Geographical information system parallelization for spatial big data processing: a review

2015 ◽  
Vol 19 (1) ◽  
pp. 139-152 ◽  
Author(s):  
Lingjun Zhao ◽  
Lajiao Chen ◽  
Rajiv Ranjan ◽  
Kim-Kwang Raymond Choo ◽  
Jijun He
Keyword(s):  
Information System ◽  
Big Data ◽  
Data Processing ◽  
Geographical Information System ◽  
Geographical Information ◽  
Big Data Processing ◽  
Spatial Big Data

Improving the performance of GIS polygon overlay computation with MapReduce for spatial big data processing

2015 ◽  
Vol 18 (2) ◽  
pp. 507-516 ◽  
Author(s):  
Yong Wang ◽  
Zhenling Liu ◽  
Hongyan Liao ◽  
Chengjun Li
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Big Data Processing ◽  
Spatial Big Data

scholarly journals Zwölf Jahre Geografisches Informationssystem im Bereich Wald – ein Erfahrungsbericht | Twelve years of a geographical forest information system - account of progress

2003 ◽  
Vol 154 (7) ◽  
pp. 289-293
Author(s):  
Stefan Fassbind
Keyword(s):  
Information System ◽  
Data Processing ◽  
Case Studies ◽  
Geographical Information System ◽  
Complex Structure ◽  
Geographical Information ◽  
Forest Department ◽  
Use Of Data ◽  
Central Data

The Forest Department of the canton of Argovia has been working with the Geographical Information System (GIS) since 1991. Apart from collecting the data, which uses the greater part of the resources, other areas have been developed (e.g.,mapping). A number of programmes have been developed that facilitates the user's access to the increasingly complex structure of the database. An efficient, canton-wide network with central data processing and decentralised responsibility for the up-dating of the data has fostered a lively use of data between specialist units. Using a number of case studies we show that the work of the Forest Department can no longer be imagined without GIS.

Big data processing technology in a distributed information system

2021 ◽  
Vol 143 (2) ◽  
pp. 272-278
Author(s):  
S. K. Serikbayeva ◽  
◽  
J. A. Tussupov ◽  
M. A. Sambetbayeva ◽  
◽  
...  
Keyword(s):  
Information System ◽  
Big Data ◽  
Data Processing ◽  
Processing Technology ◽  
Big Data Processing ◽  
Distributed Information System ◽  
Distributed Information

scholarly journals Solving Big GIS Projects on Desktop Computers

2019 ◽  
Vol 18 (32) ◽  
pp. 44-62
Author(s):  
Dalibor Bartoněk
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Information Technologies ◽  
Digital Data ◽  
Geographical Information ◽  
Digital Information ◽  
Big Data Processing ◽  
Data Volume

We are witnessing great developments in digital information technologies. The situation encroaches on spatial data, which contain both attributive and localization features, and this determines their position unequally within an obligatory coordinate system. These changes have resulted in the rapid growth of digital data, significantly supported by technical advances regarding the devices which produce them. As technology for making spatial data advances, methods and software for big data processing are falling behind. Paradoxically, only about 2% of the total volume of data is actually used. Big data processing often requires high computation performance hardware and software. Only a few users possess the appropriate information infrastructure. The proportion of processed data would improve if big data could be processed by ordinary users. In geographical information systems (GIS), these problems arise when solving projects related to extensive territory or considerable secondary complexity, which require big data processing. This paper focuses on the creation and verification of methods by which it would be possible to process effectively extensive projects in GIS supported by desktop hardware and software. It is a project regarding new quick methods for the functional reduction of the data volume, optimization of processing, edge detection in 3D and automated vectorization.

scholarly journals PENENTUAN LOKASI POTENSIAL UNTUK PENGEMBANGAN TERMINAL TIPE B SEBAGAI ALTERNATIF PENGGANTI TERMINAL CIBINONG DI WILAYAH ZONA CIBINONG RAYA KABUPATEN BOGOR

2016 ◽  
Vol 15 (1) ◽  
pp. 29-33
Author(s):  
Dita Anggraeni ◽  
Sucahyanto Sucahyanto ◽  
Ode Sofyan Hardi
Keyword(s):  
Information System ◽  
Data Analysis ◽  
Data Processing ◽  
Geographical Information System ◽  
Research Method ◽  
Geographical Information ◽  
Potential Zone ◽  
System Software ◽  
Type B ◽  
Descriptive Method

ABSTRACT This research aims to map the location of a potential designed as the location to develop B type terminal as an alternative of Cibinong terminal in Cibinong Zone Raya Bogor Regency. This research was conducted in six districts in Cibinong Raya zone region. The districts are Cibinong, Citeureup, Sukaraja, Babakan Madang, Bojong Gede, and Tajur Halang. The researcher used descriptive method as the research method. The technique of data analysis refers to the suitability matrix that has been made under the term parameters of type-B terminal development. The parameters were given the scoring and then processed further by the geographical information system software. After that, the processed results were classified into some classes based on the suitability level of each parameter. The three classifications are the result of the total scores divided into three classifications. For Potential 1 (P1) with a range 14-20, Potential 2 (P2) with a range 713 and Potential 3 (P3) with a range 0-6. The result showed that based on data processing geographical information system in these included in classifying according 1 ( potential 1 ) spread right and left sides jakarta-bogor roads , major oking jayaatmaja cibinong , sukahati-karadenan and the brave believe. Classifying according to 2 ( potential 2 ) spread in roads major oking jayaatmaja citeureup, the kranggan – gunung putri and highways jagorawi. To determine the locations is 3 potential zone with the highest states to be terminals,this zone is Cibinong Zone , Karadenan Zone and Sukahati Zone. Of the three the zone,Cibinong Zone the most suitable to be locations terminal development. Keywords: Potential, Location, Terminal

scholarly journals A COMPARATIVE ANALYSIS OF CONVENTIONAL HADOOP WITH PROPOSED CLOUD ENABLED HADOOP FRAMEWORK FOR SPATIAL BIG DATA PROCESSING

2018 ◽  
Vol IV-5 ◽  
pp. 425-430 ◽  
Author(s):  
A. K. Tripathi ◽  
S. Agrawal ◽  
R. D. Gupta
Keyword(s):  
Big Data ◽  
Data Processing ◽  
High Performance ◽  
Computing Environment ◽  
Big Data Processing ◽  
Huge Data ◽  
Spatial Big Data ◽  
New Research ◽  
Performance Computing ◽  
Hadoop Framework

<p><strong>Abstract.</strong> The emergence of new tools and technologies to gather the information generate the problem of processing spatial big data. The solution of this problem requires new research, techniques, innovation and development. Spatial big data is categorized by the five V’s: volume, velocity, veracity, variety and value. Hadoop is a most widely used framework which address these problems. But it requires high performance computing resources to store and process such huge data. The emergence of cloud computing has provided, on demand, elastic, scalable and payment based computing resources to users to develop their own computing environment. The main objective of this paper is to develop a cloud enabled hadoop framework which combines cloud technology and high computing resources with the conventional hadoop framework to support the spatial big data solutions. The paper also compares the conventional hadoop framework and proposed cloud enabled hadoop framework. It is observed that the propose cloud enabled hadoop framework is much efficient to spatial big data processing than the current available solutions.</p>

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