Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 641–644, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-641-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 641–644, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-641-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

MACHINE LEARNING IN BIG LIDAR DATA: A REVIEW

S. S. Teri and I. A. Musliman S. S. Teri and I. A. Musliman
  • Dept. of Geoinformation, Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

Keywords: Machine Learning, Big LIDAR Data, Deep Learning, Supervised Learning, Unsupervised Learning

Abstract. Machine Learning used to refer as one Artificial Intelligence subsection that perform self-learning computational algorithms either supervised learning or unsupervised learning tasks. Machine Learning can compute a prediction onto hidden data patterns that hardly for human to detect. This valuable information and predictions able to help companies or researchers make a crucial decision making especially in natural disasters. In Geographic Information Systems (GIS), the advancement of Machine Learning used literally on satellite imagery analyses and fewer on LIDAR point clouds. In this paper presents an overview of Machine Learning definitions, big geospatial data, Machine Learning types and models, and advancement researches using Machine Learning in big LIDAR data.