International Conference and Exhibition on Computing for Geospatial Research & Application最新文献_第2页

Exploring multivariate spatio-temporal change in climate data using image analysis techniques 利用图像分析技术探索气候数据的多变量时空变化

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345333

M. P. McGuire, A. Gangopadhyay, V. Janeja

{"title":"Exploring multivariate spatio-temporal change in climate data using image analysis techniques","authors":"M. P. McGuire, A. Gangopadhyay, V. Janeja","doi":"10.1145/2345316.2345333","DOIUrl":"https://doi.org/10.1145/2345316.2345333","url":null,"abstract":"Spatio-temporal data from earth observation systems and models are increasing at astronomical rates in the climate domain. This results in a massive dataset that is increasingly difficult to navigate to find interesting time periods where the spatial pattern of a process changes. The ability to navigate to such areas can lead to new knowledge about the factors that contribute to a spatio-temporal process. This paper proposes a method to automatically characterize multi-variate spatio-temporal datasets using basic image processing techniques and an efficient distance measure. The approach uses a measure of local image entropy combined with edge detection to find naturally occurring boundaries in the dataset. Then a distance measure is used to track the change in these boundaries over time. The resulting measure of spatio-temporal change can be used to explore spatio-temporal datasets to find new relationships between the spatial pattern of variables over time. Experiments were performed on a real-world climate dataset and the results were promising in that new patterns emerged and interesting relationships between variables were found.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129656944","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

LiDAR data management pipeline; from spatial database population to web-application visualization 激光雷达数据管理管道;从空间数据库填充到web应用程序可视化

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345336

P. Lewis, C. McElhinney, T. McCarthy

{"title":"LiDAR data management pipeline; from spatial database population to web-application visualization","authors":"P. Lewis, C. McElhinney, T. McCarthy","doi":"10.1145/2345316.2345336","DOIUrl":"https://doi.org/10.1145/2345316.2345336","url":null,"abstract":"While the existence of very large and scalable Database Management Systems (DBMSs) is well recognized, it is the usage and extension of these technologies to managing spatial data that has seen increasing amounts of research work in recent years. A focused area of this research work involves the handling of very high resolution Light Detection and Ranging (LiDAR) data. While LiDAR has many real world applications, it is usually the purview of organizations interested in capturing and monitoring our environment where it has become pervasive. In many of these cases, it has now become the de facto minimum standard expected when a need to acquire very detailed 3D spatial data is required. However, significant challenges exist when working with these data sources, from data storage to feature extraction through to data segmentation all presenting challenges relating to the very large volumes of data that exist. In this paper, we present the complete LiDAR data pipeline as managed in our spatial database framework. This involves three distinct sections, populating the database, building a spatial hierarchy that describes the available data sources, and spatially segmenting data based on user requirements which generates a visualization of these data in a WebGL enabled web-application viewer. All work presented is in an experimental results context where we show how this approach is runtime efficient given the very large volumes of LiDAR data that are being managed.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128489303","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

ArchaeoSTOR map: publishing archaeological geodata on the web ArchaeoSTOR地图:在网络上发布考古地理数据

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345355

Yuma Matsui, Aaron Gidding, T. Levy, F. Kuester, T. DeFanti

引用次数: 4

CiVicinity events: pairing geolocation tools with a community calendar CiVicinity events:将地理定位工具与社区日历配对

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345334

Blaine Hoffman, Harold R. Robinson, Keith Han, John Millar Carroll

引用次数: 17

On clusterization of "big data" streams 论“大数据”流的集群化

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345320

S. Berkovich, Duoduo Liao

{"title":"On clusterization of \"big data\" streams","authors":"S. Berkovich, Duoduo Liao","doi":"10.1145/2345316.2345320","DOIUrl":"https://doi.org/10.1145/2345316.2345320","url":null,"abstract":"Big Data refers to the rising flood of digital data from many different sources, including the sensors, digitizers, scanners, mobile phones, cameras, software-based tools, internet, and so on. \"Big\" and \"diverse\" are two important characteristics of Big Data. The diversity of the Big Data, such as text, geometry, image, video, or sound, also increases difficulties of big data processing.\u0000 Coping with the \"Big Data\" problems requires a radical change in the philosophy of the organization of information processing. Primarily, the Big Data approach has to modify the underlying computational model in order to manage the uncertainty in the access to information items in a huge nebulous environment. As a result, the produced outcomes are directly influenced only by some active part of all information items, while the rest of the available information items just indirectly affect the choice of the active part. An analogous functionality exhibits the organization of the brain featuring the unconsciousness, and a characteristic similarity shows the retrieval process in Google.\u0000 In this talk, we introduce a novel method for on-the-fly clusterization of amorphous data from diverse sources. The devised construction is based on the previously developed FuzzyFind Dictionary reversing the error-correction scheme of Golay Code. This clusterization involves processing of intensive continuous data streams that can be effectively implemented using multi-core pipelining with forced interrupts. The suggested clusterization is especially suitable for the Big Data computational model as it materializes the requirement of purposeful selection of information items in unsteady framework of cloud computing and stream processing. Furthermore, the uncertainties in relation to the considered method of clusterization are moderated due to the idea of the bounded rationality, an approach that does not require a complete exact knowledge for sensible decision-making.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128930033","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: 15

