Obtaining optimal parameters in the classification of LIDAR points clouds, from airborne sensors
DOI:
https://doi.org/10.18041/1794-4953/avances.1.1280Keywords:
ALS - Airbone laser Scanning, Data validation, Dot cloud classification, Digital field models, DTM Interpolation methods, Point cloud LiDARAbstract
In the present work the information obtained from the data of two airborne topographic sensors LiDAR, Riegl VQ 580 and Leica ALS70 is used, obtaining cloud of points of the same zone. By performing a comparative iterative analysis, obtaining the optimal parameters of iteration angle, terrain, slope and iteration distance, used in the semiautomatic classification of points clouds and generate digital terrain models - DTM. In order to analyze the behavior of the point clouds and precision check, a control of dimensions was carried out and comparisons of the different digital terrain models were obtained, obtaining, therefore, this methodology.
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