A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA
Airborne LiDAR technology has proven to be the most powerful tools to obtain high-density, high-accuracy and significantly detailed surface information of terrain and surface objects within a short time, and from which the Digital Elevation Model of high quality can be extracted. Point cloud data ge...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2015-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/1209/2015/isprsarchives-XL-7-W3-1209-2015.pdf |
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| author | X. Jian X. Xiao H. Chengfang Z. Zhizhong W. Zhaohui Z. Dengzhong |
| author_facet | X. Jian X. Xiao H. Chengfang Z. Zhizhong W. Zhaohui Z. Dengzhong |
| author_sort | X. Jian |
| collection | DOAJ |
| description | Airborne LiDAR technology has proven to be the most powerful tools to obtain high-density, high-accuracy and significantly
detailed surface information of terrain and surface objects within a short time, and from which the Digital Elevation Model of high
quality can be extracted. Point cloud data generated from the pre-processed data should be classified by segmentation algorithms, so
as to differ the terrain points from disorganized points, then followed by a procedure of interpolating the selected points to turn
points into DEM data. The whole procedure takes a long time and huge computing resource due to high-density, that is concentrated
on by a number of researches. Hadoop is a distributed system infrastructure developed by the Apache Foundation, which contains a
highly fault-tolerant distributed file system (HDFS) with high transmission rate and a parallel programming model (Map/Reduce).
Such a framework is appropriate for DEM generation algorithms to improve efficiency. Point cloud data of Dongting Lake acquired
by Riegl LMS-Q680i laser scanner was utilized as the original data to generate DEM by a Hadoop-based algorithms implemented in
Linux, then followed by another traditional procedure programmed by C++ as the comparative experiment. Then the algorithm’s
efficiency, coding complexity, and performance-cost ratio were discussed for the comparison. The results demonstrate that the
algorithm's speed depends on size of point set and density of DEM grid, and the non-Hadoop implementation can achieve a high
performance when memory is big enough, but the multiple Hadoop implementation can achieve a higher performance-cost ratio,
while point set is of vast quantities on the other hand. |
| first_indexed | 2024-12-12T01:41:16Z |
| format | Article |
| id | doaj.art-b6e2655869bc4f07bfcdacd35d3eb6e1 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-12T01:41:16Z |
| publishDate | 2015-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-b6e2655869bc4f07bfcdacd35d3eb6e12022-12-22T00:42:41ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342015-04-01XL-7/W31209121410.5194/isprsarchives-XL-7-W3-1209-2015A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATAX. Jian0X. Xiao1H. Chengfang2Z. Zhizhong3W. Zhaohui4Z. Dengzhong5Changjiang River Scientific Research Institute, Wuhan, ChinaSchool of Resource and Environmental Science, Wuhan University, Wuhan, ChinaChangjiang River Scientific Research Institute, Wuhan, ChinaChangjiang River Scientific Research Institute, Wuhan, ChinaChangjiang River Scientific Research Institute, Wuhan, ChinaChangjiang River Scientific Research Institute, Wuhan, ChinaAirborne LiDAR technology has proven to be the most powerful tools to obtain high-density, high-accuracy and significantly detailed surface information of terrain and surface objects within a short time, and from which the Digital Elevation Model of high quality can be extracted. Point cloud data generated from the pre-processed data should be classified by segmentation algorithms, so as to differ the terrain points from disorganized points, then followed by a procedure of interpolating the selected points to turn points into DEM data. The whole procedure takes a long time and huge computing resource due to high-density, that is concentrated on by a number of researches. Hadoop is a distributed system infrastructure developed by the Apache Foundation, which contains a highly fault-tolerant distributed file system (HDFS) with high transmission rate and a parallel programming model (Map/Reduce). Such a framework is appropriate for DEM generation algorithms to improve efficiency. Point cloud data of Dongting Lake acquired by Riegl LMS-Q680i laser scanner was utilized as the original data to generate DEM by a Hadoop-based algorithms implemented in Linux, then followed by another traditional procedure programmed by C++ as the comparative experiment. Then the algorithm’s efficiency, coding complexity, and performance-cost ratio were discussed for the comparison. The results demonstrate that the algorithm's speed depends on size of point set and density of DEM grid, and the non-Hadoop implementation can achieve a high performance when memory is big enough, but the multiple Hadoop implementation can achieve a higher performance-cost ratio, while point set is of vast quantities on the other hand.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/1209/2015/isprsarchives-XL-7-W3-1209-2015.pdf |
| spellingShingle | X. Jian X. Xiao H. Chengfang Z. Zhizhong W. Zhaohui Z. Dengzhong A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA |
| title_full | A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA |
| title_fullStr | A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA |
| title_full_unstemmed | A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA |
| title_short | A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA |
| title_sort | hadoop based algorithm of generating dem grid from point cloud data |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/1209/2015/isprsarchives-XL-7-W3-1209-2015.pdf |
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