MIMIC: Mobile mapping point density calculator MIMIC:移动地图点密度计算器

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345335

C. Cahalane, T. McCarthy, C. McElhinney

{"title":"MIMIC: Mobile mapping point density calculator","authors":"C. Cahalane, T. McCarthy, C. McElhinney","doi":"10.1145/2345316.2345335","DOIUrl":"https://doi.org/10.1145/2345316.2345335","url":null,"abstract":"The current generation of Mobile Mapping Systems (MMSs) capture increasingly larger amounts of data in a short time frame. Due to the relative novelty of this technology there is no concrete understanding of the point density that different hardware configurations and operating parameters will exhibit on objects at specific distances. Depending on the project requirements, obtaining the required point density impacts on survey time, processing time, data storage and is the underlying limit of automated algorithms. A limited understanding of the capabilities of these systems means that defining point density in project specifications is a complicated process. We are in the process of developing a method for determining the quantitative resolution of point clouds collected by a MMS with respect to known objects at specified distances. We have previously demonstrated the capabilities of our system for calculating point spacing, profile angle and profile spacing individually. Each of these elements are a major factor in calculating point density on arbitrary objects, such as road signs, poles or buildings -all important features in asset management surveys. This paper will introduce the current version of the MobIle Mapping point densIty Calculator (MIMIC), MIMIC's visualisation module and finally discuss the methods employed to validate our work.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114523267","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

Fast k-clustering queries on embeddings of road networks 道路网络嵌入的快速k聚类查询

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345331

James McClain, Piyush Kumar

引用次数: 2

Wavelet-based automated river network generalization 基于小波的河网自动泛化

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345332

M. Gutman, C. Weaver

{"title":"Wavelet-based automated river network generalization","authors":"M. Gutman, C. Weaver","doi":"10.1145/2345316.2345332","DOIUrl":"https://doi.org/10.1145/2345316.2345332","url":null,"abstract":"We have created an interactive map that can smoothly zoom to any region. The core of our system utilizes wavelets to achieve this effect. The system is implemented to view hydrographic flowline data, such as in the USGS National Hydrography Dataset (NHD). The map demonstrates that a wavelet-based approach is well suited for basic generalization operations. It provides smoothing and pruning that is continuously dependent on map scale.\u0000 The method is applied to the Vermont river network, with the goal of creating an interactive map visualization. The process involves removing cycles from the network, prioritizing the segments according to their Strahler numbers, and extracting tributaries. Then each tributary is decomposed into wavelet details.\u0000 When the user requests a map of a region B, the window size infers the scale s. Functions ε(s) and σ(s) determine the accuracy and the pruning level. The tributaries that are visible in B are synthesized to the required accuracy ε(s) and displayed according to the pruning function σ(s). In our system, the pruning is designed to be continuous with respect to the scale.\u0000 Our implementation shows that the interactive map renders views in subsecond time. We have determined experimentally that the FBI (9--7) biorthogonal wavelet family provides the best compromise between quality of approximation and computation time.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126325196","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

Real-time 3-D mapping for robotic applications 机器人应用的实时三维绘图

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345353

William Smith, Bingcai Zhang

引用次数: 3

Transport and dispersion simulation in downtown Oklahoma City and New York City 俄克拉荷马城和纽约市市中心的交通和分散模拟

International Conference and Exhibition on Computing for Geospatial Research & Application Pub Date : 2012-07-01 DOI: 10.1145/2345316.2345366

F. Camelli, Jyh-Ming Lien, David W. S. Wong

{"title":"Transport and dispersion simulation in downtown Oklahoma City and New York City","authors":"F. Camelli, Jyh-Ming Lien, David W. S. Wong","doi":"10.1145/2345316.2345366","DOIUrl":"https://doi.org/10.1145/2345316.2345366","url":null,"abstract":"In this video, we showcase two atmospheric dispersion simulations in an Oklahoma City dataset and a New York City (NYC) dataset. These simulations are created using a robust and efficient framework that generates seamless 3D architectural models from overlapping 2D footprints. These footprints with elevation and height information are commonly used to depict various components of buildings in GIS software such as ESRI ArcGIS and urban model synthesis methods, and usually contain small, sharp, and various (nearly) degenerate artifacts due to machine and human errors. In the first part of the video showing a simulation in Oklahoma City, the location is south of the public library in an area where there is a building currently. Two iso-surfaces of 10-4 and 10-5 ppm are shown in green and the brown clouds. The inflow is a westerly wind with a wind speed of 5 m/s at 10 meters above ground level. In the second part of the video showing a simulation in NYC, the location is the Financial District, Manhattan. The simulation assumed a boundary condition for the inflow of a logarithmic profile of 2 m/s with a velocity at 10 meters from the ground. An iso-surface of 10-5 ppm is shown. The final volume mesh produce contains 333 million tetrahedra, and 59 million points. The total time of the NYC simulation, including the initialization time and dispersion, took approximately two days on a high performance computing system running 2048 cores in a CRAY XK6 nodes. In both simulations, the release is continuous.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127405498","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