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Retrieving vegetation biophysical parameters and GPP using satellite-driven LUE model in a National Park

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Abstract

The 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.

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Abbreviations

DSNP:

Dibru Saikhowa National Park

LUE:

Light use efficiency

GPP:

Gross primary production

NEE:

Net ecosystem exchange (NEE)

NDVI:

Normalized difference vegetation index

EVI:

Enhanced vegetation index

PAR:

Photosynthetically active radiation

APAR:

Absorbed PAR

LAI:

Leaf area index

fPAR:

Fraction of absorbed PAR

LCC:

Leaf chlorophyll content

CCC:

Canopy chlorophyll content

NAVI:

Normalized area vegetation index (NAVI)

LSWI:

Land surface water index

REDD+:

Reducing emissions from deforestation and forest degradation

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Acknowledgements

Authors thanks to USGS and Copernicus for providing the high-resolution Sentinel-2 satellite data.

Funding

This research was supported by the Science and Engineering Research Board (SERB, DST), project Grant No. YSS/2015/000801.

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Authors and Affiliations

  1. Department of Geoinformatics, School of Natural Resource Management, Central University of Jharkhand, Ranchi, 835222, India

    Moumita Marandi, Bikash Ranjan Parida & Surajit Ghosh

  2. International Water Management Institute (IWMI), Colombo, Sri Lanka

    Surajit Ghosh

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M.M. and B.R.P. contributed to conceptualization, methodology, software, analysis, visualization, writing—original draft, review, and editing. S.G. contributed to software, visualization, writing—original draft, review, and editing.

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Correspondence to Bikash Ranjan Parida.

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Marandi, M., Parida, B.R. & Ghosh, S. Retrieving vegetation biophysical parameters and GPP using satellite-driven LUE model in a National Park. Environ Dev Sustain 24, 9118–9138 (2022). https://doi.org/10.1007/s10668-021-01815-0

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