Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

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Modeling and Implementation of Inter-Campuses Equipment Optimized Management Based on WebGIS

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.680.534 ◽

2013 ◽

Vol 680 ◽

pp. 534-539

Author(s):

Wei Feng Ma

Keyword(s):

Information Management ◽

Spatial Data ◽

Large Scale ◽

New Technology ◽

Rapid Expansion ◽

Mathematics Model ◽

Data Mapping ◽

Geographically Dispersed ◽

New Research ◽

Research Challenge

With the rapid expansion of the campus scale and the increasing of the geographically dispersed campus, how to adopt new theory, new method and new technology to realize the equipment optimized assignment and the information management is a new research challenge. It is the key to safeguard the national fund to use reasonably, and to speed up the development of education healthily. Through analyzing the domestic and foreign related research works, the paper proposed that it can take use of the spatial data expression and analysis with Geographic Information System (GIS) to realize the large-scale and inter-campuses equipment optimized assignment and information management. It discussed the mathematics model and the system architecture. Moreover, the paper described the key implementation technology in great detail such as spatial data mapping with MapInfo professional 9 and the development of WebGIS functions with MapXtreme. The results show that the solution is feasible and effective.

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A Research of Matching Algorithm and Strategy on Entity with Complex Area

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.209-211.252 ◽

2012 ◽

Vol 209-211 ◽

pp. 252-255

Author(s):

Li Guo ◽

Hai Ying Zheng ◽

Yong Hong Wang ◽

Bin Zhang

Keyword(s):

Spatial Data ◽

Large Scale ◽

Data Matching ◽

Large Scale Data ◽

Polygon Area ◽

Spatial Data Integration ◽

One And Many ◽

Complex Polygon ◽

Scale Data ◽

Matching Relation

Data matching technology is a key technology for spatial data integration and fusion. This paper represents a solution to the complex polygon area, defines the area overlapped rate in the aspect of geometric measure, presents the data matching idea based on area overlapped rate .Then, this paper discusses and realizes the data matching relation of area elements including one to one , many to one and many to many. At last, region targets are set as the study object, large scale data are taken for example. We draw the conclusion: this algorithm is efficient.

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UAV-Enabled Spatial Data Sampling in Large-Scale IoT Systems Using Denoising Autoencoder Neural Network

IEEE Internet of Things Journal ◽

10.1109/jiot.2018.2876695 ◽

2019 ◽

Vol 6 (2) ◽

pp. 1856-1865 ◽

Cited By ~ 14

Author(s):

Tianqi Yu ◽

Xianbin Wang ◽

Abdallah Shami

Keyword(s):

Neural Network ◽

Spatial Data ◽

Large Scale ◽

Data Sampling ◽

Denoising Autoencoder

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

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7120467 ◽

2018 ◽

Vol 7 (12) ◽

pp. 467 ◽

Cited By ~ 3

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.

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Resource frontiers and agglomeration economies: The varied logics of transnational land-based investing in Southern and Eastern Africa

AMBIO ◽

10.1007/s13280-021-01682-z ◽

2022 ◽

Author(s):

Dilini Abeygunawardane ◽

Angela Kronenburg García ◽

Zhanli Sun ◽

Daniel Müller ◽

Almeida Sitoe ◽

...

Keyword(s):

Spatial Data ◽

Large Scale ◽

Agglomeration Economies ◽

Sub Saharan Africa ◽

Eastern Africa ◽

Track Record ◽

Level Data ◽

Forestry Investments ◽

Sub Saharan ◽

Investment Location

AbstractActor-level data on large-scale commercial agriculture in Sub-Saharan Africa are scarce. The peculiar choice of transnational investing in African land has, therefore, been subject to conjecture. Addressing this gap, we reconstructed the underlying logics of investment location choices in a Bayesian network, using firm- and actor-level interview and spatial data from 37 transnational agriculture and forestry investments across 121 sites in Mozambique, Zambia, Tanzania, and Ethiopia. We distinguish four investment locations across gradients of resource frontiers and agglomeration economies to derive the preferred locations of different investors with varied skillsets and market reach (i.e., track record). In contrast to newcomers, investors with extensive track records are more likely to expand the land use frontier, but they are also likely to survive the high transaction costs of the pre-commercial frontier. We highlight key comparative advantages of Southern and Eastern African frontiers and map the most probable categories of investment locations.

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Olomouc - Possibilities of Geovisualization of the Historical City

Geoinformatics FCE CTU ◽

10.14311/gi.6.33 ◽

2011 ◽

Vol 6 ◽

pp. 267-274

Author(s):

Stanislav Popelka ◽

Alžběta Brychtová

Keyword(s):

