Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems最新文献_第5页

GeoSpark: a cluster computing framework for processing large-scale spatial data GeoSpark:用于处理大规模空间数据的集群计算框架

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820860

Jia Yu, Jinxuan Wu, Mohamed Sarwat

{"title":"GeoSpark: a cluster computing framework for processing large-scale spatial data","authors":"Jia Yu, Jinxuan Wu, Mohamed Sarwat","doi":"10.1145/2820783.2820860","DOIUrl":"https://doi.org/10.1145/2820783.2820860","url":null,"abstract":"This paper introduces GeoSpark an in-memory cluster computing framework for processing large-scale spatial data. GeoSpark consists of three layers: Apache Spark Layer, Spatial RDD Layer and Spatial Query Processing Layer. Apache Spark Layer provides basic Spark functionalities that include loading / storing data to disk as well as regular RDD operations. Spatial RDD Layer consists of three novel Spatial Resilient Distributed Datasets (SRDDs) which extend regular Apache Spark RDDs to support geometrical and spatial objects. GeoSpark provides a geometrical operations library that accesses Spatial RDDs to perform basic geometrical operations (e.g., Overlap, Intersect). System users can leverage the newly defined SRDDs to effectively develop spatial data processing programs in Spark. The Spatial Query Processing Layer efficiently executes spatial query processing algorithms (e.g., Spatial Range, Join, KNN query) on SRDDs. GeoSpark also allows users to create a spatial index (e.g., R-tree, Quad-tree) that boosts spatial data processing performance in each SRDD partition. Preliminary experiments show that GeoSpark achieves better run time performance than its Hadoop-based counterparts (e.g., SpatialHadoop).","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134050776","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: 338

Optimal mobile facility localization 最优移动设施定位

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820862

A. K. M. M. R. Khan, L. Kulik, E. Tanin, T. Hashem

引用次数: 3

Video route 视频的路线

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820793

Tobias Emrich, Olivia Hofer, A. Kolb, Johannes Niedermayer, Nepumuk Seiler, Michael Weiler

引用次数: 1

Designing an on-line ride-sharing system 设计一个在线拼车系统

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820850

Blerim Cici, A. Markopoulou, Nikolaos Laoutaris

{"title":"Designing an on-line ride-sharing system","authors":"Blerim Cici, A. Markopoulou, Nikolaos Laoutaris","doi":"10.1145/2820783.2820850","DOIUrl":"https://doi.org/10.1145/2820783.2820850","url":null,"abstract":"Ride-sharing systems have the potential to match travelers with similar itineraries and time schedules, and to bring significant benefits to individual users and the city as a whole. However, this is a challenging task, since users' requests are not known in advance and they become available a few minutes before departure. In this paper, we design an online ride sharing system, where drivers and passengers send their requests for a ride in advance, possibly on a short notice. Our design is efficient and optimal. This is achieved by dividing the system into two components: the constraint satisfier and the matching module. The constraint satisfier takes as input the spatio-temporal constraints of drivers and passengers and provides feasible (driver, passenger) pairs in real time, and the matching module takes as input the feasible pairs and provides a maximum cardinality matching of drivers and passengers. Our preliminary evaluation shows that the constraint satisfier can resolve the most expensive queries (matching of passenger to en-route drivers) in 2 seconds (on average), while the matching module can achieve a matching ratio of 78% when the offline upper-bound is 80%.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125904168","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

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems 第23届SIGSPATIAL国际地理信息系统进展会议论文集

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783

Mohamed H. Ali, Y. Huang, Michael Gertz, M. Renz, Jagan Sankaranarayanan

引用次数: 3

Querying historical maps as a unified, structured, and linked spatiotemporal source: vision paper 查询历史地图作为一个统一的，结构化的，和链接的时空来源:视觉论文

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820887

Yao-Yi Chiang

{"title":"Querying historical maps as a unified, structured, and linked spatiotemporal source: vision paper","authors":"Yao-Yi Chiang","doi":"10.1145/2820783.2820887","DOIUrl":"https://doi.org/10.1145/2820783.2820887","url":null,"abstract":"Historical spatiotemporal datasets are important for a variety of studies such as cancer and environmental epidemiology, urbanization, and landscape ecology. However, existing data sources typically contain only contemporary datasets. Historical maps hold a great deal of detailed geographic information at various times in the past. Yet, finding relevant maps is difficult and the map content are not machine-readable. I envision a map processing, modeling, linking, and publishing framework that allows querying historical map collections as a unified and structured spatiotemporal source in which individual geographic phenomena (extracted from maps) are modeled with semantic descriptions and linked to other data sources (e.g., DBpedia). This framework will make it possible to efficiently study historical spatiotemporal datasets on a large scale. Realizing such a framework poses significant research challenges in multiple fields in computer science including digital map processing, data integration, and the Semantic Web technologies, and other disciplines such as spatial, earth, social, and health sciences. Tackling these challenges will not only advance research in computer science but also present a unique opportunity for interdisciplinary research.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127263948","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

