dc.contributor.author | Erkkilä, Anna-Leena | |
dc.contributor.author | Pölönen, Ilkka | |
dc.contributor.author | Lindfors, A. | |
dc.contributor.author | Honkavaara, E. | |
dc.contributor.author | Nurminen, K. | |
dc.contributor.author | Näsi, R. | |
dc.contributor.editor | Honkavaara, E. | |
dc.contributor.editor | Hu, B. | |
dc.contributor.editor | Karantzalos, K. | |
dc.contributor.editor | Liang, X. | |
dc.contributor.editor | Müller, R. | |
dc.contributor.editor | Nocerino, E. | |
dc.contributor.editor | Pölönen, Ilkka | |
dc.contributor.editor | Rönnholm, P. | |
dc.date.accessioned | 2017-11-07T11:48:03Z | |
dc.date.available | 2017-11-07T11:48:03Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Erkkilä, A.-L., Pölönen, I., Lindfors, A., Honkavaara, E., Nurminen, K., & Näsi, R. (2017). Choosing of Optimal Reference Samples for Boreal Lake Chlorophyll A Concentration Modeling Using Aerial Hyperspectral Data. In E. Honkavaara, B. Hu, K. Karantzalos, X. Liang, R. Müller, E. Nocerino, I. Pölönen, & P. Rönnholm (Eds.), <i>ISPRS SPEC3D 2017 : Frontiers in Spectral imaging and 3D Technologies for Geospatial Solutions</i> (pp. 39-46). International Society for Photogrammetry and Remote Sensing. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W3. <a href="https://doi.org/10.5194/isprs-archives-XLII-3-W3-39-2017" target="_blank">https://doi.org/10.5194/isprs-archives-XLII-3-W3-39-2017</a> | |
dc.identifier.other | CONVID_27317928 | |
dc.identifier.other | TUTKAID_75510 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/55788 | |
dc.description.abstract | Optical remote sensing has potential to overcome the limitations of point estimations of lake water quality by providing spatial and
temporal information. In open ocean waters the optical properties are dominated by phytoplankton density, while the relationship
between color and the constituents is more complicated in inland waters varying regionally and seasonally. Concerning the difficulties
relating to comprehensive modeling of complex inland and coastal waters, the alternative approach is considered in this paper: the
raw digital numbers (DN) recorded using aerial remote hyperspectral sensing are used without corrections and derived by means of
regression modeling to predict Chlorophyll a (Chl-a) concentrations using in situ reference measurements. The target of this study
is to estimate which number of local reference measurements is adequate for producing reliable statistical model to predict Chl-a
concentration in complex lake water ecosystem. Based on the data collected from boreal lake Lohjanjarvi, the effect of standard ¨
deviation of Chl-a concentration of reference samples and their local clustering on predictability of model increases when number of
reference samples or bands used as model variables decreases. However, the 2 or 3 band models are beneficial and more cost efficient
when compared to 5 or 7 band models when the standard deviation of Chl-a concentration of reference samples is over certain level.
The simple empirical approach combining remote sensing and traditional sampling may be feasible for regional and seasonal retrieval
of Chl-a concentration distributions in complex ecosystems, where the comprehensive models are difficult or even impossible to derive. | |
dc.language.iso | eng | |
dc.publisher | International Society for Photogrammetry and Remote Sensing | |
dc.relation.ispartof | ISPRS SPEC3D 2017 : Frontiers in Spectral imaging and 3D Technologies for Geospatial Solutions | |
dc.relation.ispartofseries | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | |
dc.relation.uri | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3-W3/39/2017/isprs-archives-XLII-3-W3-39-2017.pdf | |
dc.subject.other | aerial remote sensing | |
dc.subject.other | lake water color | |
dc.subject.other | water quality monitoring | |
dc.subject.other | hyperspectral imaging | |
dc.subject.other | chlorophyll a | |
dc.title | Choosing of Optimal Reference Samples for Boreal Lake Chlorophyll A Concentration Modeling Using Aerial Hyperspectral Data | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-201711024122 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2017-11-02T13:15:39Z | |
dc.type.coar | conference paper | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 39-46 | |
dc.relation.issn | 1682-1750 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © Authors, 2017. This is an open access article distributed under the terms of the Creative Commons License. | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.conference | Congress of the International Society for Photogrammetry and Remote Sensing | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.5194/isprs-archives-XLII-3-W3-39-2017 | |