| dc.contributor | 地政系 | - |
| dc.creator (作者) | 范噶色; 林士淵 | - |
| dc.creator (作者) | Gasselt, Stephan van; Lin, Shih-Yuan | - |
| dc.creator (作者) | Lin, Cheng-Wei | - |
| dc.date (日期) | 2021-07 | - |
| dc.date.accessioned | 6-一月-2022 16:27:31 (UTC+8) | - |
| dc.date.available | 6-一月-2022 16:27:31 (UTC+8) | - |
| dc.date.issued (上傳時間) | 6-一月-2022 16:27:31 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/138704 | - |
| dc.description.abstract (摘要) | We here present an object-based image analysis (OBIA) approach to identify temporal changes in radar intensity images and to locate land-cover changes caused by mass-wasting processes at small to large scales, such as landslides. OBIA was introduced to systematically and semi-automatically detect landslides in image pairs with an overall accuracy of at least 60% when compared to in-situ landslide inventory data. Our approach is based upon change detection in intensity images that remain in their original imaging coordinate system rather than being map projected, in order to reduce image artefacts. Intensity images in their native coordinate frame allow for a consistent level of detection of land-cover changes. If wrapped within a continuous monitoring framework, our approach might help to assist to not only assess large-scale landslides as they occur, but to identify subtle movements prior to slope failure in order to launch mitigation measures and response. | - |
| dc.format.extent | 2645508 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS | - |
| dc.subject (關鍵詞) | Remote Sensing; Synthetic Aperture Radar; Landslides; Natural Hazards; Object-Based Image Analysis | - |
| dc.title (題名) | Towards Monitoring of Mountain Mass Wasting using Object-Based Image Analysis using SAR Intensity Images | - |
| dc.type (資料類型) | conference | - |
