scholarly journals Interactive and Online Buffer-Overlay Analytics of Large-Scale Spatial Data

2019 ◽  
Vol 8 (1) ◽  
pp. 21 ◽  
Author(s):  
Mengyu Ma ◽  
Ye Wu ◽  
Luo Chen ◽  
Jun Li ◽  
Ning Jing
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Large Scale ◽  
Optimization Method ◽  
Spatial Index ◽  
Overlay Analysis ◽  
Analysis Model ◽  
Time Buffer ◽  
Real World Datasets ◽  
Processing Architecture

Buffer and overlay analysis are fundamental operations which are widely used in Geographic Information Systems (GIS) for resource allocation, land planning, and other relevant fields. Real-time buffer and overlay analysis for large-scale spatial data remains a challenging problem because the computational scales of conventional data-oriented methods expand rapidly with data volumes. In this paper, we present HiBO, a visualization-oriented buffer-overlay analysis model which is less sensitive to data volumes. In HiBO, the core task is to determine the value of pixels for display. Therefore, we introduce an efficient spatial-index-based buffer generation method and an effective set-transformation-based overlay optimization method. Moreover, we propose a fully optimized hybrid-parallel processing architecture to ensure the real-time capability of HiBO. Experiments on real-world datasets show that our approach is capable of handling ten-million-scale spatial data in real time. An online demonstration of HiBO is provided (http://www.higis.org.cn: 8080/hibo).

scholarly journals HiBuffer: Buffer Analysis of 10-Million-Scale Spatial Data in Real Time

2018 ◽  
Vol 7 (12) ◽  
pp. 467 ◽  
Author(s):  
Mengyu Ma ◽  
Ye Wu ◽  
Wenze Luo ◽  
Luo Chen ◽  
Jun Li ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Buffer Analysis ◽  
Data Volume ◽  
Time Buffer ◽  
Real World Datasets ◽  
Spatial Indexes

Buffer analysis, a fundamental function in a geographic information system (GIS), identifies areas by the surrounding geographic features within a given distance. Real-time buffer analysis for large-scale spatial data remains a challenging problem since the computational scales of conventional data-oriented methods expand rapidly with increasing data volume. In this paper, we introduce HiBuffer, a visualization-oriented model for real-time buffer analysis. An efficient buffer generation method is proposed which introduces spatial indexes and a corresponding query strategy. Buffer results are organized into a tile-pyramid structure to enable stepless zooming. Moreover, a fully optimized hybrid parallel processing architecture is proposed for the real-time buffer analysis of large-scale spatial data. Experiments using real-world datasets show that our approach can reduce computation time by up to several orders of magnitude while preserving superior visualization effects. Additional experiments were conducted to analyze the influence of spatial data density, buffer radius, and request rate on HiBuffer performance, and the results demonstrate the adaptability and stability of HiBuffer. The parallel scalability of HiBuffer was also tested, showing that HiBuffer achieves high performance of parallel acceleration. Experimental results verify that HiBuffer is capable of handling 10-million-scale data.

scholarly journals An Efficient Parallel Algorithm for Polygons Overlay Analysis

2019 ◽  
Vol 9 (22) ◽  
pp. 4857 ◽  
Author(s):  
Yuke Zhou ◽  
Shaohua Wang ◽  
Yong Guan
Keyword(s):  
Parallel Algorithm ◽  
Spatial Data ◽  
Large Scale ◽  
High Efficiency ◽  
Spatial Index ◽  
Overlay Analysis ◽  
Data Decomposition ◽  
Space Filling Curve ◽  
Index Decomposition ◽  
Filling Curve

Map overlay analysis is essential for geospatial analytics. Large scale spatial data pressing poses challenges for geospatial map overlay analytics. In this study, we propose an efficient parallel algorithm for polygons overlay analysis, including active-slave spatial index decomposition for intersection, multi-strategy Hilbert ordering decomposition, and parallel spatial union algorithm. Multi-strategy based spatial data decomposition mechanism is implemented, including parallel spatial data index, the Hilbert space-filling curve sort, and decomposition. The results of the experiments showed that the parallel algorithm for polygons overlay analysis achieves high efficiency.

