过程中，提出了一种工具型二维地理信息系统和二三维地理信息系统地功能模块的设计思路，探讨了了面向对象方法，面向对象数据模型，面向对象数据库、无缝集成、开放式数据库互联技术在理信息系统研制中的运用；并用实例证明了此设计方法的可行性和实用性。     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

侧视地图中建筑物轮廓线提取的三维城市模型法

针对城市侧视地图上建筑物轮廓线主要依靠人工交互提取,成本高昂、效率低下且精细度和准确度有限的问题,提出了一种任意视角侧视地图中建筑物轮廓线的自动提取方法。采用深度缓冲区分割算法获取单个建筑物对象的颜色缓冲区,顾及了存在建筑群的情况和建筑物密集区域的遮挡问题,再基于颜色缓冲区追踪建筑物轮廓线。为了保持遮挡一致性且便于匹配提取出的矢量轮廓线与栅格侧视地图,本文还提出了基于投影空间分块加载三维城市模型的方法。最后,以武汉市典型三维城市模型数据为例,证明了该方法的有效性和可靠性。     

A procedural footprint enhancement of global topographic surface with multiple levels of detail

ABSTRACT

Virtual globes are technologies for visual navigation through a three-dimensional, multi-resolution model of the entire planet. Data representations used in virtual globes, however, lack geometric flexibility at high-resolution levels of the planet-wide terrain surface. This is a problem especially if boundaries between individual geospatial features and the terrain are important. A novel integration of individual polygonal boundaries with a specific multi-resolution representation of the planet-wide terrain is developed in this article. In the preparation stage, the integration relies on an original simplification algorithm applied to the polygonal boundaries between geospatial features and the terrain. Its output is a multiple level-of-detail (LOD) geometry, which can be combined with a known multi-LOD representation of the terrain that uses run-time triangulation. This data representation is suitable for storage in existing database systems, avoids any data redundancy across LODs, and is even independent of the subdivision schema that partitions the planet's surface for the sake of dealing with LODs. At run-time, a novel reconstruction algorithm stitches geometric parts from different LODs together in a manner that augments the multi-LOD representation of the terrain. Within a certain proximity range from a given position, the method reconstructs a scene that preserves topological relations between the boundaries of geospatial features with the terrain. The method also guarantees that certain nearest proximity to the given position consists of the best geometries that correspond to the original datasets. Such properties of the method close up the gap between a mere exploratory visualization of static, pre-generated models and the models supporting geospatial analysis, which is deemed crucial for applications in Geographic Information Systems, Building Information Modelling and other software industries. A prototype implementation and experiment results that prove this method are also presented.     

面向对象的高光谱遥感影像稀疏表示分类

稀疏表示用于高光谱遥感影像分类多是基于像素层次来处理的。文中提出一种面向对象的高光谱遥感影像稀疏表示分类方法。首先从高光谱影像中提取4个波段组成标准的多波段影像,进行面向对象的影像分割;然后计算各对象在各波段上的光谱均值,并选取少量样本进行训练;最后利用基于Fisher字典学习的稀疏表示进行高光谱遥感影像的分类。实验结果表明,该方法可以利用较少的样本得到较好的分类效果,与基于像素层的稀疏分类相比较,分类精度与效率均有所提高,分类结果更接近真实地物,避免了零碎图斑。     

激光雷达点云树木建模研究进展与展望

三维树木几何模型是数字城市与数字林业工程的重要组成部分.针对点云树木建模,深入分析了基于广义(泛在)激光雷达点云的树木模型重建方法,提出了聚类思想建模、图论方法建模、先验假设建模、拉普拉斯算子建模与轻量化表达建模5类建模体系,归纳总结了不同建模体系在树冠枝干的细节表达、建模算法性能、树木模型的多层次细节表达、建模体系综...     

Geo-questionnaires in urban planning: recruitment methods,participant engagement,and data quality

ABSTRACT

Recent focus on sustainable urban development and livability has increased the demand for new data sourcing techniques to capture experiences and preferences of urban dwellers. At the same time, developments of geospatial technologies and social media have enabled new types of user-generated geographic information and spatially explicit online communication. As a result, new public participation GIS methods for engaging large groups of individuals have emerged. One such method is geo-questionnaire, an online questionnaire with mapping capabilities, which has been used to elicit geographic data in variety of topics and geographical contexts. This article presents two recent cases, in which geo-questionnaires have been used in Polish cities to obtain public input on quality of life and development preferences in local land use planning. The article evaluates participant recruitment methods focusing on sample representativeness, participant engagement, and data quality. Recruitment via social media was found to increase bias towards younger population. Paper questionnaires used along the online version provided for better representation of target population’s age structure, but did not reduce bias related to educational attainment. We discuss how these issues relate to data usability and generalizability in the context of digital divide, and suggest directions for future research.     

