Detection and classification of changes in buildings by direct comparison of multi-temporal LIDAR Systems data

Abstract

This study consists in the detection of changes in buildings with LIDAR technology, for which, changes in buildings are identified,classified and quantified of two study areas mapped by LIDAR sensors, using the direct comparison of multi-temporal points clouds obtained from mapping. The process begins with the correction of errors in point cloud records after two detection methods are applied:the first one is called indirect method due to the transformation of the raster data; the second one is called direct method, of vector type.When quantifying the detected buildings, an important approximation was obtained from both methods concerning the locations of these buildings and, when estimating height and area, the direct method presented higher accuracy. In conclusion, both methods are efficient tools for observation of the real estate dynamics through different time intervals.