MigrO: a plug-in for the analysis of individual mobility behavior based on the stay region model MigrO:基于停留区域模型分析个人移动行为的插件

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820794

M. Damiani, H. Issa, Giuseppe Fotino, F. Hachem, N. Ranc, F. Cagnacci

引用次数: 7

Find the butterfly: a social media based arterial incidents detection and causality analysis system 寻找蝴蝶:基于社交媒体的动脉事件检测和因果分析系统

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820797

Kaiqun Fu, Weisheng Zhong, Chang-Tien Lu, Arnold P. Boedihardjo

{"title":"Find the butterfly: a social media based arterial incidents detection and causality analysis system","authors":"Kaiqun Fu, Weisheng Zhong, Chang-Tien Lu, Arnold P. Boedihardjo","doi":"10.1145/2820783.2820797","DOIUrl":"https://doi.org/10.1145/2820783.2820797","url":null,"abstract":"Traditional statistical analysis on speed, volume, and occupancy has dominated the field of Arterial Incident Management Study (AIMS). However, few previous works have focused on investigating into the causality of the incidents. In this paper, we present ButterFly, a social media based arterial incident detection and analysis system. The proposed system is dedicated to identify the traffic incident from a novel perspective and discover causalities between traffic incidents. The main functionalities of the proposed system include: 1) Traffic incident detection based on userinput social media contents, 2) Transportation incidents storyline generation, and 3) Traffic incidents causalities analysis and visualization. We demonstrate the system by considering the Washington DC area as our experimental environment. ButterFly is targeted to provide effective and convenient real-time and historical traffic incidents analysis interfaces for transportation management agencies and academies. Our proposed system, integrated with multiple social media resources, can greatly broaden the visions for traffic incidents analysis.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126314031","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: 3

Towards distributed convoy pattern mining 面向分布式护航模式挖掘

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820840

F. Orakzai, T. Devogele, T. Calders

引用次数: 10

Detecting urban black holes based on human mobility data 基于人类移动数据探测城市黑洞

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2015-11-03 DOI: 10.1145/2820783.2820811

Liang Hong, Yu Zheng, Duncan Yung, Jingbo Shang, Lei Zou

{"title":"Detecting urban black holes based on human mobility data","authors":"Liang Hong, Yu Zheng, Duncan Yung, Jingbo Shang, Lei Zou","doi":"10.1145/2820783.2820811","DOIUrl":"https://doi.org/10.1145/2820783.2820811","url":null,"abstract":"Many types of human mobility data, such as flows of taxicabs, card swiping data of subways, bike trip data and Call Details Records (CDR), can be modeled by a Spatio-Temporal Graph (STG). STG is a directed graph in which vertices and edges are associated with spatio-temporal properties (e.g. the traffic flow on a road and the geospatial location of an intersection). In this paper, we instantly detect interesting phenomena, entitled black holes and volcanos, from an STG. Specifically, a black hole is a subgraph (of an STG) that has the overall inflow greater than the overall outflow by a threshold, while a volcano is a subgraph with the overall outflow greater than the overall inflow by a threshold (detecting volcanos from an STG is proved to be equivalent to the detection of black holes). The online detection of black holes/volcanos can timely reflect anomalous events, such as disasters, catastrophic accidents, and therefore help keep public safety. The patterns of black holes/volcanos and the relations between them reveal human mobility patterns in a city, thus help formulate a better city planning or improve a system's operation efficiency. Based on a well-designed STG index, we propose a two-step black hole detection algorithm: The first step identifies a set of candidate grid cells to start from; the second step expands an initial edge in a candidate cell to a black hole and prunes other candidate cells after a black hole is detected. Then, we adapt this detection algorithm to a continuous black hole detection scenario. We evaluate our method based on Beijing taxicab data and the bike trip data in New York, finding urban anomalies and human mobility patterns.","PeriodicalId":241302,"journal":{"name":"Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121122342","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: 74