scholarly journals Digital matter as interdisciplinary commodity

2017 ◽  
Vol 2 (3) ◽  
pp. 103
Author(s):  
Uwe Rieger
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Architectural Design ◽  
Large Scale ◽  
Mixed Reality ◽  
Digital Fabrication ◽  
Digital Information ◽  
Design Environment ◽  
Digital World ◽  
Starting Point

<p>With the current exponential growth in the sector of Spatial Data Technology and Mixed Reality display devises we experience an increasing overlap of the physical and digital world. Next to making data spatially visible the attempt is to connect digital information with physical properties. Over the past years a number of research institutions have been laying the ground for these developments. In contemporary architecture architectural design the dominant application of data technology is connected to graphical presentation, form finding and digital fabrication.<br />The <em>arc/sec Lab for Digital Spatial Operations </em>at the University of Auckland takes a further step. The Lab explores concepts for a new condition of buildings and urban patterns in which digital information is connected with spatial appearance and linked to material properties. The approach focuses on the step beyond digital re-presentation and digital fabrication, where data is re-connected to the multi-sensory human perceptions and physical skills. The work at the Lab is conducted in a cross disciplinary design environment and based on experiential investigations. The arc/sec Lab utilizes large-scale interactive installations as the driving vehicle for the exploration and communication of new dimensions in architectural space. The experiments are aiming to make data “touchable” and to demonstrate real time responsive environments. In parallel they are the starting point for both the development of practice oriented applications and speculation on how our cities and buildings might change in the future.<br />The article gives an overview of the current experiments being undertaken at the arc/sec Lab. It discusses how digital technologies allow for innovation between the disciplines by introducing real time adaptive behaviours to our build environment and it speculates on the type of spaces we can construct when <em>digital matter </em>is used as a new dynamic building material.</p>

scholarly journals ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

2016 ◽  
Vol 56 (1) ◽  
pp. 67 ◽  
Author(s):  
Amanda Prorok ◽  
M. Ani Hsieh ◽  
Vijay Kumar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Optimization Problem ◽  
Optimization Method ◽  
Transition Rates ◽  
Trait Distribution ◽  
Time Optimization ◽  
Heterogeneous Robots ◽  
Real Time Optimization ◽  
Optimal Set

We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

scholarly journals QOS MANAGEMENT IN REAL-TIME SPATIAL BIG DATA USING FEEDBACK CONTROL SCHEDULING

2015 ◽  
Vol II-3/W5 ◽  
pp. 243-248 ◽  
Author(s):  
S. Hamdi ◽  
E. Bouazizi ◽  
S. Faiz
Keyword(s):  
Big Data ◽  
Feedback Control ◽  
Real Time ◽  
Spatial Data ◽  
Large Scale ◽  
The Real ◽  
Remote Sensors ◽  
Spatial Big Data ◽  
Active Research ◽  
Access To Data

Geographic Information System (GIS) is a computer system designed to capture, store, manipulate, analyze, manage, and present all types of spatial data. Spatial data, whether captured through remote sensors or large scale simulations has always been big and heterogenous. The issue of real-time and heterogeneity have been extremely important for taking effective decision. Thus, heterogeneous real-time spatial data management has become a very active research domain. Existing research has principally focused on querying of real-time spatial data and their updates. But the unpredictability of access to data maintain the behavior of the real-time GIS unstable. In this paper, we propose the use of the real-time Spatial Big Data and we define a new architecture called FCSA-RTSBD (Feedback Control Scheduling Architecture for Real-Time Spatial Big Data). The main objectives of this architecture are the following: take in account the heterogeneity of data, guarantee the data freshness, enhance the deadline miss ratio even in the presence of conflicts and unpredictable workloads and finally satisfy the requirements of users by the improving of the quality of service (QoS).

scholarly journals Risk Analysis for Reservoir Real-Time Optimal Operation Using the Scenario Tree-Based Stochastic Optimization Method

