Above Ground Biomass Assessment from Sentinel-2A data Using Multiple Linear Regression Analysis

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  • - - Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Isan. Khon Kaen Campus.
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Keywords: Above Ground Biomass, Sentinel-2A data, Multiple Linear Regression Analysis

Abstract

The biomass can convert to the carbon stock value by multiplying the constant value from Intergovernmental Panel on Climate Change (IPCC). At present, biomass and carbon stock assessments are of great interest. This article presents an above-ground biomass assessment from Sentinel-2A data using multiple linear regression analysis. The objective of the study was mathematical modeling with multiple linear regression analysis. The factors to be used in the analysis were (1) biomass data from in-situ measurement and allometry equation, (2) Sentinel-2A data including blue, green, red, and near-infrared bands, and (3) normalized difference vegetation index (NDVI). As a result, the factor related to above-ground biomass was NDVI. The above-ground biomass model was “Biomass = (12,281.87NDVI) - 2,682.65” with R-squared of 0.76. The above-ground biomass value of the study area was about 39.11 tons/rai.

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Published
2022-09-19
How to Cite
[1]
- -, - -, - -, - -, and - -, “Above Ground Biomass Assessment from Sentinel-2A data Using Multiple Linear Regression Analysis”, ncce27, vol. 27, pp. SGI06-1, Sep. 2022.
Section
Survey and Geographic Information System Engineering

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