Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91055
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.creatorLi, Xen_US
dc.creatorLiang, HYen_US
dc.creatorCheng, WMen_US
dc.date.accessioned2021-09-09T03:39:18Z-
dc.date.available2021-09-09T03:39:18Z-
dc.identifier.issn1569-8432en_US
dc.identifier.urihttp://hdl.handle.net/10397/91055-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 The Author(s). Published by Elsevier B.V.en_US
dc.rightsThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Xin Li, Hongyu Liang, Weiming Cheng, Evaluation and comparison of light use efficiency models for their sensitivity to the diffuse PAR fraction and aerosol loading in China, International Journal of Applied Earth Observation and Geoinformation, Volume 95, 2021, 102269 is available at https://doi.org/10.1016/j.jag.2020.102269.en_US
dc.subjectPAR(dif) fractionen_US
dc.subjectAerosol optical depth (AOD)en_US
dc.subjectGross primary productivity (GPP)en_US
dc.subjectSensitivityen_US
dc.titleEvaluation and comparison of light use efficiency models for their sensitivity to the diffuse PAR fraction and aerosol loading in Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume95en_US
dc.identifier.doi10.1016/j.jag.2020.102269en_US
dcterms.abstractThe diffuse photosynthetically active radiation (PAR(dif)) is highly related to the gross primary productivity (GPP) of vegetation and can enhance the photosynthetic rate of shaded leaves. The PAR(dif) is mainly influenced by aerosols on clear sky days. To explore the impacts of the PAR(dif) fraction and aerosol loading on the accuracy of GPP estimations, we evaluated and compared the sensitivity of one-leaf and two-leaf light use efficiency (LUE) models (MOD17 and TL-LUE models) to the PAR(dif) fraction and aerosol optical depth (AOD) using satellite data and measurements at ChinaFLUX sites in China from 2003 to 2010. The estimated GPP from two models (GPP_MOD and GPP_TL) showed systematic underestimations when compared with the measured GPP at ChinaFLUX sites (GPP_FLUX). In addition, the underestimation of the GPP estimated by the two models was larger in months with high PAR(dif) fractions than in months with low PAR(dif) fractions at most sites. The TL-LUE model exhibited better performance than the MOD17 model with reduced underestimation and root-mean-square error (RMSE) values when the PAR(dif) fraction was greater than 0.7 or 0.8. When the PAR(dif) fraction was low, the TL-LUE model reduced the overestimation or increased the underestimations of GPP compared with the MOD17 model depending on the site. Both MOD17 and TL-LUE exhibited higher underestimations of GPP at high AOD values than at low AOD values at most sites. The TL-LUE model exhibited an overall better performance than MOD17 under high AOD. The overestimation also occurred for low AOD, which was consistent with that for low PARdif fractions. Therefore, the two LUE models showed dynamic performance with variations in the PAR(dif) fraction and AOD, which should be considered in the application and further improvement of GPP models.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of applied earth observation and geoinformation, Mar. 2021, v. 95, 102269en_US
dcterms.isPartOfInternational journal of applied earth observation and geoinformationen_US
dcterms.issued2021-03-
dc.identifier.isiWOS:000601163600002-
dc.identifier.eissn1872-826Xen_US
dc.identifier.artn102269en_US
dc.description.validate202109 bchyen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.pubStatusPublisheden_US
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