出版社：Vilnius University, University of Latvia, Latvia University of Agriculture, Institute of Mathematics and Informatics of University of Latvia
摘要：Real estate monitoring is very important aspect of country economics, but old manual
methods of land survey are time and resources consuming processes as geodata actualization tasks.
Actual, precise, multidimensional and detailed information is the main instrument of geospatial
intelligence to understand current economic situation and to make effective decision. Actualization
of geoinformation using remote sensing is the modern approach of the computer age to complete
Earth observation and human environment monitoring. This article describes multi-stage
classification model, which detects man-made constructions in LiDAR point cloud. Proposed
classification model applies decision tree and geometrical features of shape to remove noises. The
goal of study is to experimentally compare decision trees with crisp and fuzzy logic (ID3
algorithms) to select the more suitable algorithm for noise reduction task. Algorithms are
compared using total accuracy and Cohen’s Kappa coefficient.
关键词：classification; decision tree; features; fuzzy; ID3; LiDAR; real estate
