Learning Centre

Environment Awareness with Hyperspectral LiDAR Technologies

 |  Login

Show simple item record

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


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search archive


Advanced Search

article-iconSubmit a publication

Browse

Statistics