Proceedings of the 28th International Conference on Advances in Geographic Information Systems最新文献_第6页

TrioStat

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422220

Anas Daghistani, Walid G. Aref, Arif Ghafoor

{"title":"TrioStat","authors":"Anas Daghistani, Walid G. Aref, Arif Ghafoor","doi":"10.1145/3397536.3422220","DOIUrl":"https://doi.org/10.1145/3397536.3422220","url":null,"abstract":"The wide spread of GPS-enabled devices and the Internet of Things (IoT) has increased the amount of spatial data being generated every second. The current scale of spatial data cannot be handled using centralized systems. This has led to the development of distributed spatial data streaming systems that scale to process in real-time large amounts of streamed spatial data. The performance of distributed streaming systems relies on how even the workload is distributed among their machines. However, it is challenging to estimate the workload of each machine because spatial data and query streams are skewed and rapidly change with time and users' interests. Moreover, a distributed spatial streaming system often does not maintain a global system workload state because it requires high network and processing overheads to be collected from the machines in the system. This paper introduces TrioStat; an online workload estimation technique that relies on a probabilistic model for estimating the workload of partitions and machines in a distributed spatial data streaming system. It is infeasible to collect and exchange statistics with a centralized unit because it requires high network overhead. Instead, TrioStat uses a decentralised technique to collect and maintain the required statistics in real-time locally in each machine. TrioStat enables distributed spatial data streaming systems to compare the workloads of machines as well as the workloads of data partitions. TrioStat requires minimal network and storage overhead. Moreover, the required storage is distributed across the system's machines.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126232464","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: 0

A Time-Windowed Data Structure for Spatial Density Maps 空间密度图的时间窗数据结构

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422242

A. Bonerath, Benjamin Niedermann, J. Diederich, Yannick Orgeig, Johannes Oehrlein, J. Haunert

{"title":"A Time-Windowed Data Structure for Spatial Density Maps","authors":"A. Bonerath, Benjamin Niedermann, J. Diederich, Yannick Orgeig, Johannes Oehrlein, J. Haunert","doi":"10.1145/3397536.3422242","DOIUrl":"https://doi.org/10.1145/3397536.3422242","url":null,"abstract":"The visualization of spatio-temporal data helps researchers understand global processes such as animal migration. In particular, interactively restricting the data to different time windows reveals new insights into the short-term and long-term changes of the research data. Inspired by this use case, we consider the visualization of point data annotated with time stamps. We pick up classical, grid-based density maps as the underlying visualization technique and enhance them with an efficient data structure for arbitrarily specified time-window queries. The running time of the queries is logarithmic in the total number of points and linear in the number of actually colored cells. In experiments on real-world data we show that the data structure answers time-window queries within milliseconds, which supports the interactive exploration of large point sets. Further, the data structure can be used to visualize additional decision problems, e.g., it can answer whether the sum or maximum of additional weights given with the points exceed a certain threshold. We have defined the data structure general enough to also support multiple thresholds expressed by different colors.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114323660","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

Large-Scale Geospatial Planning of Wireless Backhaul Links 无线回程链路的大规模地理空间规划

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422256

Philip E. Brown, Krystian Czapiga, Arun Jotshi, Y. Kanza, Velin Kounev, Poornima Suresh

引用次数: 5

Grab-Posisi-L: A Labelled GPS Trajectory Dataset for Map Matching in Southeast Asia Grab-Posisi-L:用于东南亚地图匹配的标记GPS轨迹数据集

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422218

Zhengmin Xu, Yifang Yin, Chengcheng Dai, Xiaocheng Huang, Robinson Kudali, Jinal Foflia, Guanfeng Wang, Roger Zimmermann

{"title":"Grab-Posisi-L: A Labelled GPS Trajectory Dataset for Map Matching in Southeast Asia","authors":"Zhengmin Xu, Yifang Yin, Chengcheng Dai, Xiaocheng Huang, Robinson Kudali, Jinal Foflia, Guanfeng Wang, Roger Zimmermann","doi":"10.1145/3397536.3422218","DOIUrl":"https://doi.org/10.1145/3397536.3422218","url":null,"abstract":"Map matching has long been a fundamental yet challenging problem. However, there are currently only a few public small-scale map matching benchmark datasets. Both the GPS trajectories and the road network in the existing map matching datasets are represented by location only, which cannot support the development of data-driven and semantic-enriched map matching algorithms that have increasingly emerged in recent years. To bridge the gap, we present the first large-scale attribute-rich map matching benchmark dataset covering two cities in Southeast Asia (i.e., Singapore and Jakarta). Our GPS trajectories contain rich contextual information including the accuracy level, bearing, speed, and transport mode in addition to the latitude and longitude geo-coordinates. The underlying road network is a snapshot of the OpenStreetMap where roads are associated with rich attributes such as road type, speed limit, etc. To ensure the quality of our dataset, the annotation of the map-matched routes has been conducted by a team of professional map operators. Analysis on our dataset provides new insights into the challenges and opportunities in map matching algorithms.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117212683","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: 1

Efficient Filters for Geometric Intersection Computations using GPU 高效过滤器的几何交集计算使用GPU

