Foliage-wood separation from terrestrial laser scanner point clouds using a machine learning approach | |
| Author | Sindhu, Kuna |
| Call Number | AIT Thesis no.RS-23-15 |
| Subject(s) | Three-dimensional imaging in geology Geographic information systems |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | This study presents a methodology for the precise analysis of point cloud data in the realm of Remote Sensing and Geographical Information Systems (GIS). The primary objective is the segmentation of distinct tree components,specifically bark and leaves, imposing on advanced spatial data processing techniques. The data preprocessing stage incorporates CloudCompare for data cleaning and optimizing the point cloud for further analysis. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, the research efficiently identifies and categorizes clusters within the point cloud. An in-depth exploration of diverse parameter configurations for DBSCAN clustering leads to the identification of optimal settings for precise wood and leaf separation. The analysis further explores into frequency-based evaluations to recognize critical points in the clustering process, utilizing continuation and selection graphs. Finally, the study enabling the visual representation of clustcred point cloud data. This methodology holds significant potential for various applications within the domain of Remote Sensing and GIS, including land cover analysis, vegetation classification and environmental monitoring. The results offer valuable insights into the intricacies of point cloud data analysis, providing a foundation for enhanced decision-making processes and data-driven solutions in geospatial applications. |
| Year | 2023 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Virdis, Salvatore G.P. |
| Examination Committee(s) | Tripathi, Nitin Kumar;Mozumder, Chitrini |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2023 |