dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.advisor | Hyyppä, Juha, Prof., Finnish Geospatial Research Institute, Finland | |
dc.contributor.author | Chen, Yuwei | |
dc.date.accessioned | 2020-11-11T10:00:06Z | |
dc.date.available | 2020-11-11T10:00:06Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-952-64-0077-8 (electronic) | |
dc.identifier.isbn | 978-952-64-0076-1 (printed) | |
dc.identifier.issn | 1799-4942 (electronic) | |
dc.identifier.issn | 1799-4934 (printed) | |
dc.identifier.issn | 1799-4934 (ISSN-L) | |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/47576 | |
dc.description.abstract | LiDAR (Light Detection And Ranging, also known as LADAR) is an active optical remote sensing technique that can measure the distance by counting the time of flight (ToF) of the transmitted laser and acquire other physical properties of a target by illuminating the target with a light source, often using a pulsed laser due to the high spatial and temporal coherence nature. Traditionally a monochromatic laser beam can map physical features with a very high spatial resolution in a non-contact manner. Limited by the employed monochromatic laser source, traditional LiDAR sensors usually operate at one or several discrete wavelength bands. These systems can provide high-accuracy spatial information, but restricted spectral information: compared with a passive spectrometer, the spectral information and spectral resolution are inadequate for some particular remote sensing applications. The motivation of this research is straightforward: investigating SCL-based hyperspectral LiDAR (HSL) technology, more specifically: investigating HSL technique with different system configuration, confirming their accuracy both in spatial and spectral measurements, and conducting various feasibility studies towards environmental awareness applications, more specific, in in forestry, plant science and mining. The emphasis was on system development and methodology development. The specific aims of this dissertation based on six prototyped hyperspectral LiDAR were as follows: • to investigate different hardware techniques including optics, electronics, and post-processing techniques for HSL system development covering the spectrum from visible to near-infrared (VNIR) to shortwave infrared (SWIR) (for better eye-safety operation) with discrete or continuous spectral channels for remote sensing applications; • to develop methods to evaluate the performance of the HSL systems concerning the spectral measurement accuracy, the range stability and resolution over the covered spectral range ; • to assess the feasibility of the developed methods in forestry, mining and plant sciences related environment awareness applications with the point clouds or range measurement containing the spectral information. | en |
dc.format.extent | 106 + app. 68 | |
dc.format.mimetype | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | Aalto University | en |
dc.publisher | Aalto-yliopisto | fi |
dc.relation.ispartofseries | Aalto University publication series DOCTORAL DISSERTATIONS | en |
dc.relation.ispartofseries | 156/2020 | |
dc.relation.haspart | [Publication 1]: Chen Yuwei, Raikkonen Esa, Kaasalainen Sanna, Suomalainen Juha, Hakala Teemu, Hyyppa Juha, Chen Ruizhi. "Two-channel hyperspectral Li- DAR with a supercontinuum laser source." Sensors 10, no. 7 (2010): 7057- 7066. DOI:10.3390/s100707057 | |
dc.relation.haspart | [Publication 2]: Hakala Teemu, Suomalainen Juha, Kaasalainen Sanna, Chen Yuwei. "Full waveform hyperspectral LiDAR for terrestrial laser scanning." Optics Express 20, no. 7 (2012): 7119-7127. DOI:10.1364/OE.20.007119 | |
dc.relation.haspart | [Publication 3]: Wang Zhen, Chen Yuwei, Li Chuanrong, Tian Mi, Zhou Mei, He Wenjing, Wu Haohao, Zhang Huijing, Tang Lingli, Wang Yiwu, Zhou Hui, Puttonen, Eetu, Hyyppa Juha. "A Hyperspectral LiDAR with Eight Channels Covering from VIS to SWIR." In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, pp. 4293-4296. IEEE, 2018. DOI: 10.1109/IGARSS.2018.8517741 | |
dc.relation.haspart | [Publication 4]: Chen Yuwei, Jiang Changhui, Hyyppa Juha, Qiu Shi, Wang Zhen, Tian Mi, Li Wei, Puttonen Eetu, Zhou Hui, Feng Ziyi, Yuming Bo, Zhijie Wen. "Feasibility study of ore classification using active hyperspectral LiDAR." IEEE Geoscience and Remote Sensing Letters 15, no. 11 (2018): 1785-1789. DOI: 10.1109/LGRS.2018.2854358 | |
dc.relation.haspart | [Publication 5]: Li Wei, Jiang Changhui Jiang, Chen Yuwei, Hyyppa Juha, Tang Lingli Tang, Li Chuanrong, Wang Shao Wei. "A Liquid Crystal Tunable Filter- Based Hyperspectral LiDAR System and Its Application on Vegetation Red Edge Detection." IEEE Geoscience and Remote Sensing Letters 16, no. 2 (2018): 291-295. DOI: 10.1109/LGRS.2018.2870143 | |
dc.relation.haspart | [Publication 6]: Chen Yuwei, Li Wei, Hyyppa Juha, Wang Ning, Jiang Changhui, Meng Fanrong, Tang Lingli, Puttonen Eetu, Li Chuanrong. "A 10-nm spectral resolution hyperspectral LiDAR system based on an acousto-optic tunable filter." Sensors 19, no. 7 (2019): 1620. DOI:10.3390/s19071620 | |
dc.subject.other | Computer science | en |
dc.title | Environment Awareness with Hyperspectral LiDAR Technologies | en |
dc.type | G5 Artikkeliväitöskirja | fi |
dc.contributor.school | Perustieteiden korkeakoulu | fi |
dc.contributor.school | School of Science | en |
dc.contributor.department | Tietotekniikan laitos | fi |
dc.contributor.department | Department of Computer Science | en |
dc.subject.keyword | remote sensing | en |
dc.subject.keyword | hyperspectral LiDAR | en |
dc.subject.keyword | environment awareness | en |
dc.subject.keyword | mining | en |
dc.subject.keyword | forestry | en |
dc.subject.keyword | plant science | en |
dc.identifier.urn | URN:ISBN:978-952-64-0077-8 | |
dc.type.dcmitype | text | en |
dc.type.ontasot | Doctoral dissertation (article-based) | en |
dc.type.ontasot | Väitöskirja (artikkeli) | fi |
dc.contributor.supervisor | Ylä-Jääski, Antti, Prof., Aalto University, Department of Computer Science, Finland | |
dc.opn | Pulliainen, Jouni, Prof., Finnish Meteorological Institute, Finland | |
dc.rev | Pulliainen, Jouni, Prof., Finnish Meteorological Institute, Finland | |
dc.rev | Li, Jonathan, Prof., University of Waterloo, Canada | |
dc.date.defence | 2020-11-24 | |
local.aalto.acrisexportstatus | checked 2020-12-21_1205 | |
local.aalto.formfolder | 2020_11_10_klo_12_16 | |
local.aalto.archive | yes |
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