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422264

Yiming Liu, S. Puri

{"title":"Efficient Filters for Geometric Intersection Computations using GPU","authors":"Yiming Liu, S. Puri","doi":"10.1145/3397536.3422264","DOIUrl":"https://doi.org/10.1145/3397536.3422264","url":null,"abstract":"Geometric intersection algorithms are fundamental in spatial analysis in Geographic Information System (GIS). Applying high performance computing to perform geometric intersection on huge amount of spatial data to get real-time results is necessary. Given two input geometries (polygon or polyline) of a candidate pair, we introduce a new two-step geospatial filter that first creates sketches of the geometries and uses it to detect workload and then refines the sketches by the common areas of sketches to decrease the overall computations in the refine phase. We call this filter PolySketch-based CMBR (PSCMBR) filter. We show the application of this filter in speeding-up line segment intersections (LSI) reporting task that is a basic computation in a variety of geospatial applications like polygon overlay and spatial join. We also developed a parallel PolySketch-based PNP filter to perform PNP tests on GPU which reduces computational workload in PNP tests. Finally, we integrated these new filters to the hierarchical filter and refinement (HiFiRe) system to solve geometric intersection problem. We have implemented the new filter and refine system on GPU using CUDA. The new filters introduced in this paper reduce more computational workload when compared to existing filters. As a result, we get on average 7.96X speedup compared to our prior version of HiFiRe system.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130349506","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: 5

Close Weighted Shortest Paths on 3D Terrain Surfaces 三维地形表面的接近加权最短路径

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422216

N. Tran, Michael J. Dinneen, S. Linz

{"title":"Close Weighted Shortest Paths on 3D Terrain Surfaces","authors":"N. Tran, Michael J. Dinneen, S. Linz","doi":"10.1145/3397536.3422216","DOIUrl":"https://doi.org/10.1145/3397536.3422216","url":null,"abstract":"This paper proposes an efficient method for the weighted region problem (WRP) on the surface of three-dimensional terrains. WRP is a classical path planning problem, asking for the minimum cost path between two given points crossing different regions in which each region is assigned a traversal cost per unit distance. Although WRP has been studied for decades, the exact solution for WRP, even in a two-dimensional environment, is unknown. Thus, the existing solutions for WRP are all approximations with decomposition-based and heuristic methods being the most widely-used in practice. However, when a very-close to optimal path is required, especially on real terrains with many regions, these approaches are not guaranteed or cannot return a satisfactory result in reasonable time. In this paper, we first present a new algorithm of finding a very-close optimal path, based on a user-defined parameter &dgr;, between two points, crossing the surface of a sequence of regions in 3D, using Snell's law of physical refraction. We then show how to combine this algorithm with one existing decomposition-based method to compute a close optimal path over the whole terrain. In addition to a theoretical analysis, with an extensive set of test cases, the practicality and feasibility of our method are confirmed by that, our method always runs faster and returns closer to optimal paths in comparison with the existing ones.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121396412","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

A Demonstration of Interactive Exploration of Big Geospatial Data on UCR-Star UCR-Star上大地理空间数据交互探索的演示

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422334

Saheli Ghosh, Akil Sevim, A. Eldawy

{"title":"A Demonstration of Interactive Exploration of Big Geospatial Data on UCR-Star","authors":"Saheli Ghosh, Akil Sevim, A. Eldawy","doi":"10.1145/3397536.3422334","DOIUrl":"https://doi.org/10.1145/3397536.3422334","url":null,"abstract":"The ever rising volume of geospatial data is undeniable. So is the need to explore and analyze these datasets. However, these datasets vary widely in their size, coverage, and accuracy. Therefore, users need to assess these aspects of the data to choose the right dataset to use in their analysis. Unfortunately, all the publicly available repositories for geospatial datasets provide a list of datasets with some information about them with no way to explore the datasets beforehand. Through this demonstration, we propose the repository, UCR-Star, that is capable of hosting hundreds of thousands of geospatial datasets that a user can explore visually to judge their quality before even downloading them. This demo provides a deeper dive into the core engine behind UCR-Star. It provides a web interface geared towards database researchers to understand how the index internally works. It provides a comparison interface where the attendees can see side-by-side how two versions of the system work with the ability to customize each of them separately. Finally, the interface reports the response time of the indexes for a quantitative comparison.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121741836","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

Urban Night Scenery Reconstruction by Day-night Registration and Synthesis 基于昼夜配准与合成的城市夜景重建

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422200

A. Dai, D. Meger

{"title":"Urban Night Scenery Reconstruction by Day-night Registration and Synthesis","authors":"A. Dai, D. Meger","doi":"10.1145/3397536.3422200","DOIUrl":"https://doi.org/10.1145/3397536.3422200","url":null,"abstract":"Although large-scale 3D reconstruction by photogrammetry has been well studied and applied, the reconstruction of night scenery in urban areas has not been thoroughly considered. At night, low-light conditions often cause the images to lack sharpness and high-dynamic range issue leads to saturation. The SFM reconstruction pipeline that works well in daylight is likely to recover only limited dense points of bright fragmented objects near artificial lighting. Here, we propose a novel solution based on registration and synthesis between the night-time reconstruction and that of the same region in daytime. A registration pipeline is developed for conformal matching of the day and night point clouds. For the coarse registration step, we use detected plane features to search and match 4-plane congruent sets. For the fine registration step, we consider the positions of windows, a commonly-occurring object cue in urban building scenes as markers for accurate positioning. This leads to final registration error less than 0.2 degrees in rotation, and 0.2% in scale and translation. Finally, we synthesize the daytime textured model and the night point clouds to produce vivid visual effects of urban night scenery.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117136277","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: 0

staty

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422342

H. Bast, P. Brosi, Markus Näther

引用次数: 2

CPM CPM

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422341

Ying Hu, Jinping Jia, Bin Zhao, G. Ji, Zhaoyuan Yu, Xintao Liu

引用次数: 1