Retrieving vegetation biophysical parameters and GPP [Gross Primary Production] using satellite-driven LUE [Light Use Efficiency] model in a national park

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cg.coverage.countryIndia
cg.coverage.iso3166-alpha2IN
cg.coverage.regionSouthern Asia
cg.coverage.subregionAssam
cg.coverage.subregionDibru Saikhowa National Park
cg.creator.identifierSurajit Ghosh: 0000-0002-3928-2135en
cg.identifier.doihttps://doi.org/10.1007/s10668-021-01815-0en
cg.identifier.iwmilibraryH050796en
cg.isijournalISI Journalen
cg.issn1387-585Xen
cg.issue7en
cg.journalEnvironment, Development and Sustainabilityen
cg.reviewStatusPeer Reviewen
cg.volume24en
dc.contributor.authorMarandi, M.en
dc.contributor.authorParida, B. R.en
dc.contributor.authorGhosh, Surajiten
dc.date.accessioned2021-11-30T21:50:09Zen
dc.date.available2021-11-30T21:50:09Zen
dc.identifier.urihttps://hdl.handle.net/10568/116415
dc.titleRetrieving vegetation biophysical parameters and GPP [Gross Primary Production] using satellite-driven LUE [Light Use Efficiency] model in a national parken
dcterms.abstractThe terrestrial biosphere plays an active role in governing the climate system by regulating carbon exchange between the land and the atmosphere. Analysis of vegetation biophysical parameters and gross primary production (GPP) makes it convenient to monitor vegetation's health. A light use efficiency (LUE) model was employed to estimate daily GPP from satellite-driven data and environmental factors. The LUE model is driven by four major variables, namely normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and moisture for which both satellite-based and ERA5-Land data were applied. In this study, the vegetation health of Dibru Saikhowa National Park (DSNP) in Assam has been analyzed through vegetation biophysical and biochemical parameters (i.e., NDVI, EVI, LAI, and chlorophyll content) using Sentinel-2 data. Leaf area index (LAI) varied between 1 and 5.2, with healthy forests depicted LAI more than 2.5. Daily GPP was estimated for January (winter) and August (monsoon) 2019 for tropical evergreen and deciduous forest types. A comparative analysis of GPP for two seasons has been performed. In January, GPP was found to be 3.6 gC m-2 day-1, while in August, GPP was 5 gC m-2 day-1. The outcome of this study may be constructive to forest planners to manage the National Park so that net carbon sink may be attained in DSNP.en
dcterms.accessRightsLimited Access
dcterms.available2021-09-14en
dcterms.bibliographicCitationMarandi, M.; Parida, B. R.; Ghosh, Surajit. 2022. Retrieving vegetation biophysical parameters and GPP [Gross Primary Production] using satellite-driven LUE [Light Use Efficiency] model in a national park. Environment, Development and Sustainability, 24(7):9118-9138. [doi: https://doi.org/10.1007/s10668-021-01815-0]en
dcterms.extent9118-9138en
dcterms.issued2022-07en
dcterms.languageen
dcterms.licenseCopyrighted; all rights reserved
dcterms.publisherSpringeren
dcterms.subjectnormalized difference vegetation indexen
dcterms.subjectphotosynthetically active radiationen
dcterms.subjectair temperatureen
dcterms.subjectmoistureen
dcterms.subjectleaf area indexen
dcterms.subjectland useen
dcterms.subjectland coveren
dcterms.subjectnational parksen
dcterms.subjectsatellite observationen
dcterms.subjectmoderate resolution imaging spectroradiometeren
dcterms.subjectmodelsen
dcterms.typeJournal Article

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