Use of a Three-Domain Repesentation to Enhance GIS Support for Complex Spatiotemporal Queries

As the development of Geographic Information Systems (GIS) proceeds to advanced scientific and societal applications, there is an emerging need to enhance GIS support for complex spatiotemporal queries. Dynamic GIS representations (as opposed to static, map-based representations) that can integrate proper data elements in the production of geographic information are required. This paper demonstrates the use of a three-domain representation that facilitates compilation of higher-level information (such as frequency and rate) from preliminary data records (such as time and location) stored in a database. The three-domain representation is compared with snapshot, space-time composite, and spatiotemporal object models using a sample data set for forest transitions. While the three-domain representation is a normalization of these data models, it offers a conceptual alternative that enables GIS to represent spatiotemporal behaviors of geographic entities, in addition to entities as well as histories at locations as emphasized in most GIS data models. The comparison shows that the three-domain representation has combined the strengths of the space-time composite and spatiotemporal object models. Moreover, it enables aggregations of analytical use along with dynamic mappings between geographic concepts and locations, a distinct capability that takes GIS query processing beyond the level of information support offered by static map-based data models.     

A Method of Positional Quality Control Testing for 2D and 3D Line Strings

This article presents a positional quality acceptance control method for 2D and 3D line strings based on a statistical hypothesis test. Two statistical models are applied together: a Binomial Model is applied over a Base Model. By means of the Base Model the method can be applied to any parametric or non‐parametric error model. The Base Model represents the hypothesis about the error behavior. The Binomial Model is fixed and consists of counting the number F of fail events in a sample of a determined size. The π parameter of the Binomial Model is derived from the Base Model by means of a desired tolerance. By comparing the probabilities associated to F and π a statistical acceptance/rejection decision is achieved. This method allows us to know and control the user's and producer's risk of acceptance/rejection. An example using a 2D line string data set from a commercial product is presented. The extension of the method to the 3D line string case is also presented. In order to facilitate the application of the method, some tables linking π with F and the control sample sizes are presented.     

兼容多源数据的森林湿地信息提取和比较分析

针对以光谱特征差异为依据,提取森林湿地信息精度低的问题,该文采用兼容多源数据的分类回归树(CART)提取方法,并以大沾河国家森林湿地进行实证研究。基于Landsat8遥感数据、Radarsat-2极化雷达数据和地形辅助数据,采用SPM软件分别构建3种特征变量组合的CART决策树模型,并获取分类规则,最后根据规则对研究区的森林湿地信息进行提取。结果表明:3种特征变量组合中,兼容光谱、纹理、雷达与地形辅助数据的CART决策树的森林湿地信息提取精度最高,用户精度和制图精度分别达到了88.46%和82.14%。研究结果体现了雷达数据与地形辅助数据有助于提取森林湿地信息。     

城市街区和签到数据结合的个性化城市兴趣区域推荐方法

利用社交媒体用户的历史签到数据分析用户空间活动偏好实现用户兴趣区域推荐,在城市商业规划中起着重要作用,也为了解人们的城市生活和需求提供帮助。已有方法获得的ROI具有模糊性和多样性,无法给ROI赋予准确的地理描述信息,对用户来说可解释性不强。因此,本文提出了一种结合城市街区和签到数据的个性化兴趣区域推荐方法(CBCD),引入城市街区概念解决ROI边界模糊问题。首先,通过城市道路网生成城市街区,并将大规模签到数据映射到城市街区转换为区域签到;然后,基于区域签到对用户空间活动偏好和类别偏好分别进行个性化建模;最后,融合空间和类别活动偏好,向用户推荐其可能感兴趣的区域。在真实的数据集上进行试验,结果表明该方法具有较高的推荐精度,对用户感兴趣城市街区的挖掘和推荐具有一定的价值。     

移动轨迹聚类方法研究综述

轨迹数据是人类移动行为的表征,能够映射出人的出行模式和社会属性等信息。怎样有效挖掘轨迹数据蕴藏的人类活动规律一直是研究的热点。通过轨迹聚类发现行为相似的类簇,从而探究群体的移动模式是轨迹挖掘和深度应用常见的方法之一。本文首先根据轨迹数据的特点,将轨迹数据模型分为轨迹点模型和轨迹段模型,并据此定义相应的相似性度量：空间相似性度量和时空相似性度量;然后,对两类模型的聚类方法进行了综述,并总结不同聚类算法的优缺点,以期为不同应用选取聚类算法提供科学依据;最后对移动轨迹数据聚类方法研究的发展趋势进行了讨论。     

Evaluation of the quality of an online geocoding resource in the context of a large Brazilian city

Geocoding urban addresses usually requires the use of an underlying address database. Under the influence of the format defined for TIGER files decades ago, most address databases and street geocoding algorithms are organized around street centerlines, associating numbering ranges to thoroughfare segments between two street crossings. While this method has been successfully employed in the USA for a long time, its transposition to other countries may lead to increased errors. This article presents an evaluation of the centerline‐geocoding resources provided by Google Maps, as compared to the point‐geocoding method used in the city of Belo Horizonte, Brazil, which we took as a baseline. We generated a textual address for each point object found in the city's point‐based address database, and submitted it to the Google Maps geocoding API. We then compared the resulting coordinates with the ones recorded in Belo Horizonte's GIS. We demonstrate that the centerline segment interpolation method, employed by the online resources following the American practice, has problems that can considerably influence the quality of the geocoding outcome. Completeness and accuracy have been found to be irregular, especially within lower income areas. Such errors in online services can have a significant impact on geocoding efforts related to social applications, such as public health and education, since the online service can be faulty and error‐prone in the most socially demanding areas of the city. In the conclusion, we point out that a volunteered geographic information (VGI) approach can help with the enrichment and enhancement of current geocoding resources, and can possibly lead to their transformation into more reliable point‐based geocoding services.