An Inspection Approach for Airborne LiDAR Data Filtering And Qualification
| Autor: | Ting-wei Kuo, 郭庭瑋 |
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| Rok vydání: | 2013 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 Airborne LIDAR captures the high-resolution 3D spatial coordinates of the earth’s surface and coverings and forms point cloud data in a very short period of time by illuminating targets with a laser and analyzing reflected and multiple echoes. By filtering the point cloud data, surface coverings such as buildings, bridges and vegetation can then be classified as non-ground points while appropriate points in the point cloud can be interpreted as ground points, thereby generating digital surface models (DSM) and digital elevation models (DEM). In current practices, two-stage validation that includes point cloud and DEM is the most common. Point cloud validation interprets terrains mainly based on collective data from point cloud, aerial photos, and rough terrain models to determine the accuracy of point cloud classification. However, point cloud validation tends to be subjective because results often vary when different people conduct point cloud validation on the same area. DEM validation interprets using DEM mainly based on terrain categories, coverage of the earth’s ground by vegetation, i.e. the average elevation of vegetation coverage on the surface, and there are already quantification standards for such interpretation. Results of ground point classification are directly linked to the quality of DEM products. According to current specifications, point cloud density for different slopes can reach 1.5 to 2 points per square meter, so final DEM products remain fairly accurate even if ground point classification has slight gaps. In view of the foregoing, the intent of this study is to establish a quality assessment process that estimates the reasonable classification accuracy in accordance with current DEM specifications, based on which considerable classification achievements can be expected. Based on this quality assessment process, our experiment consists of internal quality assessment, by which empirical accuracy is obtained, and external assessment of relative errors, which uses reference values to verify the rationality of the empirical accuracy. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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