Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1209-1214, 2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
30 Apr 2015
X. Jian1, X. Xiao2, H. Chengfang1, Z. Zhizhong1, W. Zhaohui1, and Z. Dengzhong1 1Changjiang River Scientific Research Institute, Wuhan, China
2School of Resource and Environmental Science, Wuhan University, Wuhan, China
Keywords: Hadoop. LiDAR, Digital Elevation Model Abstract. 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.
Conference paper (PDF, 1282 KB)

Citation: Jian, X., Xiao, X., Chengfang, H., Zhizhong, Z., Zhaohui, W., and Dengzhong, Z.: A HADOOP-BASED ALGORITHM OF GENERATING DEM GRID FROM POINT CLOUD DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 1209-1214,, 2015.

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