Water ◽  
2018 ◽  
Vol 10 (5) ◽  
pp. 606 ◽  
Author(s):  
Yimeng Sun ◽  
Feilin Zhu ◽  
Juan Chen ◽  
Jinshu Li
Keyword(s):  
Risk Analysis ◽  
Stochastic Optimization ◽  
Real Time ◽  
Flood Control ◽  
Forecast Accuracy ◽  
Optimization Method ◽  
Optimal Operation ◽  
Scenario Tree ◽  
Analysis Model ◽  
Time Optimal

The inherent uncertainty of inflow forecasts hinders the reservoir real-time optimal operation. This paper proposes a risk analysis model for reservoir real-time optimal operation using the scenario tree-based stochastic optimization method. We quantify the probability distribution of inflow forecast uncertainty by developing the relationship between two forecast accuracy metrics and the standard deviation of relative forecast error. An inflow scenario tree is generated via Monte Carlo simulation to represent the uncertain inflow forecasts. We establish a scenario tree-based stochastic optimization model to explicitly incorporate inflow forecast uncertainty into the stochastic optimization process. We develop a risk analysis model based on the principle of maximum entropy (POME) to evaluate the uncertainty propagation process from flood forecasts to optimal operation. We apply the proposed methodology to a flood control system in the Daduhe River Basin, China. In addition, numerical experiments are carried out to investigate the effect of two different forecast accuracy metrics and different forecast accuracy levels on reservoir optimal flood control operation as well as risk analysis. The results indicate that the proposed methods can provide decision-makers with valuable risk information for guiding reservoir real-time optimal operation and enable risk-informed decisions to be made with higher reliabilities.

scholarly journals HiIndex: An Efficient Spatial Index for Rapid Visualization of Large-Scale Geographic Vector Data

2021 ◽  
Vol 10 (10) ◽  
pp. 647
Author(s):  
Zebang Liu ◽  
Luo Chen ◽  
Anran Yang ◽  
Mengyu Ma ◽  
Jingzhi Cao
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Information Science ◽  
Treatment Time ◽  
Spatial Index ◽  
Vector Data ◽  
Recursion Method ◽  
Tree Generation ◽  
Real Time Visualization ◽  
Pre Treatment

In the big data era, rapid visualization of large-scale vector data has become a serious challenge in Geographic Information Science (GIS). To fill the gap, we propose HiIndex, a spatial index that enables real-time and interactive visualization of large-scale vector data. HiIndex improves the state of the art with its low memory requirements, fast construction speed, and high visualization efficiency. In HiIndex, we present a tile-quadtree structure (TQ-tree) which divides the global geographic range based on the quadtree recursion method, and each node in the TQ-tree represents a specific and regular spatial range. In this paper, we propose a quick TQ-tree generation algorithm and an efficient visualization algorithm. Experiments show that the HiIndex is simple in structure, fast in construction, and less in memory occupation, and our approach can support interactive and real-time visualization of billion scale vector data with negligible pre-treatment time.

Design Application in Suspender Tensile Force of Tied-Arch Bridges Based on Inversion Optimization Method

2012 ◽  
Vol 226-228 ◽  
pp. 1586-1590
Author(s):  
Xue Xian Sun ◽  
Yong Wang ◽  
Feng Chen
Keyword(s):  
Large Scale ◽  
Tensile Force ◽  
Bending Moment ◽  
Optimization Method ◽  
Analysis Model ◽  
Moment Distribution ◽  
Analysis Scheme ◽  
Tensile Forces ◽  
Control Objective ◽  
Arch Bridges

Taking an actual tied-arch bridge project as the background, this thesis has a system static analysis by building up the finite element analysis model with Midas/civil, a large-scale FEM software, then establishes a mathematical optimization model for the back analysis to suspender tensile forces through two optimization schemes. Scheme one takes the reasonable bending moment distribution and minimum moment stain energy as the optimal control objective function to inverse analysis. Scheme two takes the bending moment distribution of dead load as the control objective of inversion optimization analysis, when the difference of the positive and negative absolute value is the minimum in the moment envelope under the load combination, which thinks about live load on the finished state. Through comparing the analysis results, the thesis demonstrates that the inversion optimization method could fulfill the requirement of factual project and be widely used for determining suspender tensile forces of tie-arch bridges.

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