Open AccessManagement Point Cloud Data based on GeoSOT-3D Subdivision Model
Author(s) -
Zhongyue Liu,
Xian Guo
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/658/1/012017
Subject(s) - point cloud , computer science , data mining , grid , cloud computing , subdivision , metadata , search engine indexing , volume (thermodynamics) , position (finance) , point (geometry) , data management , information retrieval , database , computational science , geography , computer vision , mathematics , world wide web , geodesy , finance , quantum mechanics , economics , operating system , physics , geometry , archaeology
Owing to the rapid development of earth observation technology, the volume of point cloud dataset is growing rapidly. The efficient management and retrieval method is very important for effective use of the large point cloud datasets. Current methods for point cloud data management are generally based on file which makes it difficult to describe internal structure of the modelling objects, while current indexing is generally based on coordinates which is quite time-consuming for large volume cloud point data. To solve these problems, we proposed a method to manage and index point cloud data with a global grid model GeoSOT. The subdivision model of three-dimensional point cloud data was defined to identify the global position of point clouds and internal points with GeoSOT-3D grids. The management and indexing of point clouds were implemented based on the GeoSOT-3D grid codes integrated with the metadata table. A 3D prototype platform for showing the method was developed based on the Cesium. Experimental results show that our method is able to manage, query, visualize massive point clouds as well as other data sources in a unified global position framework.