OUTLIER DETECTION ANALYSIS FROM LiDAR DATA FOR MAPPING


Bas N., Coskun H. G. , Celik H.

7th International Conference on Cartography and GIS, Sozopol, Bulgaria, 18 - 23 June 2018, pp.781-791 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • City: Sozopol
  • Country: Bulgaria
  • Page Numbers: pp.781-791

Abstract

Airborne Light Detection and Ranging (LiDAR) technology has provided an efficient way to obtain topographic information by measuring the reflected pulses with a sensor and laser scanner for 3D modeling of disaster area. The main purpose of this study is to extract outlier points from raw data to produce terrain map modeling. A heterogeneous and mountainous terrain including the provinces of Artvin, Borcka and Ardanuc in Eastern Anatolia Region of Turkey has been selected as the study area. In this area, 4 different sites were identified in different terrains. Raw data analysis Framework (RDAF) and Adaptive Triangulation Irregular Network (ATIN) method was implemented in this process for the first time to increase the data cleaning performance. As a result of the process, the performance of the method was examined by calculating the errors. The ratios of outlier points to be removed from the data are as follows according to the comparison with respect to reference data with this application: 60% for site-1, 25% for site-2, 33% for site-3, and 38% for site-4 have been cleaned from the data set. ATIN filtering method was applied to the remaining points with the aim of removing the remaining outlier points. The outliers point were cleaned by %99 and the performance of the process was greatly facilitated with these two methods.