Spatial Data ◽

Large Scale ◽

18Th Century ◽

3D Visualization ◽

3D Models ◽

Google Earth ◽

Point Of View ◽

World Heritage Site ◽

Historical Maps ◽

The City

Olomouc, nowadays a city with 100,000 inhabitants, has always been considered as one of the most prominent Czech cities. It is a social and economical centre, which history started just about the 11th century. The present appearance of the city has its roots in the 18th century, when the city was almost razed to the ground after the Thirty years’ war and a great fire in 1709. After that, the city was rebuilt to a baroque military fortress against Prussia army. At the beginning of the 20th century the majority of the fortress was demolished. Character of the town is dominated by the large number of churches, burgher’s houses and other architecturally significant buildings, like a Holy Trinity Column, a UNESCO World Heritage Site. Aim of this project was to state the most suitable methods of visualization of spatial-temporal change in historical build-up area from the tourist’s point of view, and to design and evaluate possibilities of spatial data acquisition. There are many methods of 2D and 3D visualization which are suitable for depiction of historical and contemporary situation. In the article four approaches are discussed comparison of historical and recent pictures or photos, overlaying historical maps over the orthophoto, enhanced visualization of historical map in large scale using the third dimension and photorealistic 3D models of the same area in different ages. All mentioned methods were geolocalizated using the Google Earth environment and multimedia features were added to enhance the impression of perception. Possibilities of visualization, which were outlined above, were realized on a case study of the Olomouc city. As a source of historical data were used rapport plans of the bastion fortress from the 17th century. The accuracy of historical maps was confirmed by cartometric methods with use of the MapAnalyst software. Registration of the spatial-temporal changes information has a great potential in urban planning or realization of reconstruction and particularly in the propagation of the region and increasing the knowledge of citizens about the history of Olomouc.

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A Spatial Analysis Approach to Understanding Caddoan Mounds in the Arkansas River Drainage

Index of Texas Archaeology Open Access Grey Literature from the Lone Star State ◽

10.21112/.ita.2004.1.23 ◽

2004 ◽

Author(s):

Gregory Vogel

Keyword(s):

Spatial Analysis ◽

Spatial Data ◽

Large Scale ◽

Theoretical Background ◽

Gis Analysis ◽

Arkansas River ◽

Gis Modeling ◽

River Drainage ◽

The People ◽

Computationally Intensive

In this article I present a theoretical framework for understanding Caddoan mounds in the central Arkansas River drainage and the implications they may hold for the social structure and environmental adaptations of the people who made them. The power and efficiency of Geographic Information Systems (GIS) modeling now allows for large-scale, computationally intensive spatial analysis simply not possible before. Questions of landscape organization or spatial relationships that previously would have taken months or even years to answer can now be solved in a matter of minutes with GIS and related technologies, given the appropriate datasets. Quite importantly, though, such analyses must first be placed in context and theory if they are to be meaningful additions to our understanding of the past. While it is conventional to refer to “GIS analysis” (and I use the term in this article), it is important to keep in mind that data manipulations alone are not analysis. GIS, along with statistical software and related computer technologies, are tools of spatial analysis just as shovels and trowels are tools of excavation. Such tools can organize and reveal information if they are employed carefully, but the tools themselves have no agency and cannot interpret anything on their own. The terms “GIS analysis” or “GIS interpretation” are therefore somewhat misnomers, just as “trowel analysis” or “trowel interpretation” would be. It is not the GIS, or any component of it, that does the analysis or interpretation; it simply manipulates spatial data. We interpret these manipulations based upon theoretical background, previous research, and the questions we wish to answer.

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UAV and terrestrial laser scanner data processing for large scale topographic mapping

Mongolian Geoscientist ◽

10.5564/mgs.v50i0.1329 ◽

2020 ◽

Vol 50 ◽

pp. 63-73

Author(s):

Ganbold Ulziisaikhan ◽

Dash Oyuntsetseg

Keyword(s):

Data Processing ◽

Spatial Data ◽

Large Scale ◽

Laser Scanner ◽

Measurement Technology ◽

Topographic Mapping ◽

Terrestrial Laser Scanner ◽

Scanner Data ◽

Processing Scheme ◽

Digital Elevation

Integrating spatial data from different sources results in visualization, which is the last step in the process of digital basic topographic map creation. Digital elevation model and visualization will used for geomorphological mapping, geospatial database, urban planning and etc. Large scale topographic mapping in the world countries is really a prominent challenge in geospatial industries today. The purpose of this work is to integrate laser scanner data with the ones generated by aerial photogrammetry from UAV, to produce detailed maps that can used by geodetic engineers to optimize their analysis. In addition, terrestrial - based LiDAR scans and UAV photogrammetric data were collected in Sharga hill in the north zone of Mongolia. In this paper, different measurement technology and processing software systems combined for topographic mapping in the data processing scheme. UTM (Universal Transverse Mercator) projected coordinate system calculated in WGS84 reference ellipsoid. Feature compilation involving terrestrial laser scanner data and UAV data will integrated to offer Digital Elevation Models (DEM) as the main interest of the topographic mapping activity. Used UAV generate high-resolution orthomosaics and detailed 3D models of areas where no data, are available. That result issued to create topographic maps with a scale of 1:1000 of geodetic measurements. Preliminary results indicate that discontinuity data collection from UAV closely matches the data collected using laser scanner.

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Digital matter as interdisciplinary commodity

The Journal of Public Space ◽

10.5204/jps.v2i3.119 ◽

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

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. The arc/sec Lab for Digital Spatial Operations 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. 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 digital matter is used as a new dynamic building material.

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