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LIDAR (Light Detection and Ranging) is an especially effective tool for acquiring geo-referenced point clouds of urban site. Accurate extraction of elevated features such as building rooftops is vitally important in various applications. However, it is still challenging to determine an accurate rooftop contour from the irregularly distributed LIDAR point clouds. In this paper an efficient LIDAR segmentation...
Waveform decomposition is an important step in full-waveform LiDAR remote sensing. Under the Gaussian Mixture Model, the conventional parametric classification algorithm of Expectation-Maximization (EM) is among the most widely applied ones to decompose the waveforms. This paper introduces nonparametric classification methods, such as K-means and mean-shift to decompose the LiDAR waveforms. The experiments...
In this paper we present a growth-model based approach to the accurate estimation of stem diameter at single tree level by using high-density LiDAR data. First, we detect classes of trees characterized by different growth conditions by means of a data-driven inference process. To this end, all the environmental factors that can affect the growth of the tree (i.e., forest density and topography) are...
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