Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems最新文献_第9页

LOCAl: a personalized cache mechanism for location-based social networks LOCAl:基于位置的社交网络的个性化缓存机制

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996981

Dimitrios Tomaras, Ioannis Boutsis, V. Kalogeraki, D. Gunopulos

引用次数: 2

BigGIS: a continuous refinement approach to master heterogeneity and uncertainty in spatio-temporal big data (vision paper) BigGIS:掌握时空大数据异质性和不确定性的持续细化方法(视觉论文)

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996931

Patrick Wiener, M. Stein, Daniel Seebacher, Julian Bruns, Matthias T. Frank, V. Simko, Stefan Zander, Jens Nimis

{"title":"BigGIS: a continuous refinement approach to master heterogeneity and uncertainty in spatio-temporal big data (vision paper)","authors":"Patrick Wiener, M. Stein, Daniel Seebacher, Julian Bruns, Matthias T. Frank, V. Simko, Stefan Zander, Jens Nimis","doi":"10.1145/2996913.2996931","DOIUrl":"https://doi.org/10.1145/2996913.2996931","url":null,"abstract":"Geographic information systems (GIS) are important for decision support based on spatial data. Due to technical and economical progress an ever increasing number of data sources are available leading to a rapidly growing fast and unreliable amount of data that can be beneficial (1) in the approximation of multivariate and causal predictions of future values as well as (2) in robust and proactive decision-making processes. However, today's GIS are not designed for such big data demands and require new methodologies to effectively model uncertainty and generate meaningful knowledge. As a consequence, we introduce BigGIS, a predictive and prescriptive spatio-temporal analytics platform, that symbiotically combines big data analytics, semantic web technologies and visual analytics methodologies. We present a novel continuous refinement model and show future challenges as an intermediate result of a collaborative research project into big data methodologies for spatio-temporal analysis and design for a big data enabled GIS.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74955947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Particle filter for real-time human mobility prediction following unprecedented disaster 基于粒子滤波的空前灾难后人类流动性实时预测

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2997000

Akihito Sudo, Takehiro Kashiyama, T. Yabe, H. Kanasugi, Xuan Song, T. Higuchi, S. Nakano, Masaya M. Saito, Y. Sekimoto

{"title":"Particle filter for real-time human mobility prediction following unprecedented disaster","authors":"Akihito Sudo, Takehiro Kashiyama, T. Yabe, H. Kanasugi, Xuan Song, T. Higuchi, S. Nakano, Masaya M. Saito, Y. Sekimoto","doi":"10.1145/2996913.2997000","DOIUrl":"https://doi.org/10.1145/2996913.2997000","url":null,"abstract":"Real-time estimation of human mobility following a massive disaster will play a crucial role in disaster relief. Because human mobility in massive disasters is quite different from their usual mobility, real-time human location data is necessary for precise estimation. Due to privacy concerns, real-time data is anonymized and a popular form of anonymization is population distribution. In this paper, we aim to estimate human mobility following an unprecedented disaster using such population distribution data. To overcome technical obstacles including high dimensionality, we propose novel particle filter by devising proposal distribution. Our proposal distribution provides states considering both prediction model and acquired observation. Therefore, particles maintain high likelihood. In the experiments, our methods realized more accurate estimation than the baselines, and its estimated mobility was consistent with the survey researches. The computational cost is significantly low enough for real-time operations. The GPS data collected on the day of the Great East Japan Earthquake is used for the evaluation.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73109099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

On-demand aggregation of gridded data over user-specified spatio-temporal domains 在用户指定的时空域中按需聚合网格数据

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996944

Joel E. Tosado, Gheorghi Guzun, G. Canahuate, R. Mantilla

{"title":"On-demand aggregation of gridded data over user-specified spatio-temporal domains","authors":"Joel E. Tosado, Gheorghi Guzun, G. Canahuate, R. Mantilla","doi":"10.1145/2996913.2996944","DOIUrl":"https://doi.org/10.1145/2996913.2996944","url":null,"abstract":"The advent of satellite imagery, remote sensing products, and global scale numerical climate models over the last two decades has created an explosion of available gridded environmental data. These space-time explicit datasets are produced and distributed using different spatial and temporal resolutions. Current approaches for comparing two different products generally involve offline pre-computation of aggregations to a common spatio-temporal resolution. This limits the user's ability to interactively compare different data products or transform data products into the required input resolution for modeling. The goal of this work is to enable end users to perform on- the-fly transformations of gridded data products to different spatio-temporal resolutions to facilitate exploratory analyses and comparison of different data products. In this paper we propose a compressed columnar indexing and query processing to support online aggregation of gridded data over user-specified spatio-temporal domains. Our approach requires up to two orders of magnitude less space than more traditional indexing while maintaining competitive execution time for different aggregations in time and space.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79626001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Progressive streaming and massive rendering of 3D city models on web-based virtual globe 基于web的虚拟地球上3D城市模型的渐进式流媒体和大规模渲染

