完整後設資料紀錄
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dc.contributor.authorTeo, Tee-Annen_US
dc.contributor.authorYeh, Wan-Yien_US
dc.date.accessioned2019-04-02T05:59:36Z-
dc.date.available2019-04-02T05:59:36Z-
dc.date.issued2018-07-01en_US
dc.identifier.issn2072-4292en_US
dc.identifier.urihttp://dx.doi.org/10.3390/rs10071141en_US
dc.identifier.urihttp://hdl.handle.net/11536/147931-
dc.description.abstractWaveform lidar provides both geometric and waveform properties from the entire returned signals. The waveform analysis is an important process to extract the attributes of the reflecting surface from the waveform. The proposed method analyzes the geospatial relationship between the return signals by combining the sequential waves. The idea of this method is to analyze the waveform parameters from sequential waves. Since the adjacent return signals are geospatially correlated, they have similar waveform properties that can be used to validate the correctness of the extracted waveform parameters. The proposed method includes three major steps: (1) single-waveform processing for the initial echo detection; (2) multi-waveform processing using waveform alignment and stacking; (3) verification of the enhanced weak return. The experimental waveform lidar data were acquired using Leica ALS60, Optech Pegasus, and Riegl Q680i. The experimental result indicates that the proposed method successfully extracts the weak returns while considering the geospatial relationships. The correctness and increasing rate of the extracted ground points are related to the vegetated coverage such as the complexity and density. The correctness is above 76% in this study. Because the nearest waveform has a higher correlation, the increase in distance of adjacent waveforms will reduce the correctness of the enhanced weak return.en_US
dc.language.isoen_USen_US
dc.subjectwaveform lidaren_US
dc.subjectweak returnen_US
dc.subjectGaussian decompositionen_US
dc.subjectwaveform alignment and stackingen_US
dc.titleThe Benefit of the Geospatial-Related Waveforms Analysis to Extract Weak Laser Pulsesen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/rs10071141en_US
dc.identifier.journalREMOTE SENSINGen_US
dc.citation.volume10en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000440332500164en_US
dc.citation.woscount0en_US
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