dc.contributor.author | Riihiaho, Kimmo A. | |
dc.contributor.author | Rossi, Tuomo | |
dc.contributor.author | Pölönen, Ilkka | |
dc.contributor.editor | Jiang, J. | |
dc.contributor.editor | Shaker, A. | |
dc.contributor.editor | Zhang, H. | |
dc.date.accessioned | 2022-08-19T10:39:35Z | |
dc.date.available | 2022-08-19T10:39:35Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Riihiaho, K. A., Rossi, T., & Pölönen, I. (2022). HyperBlend : Simulating Spectral Reflectance and Transmittance of Leaf Tissue with Blender. In J. Jiang, A. Shaker, & H. Zhang (Eds.), <i>XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission III</i> (V-3-2022, pp. 471-476). Copernicus Publications. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. <a href="https://doi.org/10.5194/isprs-annals-V-3-2022-471-2022" target="_blank">https://doi.org/10.5194/isprs-annals-V-3-2022-471-2022</a> | |
dc.identifier.other | CONVID_150900468 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/82728 | |
dc.description.abstract | Remotely sensing vegetation condition and health hazards requires modeling the connection of plants’ biophysical and biochemical parameters to their spectral response. Even though many models exist already, the field suffers from lack of access to program code. In this study, we will assess the feasibility of open-source 3D-modeling and rendering software Blender in simulating hyperspectral reflectance and transmittance of leaf tissue to serve as a base for a more advanced large-scale simulator. This is the first phase of a larger HyperBlend project, which will provide a fully open-source, canopy scale leaf optical properties model for simulating remotely sensed hyperspectral images. Test results of the current HyperBlend model show good agreement with real-world measurements with root mean squared error around 1‰. The program code is available at https://github.com/silmae/ hyperblend. | en |
dc.format.extent | 711 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Copernicus Publications | |
dc.relation.ispartof | XXIV ISPRS Congress “Imaging today, foreseeing tomorrow”, Commission III | |
dc.relation.ispartofseries | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences | |
dc.rights | CC BY 4.0 | |
dc.subject.other | leaf optical properties model | |
dc.subject.other | simulation | |
dc.subject.other | ray tracing | |
dc.subject.other | hyperspectral imaging | |
dc.subject.other | remote sensing | |
dc.subject.other | open source | |
dc.title | HyperBlend : Simulating Spectral Reflectance and Transmittance of Leaf Tissue with Blender | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-202208194267 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Computing, Information Technology and Mathematics | fi |
dc.contributor.oppiaine | Tutkintokoulutus | fi |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Laskennallinen tiede | fi |
dc.contributor.oppiaine | Computing, Information Technology and Mathematics | en |
dc.contributor.oppiaine | Degree Education | en |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.contributor.oppiaine | Computational Science | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 471-476 | |
dc.relation.issn | 2194-9042 | |
dc.relation.volume | V-3-2022 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © Author(s) 2022 | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | International Society for Photogrammetry and Remote Sensing Congress | |
dc.relation.grantnumber | 327862 | |
dc.subject.yso | kasvillisuus | |
dc.subject.yso | 3D-mallinnus | |
dc.subject.yso | kaukokartoitus | |
dc.subject.yso | reflektanssi | |
dc.subject.yso | simulointi | |
dc.subject.yso | hyperspektrikuvantaminen | |
dc.subject.yso | avoin lähdekoodi | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p1756 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p26739 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2521 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p38165 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p4787 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p39290 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p17089 | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.5194/isprs-annals-V-3-2022-471-2022 | |
dc.relation.funder | Research Council of Finland | en |
dc.relation.funder | Suomen Akatemia | fi |
jyx.fundingprogram | Academy Project, AoF | en |
jyx.fundingprogram | Akatemiahanke, SA | fi |
jyx.fundinginformation | This study was funded by Academy of Finland (327862). | |
dc.type.okm | A4 | |