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2997008

Quoc-Dinh Nguyen, M. Brédif, Didier Richard, N. Paparoditis

{"title":"Progressive streaming and massive rendering of 3D city models on web-based virtual globe","authors":"Quoc-Dinh Nguyen, M. Brédif, Didier Richard, N. Paparoditis","doi":"10.1145/2996913.2997008","DOIUrl":"https://doi.org/10.1145/2996913.2997008","url":null,"abstract":"The need for the real-time interactive co-visualization of 3D urban environments on a Web-based virtual Globe arises naturally in GIS but it still remains challenging due to the complexity of city models and their huge data sizes which largely overload the computational power and memory capacity of client devices. Especially on the Web, the visualization of city models makes their rendering not real-time because of the lack of content adaptation and progressive data transmission. This paper presents technical solutions for the co-visualization of massive city models in a Web-based virtual globe, allowing navigation over 3D cities on the globe in real-time. The volume of 3D city data, such as building data, does not allow us to render them directly, nor to keep them in the main memory. We propose to use not only a hierarchical presentation of geo-spatial data to create a chunk-based multiple resolution data structure which reduces complexity of the geometry being rendered; but also a view dependent algorithm so that only small subsets of 3D city models are streamed progressively in real-time and kept in client memory to contribute efficiently to the rendered image. Experimental results show that we can navigate over 3D cities on the Globe in real-time.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91192144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Predicting interactions and contexts with context trees 使用上下文树预测交互和上下文

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996993

Alasdair Thomason, N. Griffiths, Victor Sanchez

引用次数: 2

Atlas: on the expression of spatial-keyword group queries using extended relational constructs Atlas:关于使用扩展关系结构的空间关键字组查询的表达式

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996987

Ahmed R. Mahmood, Walid G. Aref, Ahmed M. Aly, Mingjie Tang

{"title":"Atlas: on the expression of spatial-keyword group queries using extended relational constructs","authors":"Ahmed R. Mahmood, Walid G. Aref, Ahmed M. Aly, Mingjie Tang","doi":"10.1145/2996913.2996987","DOIUrl":"https://doi.org/10.1145/2996913.2996987","url":null,"abstract":"The popularity of GPS-enabled cellular devices introduced numerous applications, e.g., social networks, micro-blogs, and crowd-powered reviews. These applications produce large amounts of geo-tagged textual data that need to be processed and queried. Nowadays, many complex spatio-textual operators and their matching complex indexing structures are being proposed in the literature to process this spatio-textual data. For example, there exist several complex variations of the spatio-textual group queries that retrieve groups of objects that collectively satisfy certain spatial and textual criteria. However, having complex operators is against the spirit of SQL and relational algebra. In contrast to these complex spatio-textual operators, in relational algebra, simple relational operators are offered, e.g., relational selects, projects, order by, and group by, that are composable to form more complex queries. In this paper, we introduce Atlas, an SQL extension to express complex spatial-keyword group queries. Atlas follows the philosophy of SQL and relational algebra in that it uses simple declarative spatial and textual building-block operators and predicates to extend SQL. Not only that Atlas can represent spatio-textual group queries from the literature, but also it can compose other important queries, e.g., retrieve spatio-textual groups from subsets of object datasets where the selected subset satisfies user-defined relational predicates and the groups of close-by objects contain miss-spelled keywords. We demonstrate that Atlas is able to represent a wide range of spatial-keyword queries that existing indexes and algorithms would not be able to address. The building- block paradigm adopted by Atlas creates room for query optimization, where multiple query execution plans can be formed.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84832545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Scalable estimation of precision maps in a MapReduce framework MapReduce框架中高精度地图的可伸缩估计

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-09-24 DOI: 10.1145/2996913.2996990

C. Brenner

{"title":"Scalable estimation of precision maps in a MapReduce framework","authors":"C. Brenner","doi":"10.1145/2996913.2996990","DOIUrl":"https://doi.org/10.1145/2996913.2996990","url":null,"abstract":"This paper presents a large-scale strip adjustment method for LiDAR mobile mapping data, yielding highly precise maps. It uses several concepts to achieve scalability. First, an efficient graph-based pre-segmentation is used, which directly operates on LiDAR scan strip data, rather than on point clouds. Second, observation equations are obtained from a dense matching, which is formulated in terms of an estimation of a latent map. As a result of this formulation, the number of observation equations is not quadratic, but rather linear in the number of scan strips. Third, the dynamic Bayes network, which results from all observation and condition equations, is partitioned into two sub-networks. Consequently, the estimation matrices for all position and orientation corrections are linear instead of quadratic in the number of unknowns and can be solved very efficiently using an alternating least squares approach. It is shown how this approach can be mapped to a standard key/value MapReduce implementation, where each of the processing nodes operates independently on small chunks of data, leading to essentially linear scalability. Results are demonstrated for a dataset of one billion measured LiDAR points and 278,000 unknowns, leading to maps with a precision of a few millimeters.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85506635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

A topological algorithm for determining how road networks evolve over time 一种用于确定道路网络如何随时间演变的拓扑算法

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-09-23 DOI: 10.1145/2996913.2996976

M. Goodrich, Siddharth Gupta, Manuel R. Torres

引用次数: 1

Spatio-temporal sentiment hotspot detection using geotagged photos 基于地理标记照片的时空情感热点检测

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-09-21 DOI: 10.1145/2996913.2996978

Yi Zhu, S. Newsam

引用次数: 30