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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2016 - 1
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 HIGH-IMPACT PAPER 

An Efficient Tile-Pyramids Building Method for Fast Visualization of Massive Geospatial Raster Datasets

GUO, N. See more information about GUO, N. on SCOPUS See more information about GUO, N. on IEEExplore See more information about GUO, N. on Web of Science, XIONG, W. See more information about  XIONG, W. on SCOPUS See more information about  XIONG, W. on SCOPUS See more information about XIONG, W. on Web of Science, WU, Q. See more information about  WU, Q. on SCOPUS See more information about  WU, Q. on SCOPUS See more information about WU, Q. on Web of Science, JING, N. See more information about JING, N. on SCOPUS See more information about JING, N. on SCOPUS See more information about JING, N. on Web of Science
 
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Download PDF pdficon (1,473 KB) | Citation | Downloads: 1,974 | Views: 3,551

Author keywords
geographic information systems, indexing, parallel algorithms, spatial resolution, tiles

References keywords
visualization(11), terrain(10), tile(5), rendering(5), information(5), data(5), graphics(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04001
Web of Science Accession Number: 000390675900001
SCOPUS ID: 85007576472

Abstract
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Building tile-pyramids is an effective way for publishing and accessing the map visualization service of large-scale geospatial data in the web. But it is a time-consuming task in Geographic Information System (GIS) to build tile-pyramids using traditional methods. In this article, an adaptive multilevel tiles generation method is proposed, which first builds grid index for the geospatial raster dataset, and then generates tiles according to different hierarchy level numbers in the tile-pyramid. With the optimized map rendering engine implemented, a parallel tiles pyramid generation method for large-scale geospatial raster dataset is integrated into a high performance GIS platform. Proved by experiments, the new method shows acceptable applicability, stability and scalability besides its high efficiency.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 15
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Cited-By CrossRef

[1] An efficient visual exploration approach of geospatial vector big data on the web map, Liu, Zebang, Chen, Luo, Ma, Mengyu, Yang, Anran, Zhong, Zhinong, Jing, Ning, Information Systems, ISSN 0306-4379, Issue , 2024.
Digital Object Identifier: 10.1016/j.is.2023.102333
[CrossRef]

[2] HTile: A high‐performance real‐time raster tile service with data‐fusion and data‐hiding approaches, Chen, Jyun‐Yuan, Kuo, Chiao‐Ling, Transactions in GIS, ISSN 1361-1682, Issue 5, Volume 28, 2024.
Digital Object Identifier: 10.1111/tgis.13194
[CrossRef]

[3] A Dynamic Pyramid Tilling Method for Traffic Data Stream Based on Flink, Hu, Linshu, Zhang, Feng, Qin, Mengjiao, Fu, Zhiyi, Chen, Zhende, Du, Zhenhong, Liu, Renyi, IEEE Transactions on Intelligent Transportation Systems, ISSN 1524-9050, Issue 7, Volume 23, 2022.
Digital Object Identifier: 10.1109/TITS.2021.3060576
[CrossRef]

[4] DCPMS: A Large-Scale Raster Layer Serving Method for Custom Online Calculation and Rendering, Yang, Anbang, Zhang, Feng, Feng, Jie, Wang, Luoqi, Yue, Enjiang, Fan, Xinhua, Zhang, Jingyi, Hu, Linshu, Wu, Sensen, ISPRS International Journal of Geo-Information, ISSN 2220-9964, Issue 8, Volume 13, 2024.
Digital Object Identifier: 10.3390/ijgi13080276
[CrossRef]

[5] Dynamic heatmap pyramid computation for massive high-parallel spatial streaming in urban environments, Xu, Qi, Xiang, Longgang, Wu, Huayi, Tao, Chuang, Wang, Haocheng, Yu, Liebing, Liu, Quan, Wang, Xumei, International Journal of Digital Earth, ISSN 1753-8947, Issue 1, Volume 17, 2024.
Digital Object Identifier: 10.1080/17538947.2024.2368099
[CrossRef]

[6] A Fast Tile-Pyramid Construction Algorithm Based on Multilevel Task Parallelism, Liu, Haozheng, Wu, Ye, Jing, Ning, Feng, Shihao, IOP Conference Series: Earth and Environmental Science, ISSN 1755-1307, Issue 1, Volume 513, 2020.
Digital Object Identifier: 10.1088/1755-1315/513/1/012056
[CrossRef]

[7] Land Use and Land Cover Mapping in the Era of Big Data, Zhang, Chuanrong, Li, Xinba, Land, ISSN 2073-445X, Issue 10, Volume 11, 2022.
Digital Object Identifier: 10.3390/land11101692
[CrossRef]

[8] Map vector tile construction for arable land spatial connectivity analysis based on the Hadoop cloud platform, Ma, Shengting, Zhang, Shanshan, Frontiers in Earth Science, ISSN 2296-6463, Issue , 2023.
Digital Object Identifier: 10.3389/feart.2023.1234732
[CrossRef]

[9] HexTile: A Hexagonal DGGS-Based Map Tile Algorithm for Visualizing Big Remote Sensing Data in Spark, Yao, Xiaochuang, Yu, Guojiang, Li, Guoqing, Yan, Shuai, Zhao, Long, Zhu, Dehai, ISPRS International Journal of Geo-Information, ISSN 2220-9964, Issue 3, Volume 12, 2023.
Digital Object Identifier: 10.3390/ijgi12030089
[CrossRef]

[10] Scale Space Visualization of Dynamic Track Clusters in an Enterprise GIS, Mahajan, Sahil, M A, Rajesh, Panigrahi, Narayan, 2022 3rd International Conference for Emerging Technology (INCET), ISBN 978-1-6654-9499-1, 2022.
Digital Object Identifier: 10.1109/INCET54531.2022.9825018
[CrossRef]

[11] A Display Method of Large Underwater Photo-Mosaics Based on Pyramid Model of Tiled Images, Liu, Nannan, Li, Xiaoming, 2021 International Conference on Computer Communication and Artificial Intelligence (CCAI), ISBN 978-1-7281-9401-1, 2021.
Digital Object Identifier: 10.1109/CCAI50917.2021.9447465
[CrossRef]

[12] Cloud-Based Parallel Tiling Algorithm for Large Scale Remote Sensing Datasets, Xu, Chen, Du, Xiaoping, Yan, Zhenzhen, Fan, Xiangtao, IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, ISBN 978-1-6654-2792-0, 2022.
Digital Object Identifier: 10.1109/IGARSS46834.2022.9884712
[CrossRef]

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