Narrow band based and broadband derived vegetation indices using Sentinel-2 Imagery to estimate vegetation biomass

Imran, A.B.; Khan, K.; Ali, N.; Ahmad, N.; Ali, A.; Shah, K.

doi:10.22034/GJESM.2020.01.08

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

¹ Department of Forestry and Range Management, PMAS Arid Agriculture University, Rawalpindi, Pakistan

² Institute of Environmental Science and Engineering, National University of Science and Technology, Pakistan

³ Department of Forestry and Wildlife Management, University of Haripur, Pakistan

⁴ Ministry of Forestry, Environment and Wildlife, Khyber Pukhtunkhwa, Pakistan

https://doi.org/10.22034/GJESM.2020.01.08

Abstract

Forest’s ecosystem is one of the most important carbon sink of the terrestrial ecosystem. Remote sensing technology provides robust techniques to estimate biomass and solve challenges in forest resource assessment. The present study explored the potential of Sentinel-2 bands to estimate biomass and comparatively analyzed of red-edge band based and broadband derived vegetation indices. Broadband indices include normalized difference vegetation index, modified simple ratio and atmospherically resistant VI. Whereas, red-edge band indices include two red-edge normalized difference vegetation index and sentinel-2 red-edge position. Results showed that red-edge band derived spectral indices have performed better than the Broadband indices. The coefficient of correlation for normalized difference vegetation index, modified simple ratio and atmospherically resistant-VI was 0.51, 0.44 and 0.31 respectively, On the other hand, red-edge band indices showed higher correlation of R² 0.62, 0.64 and 0.55, respectively. Similarly, in stepwise regression red-edge normalized difference vegetation index (using band 6) was selected in final model (as overall R² of the model was 0.60) while all other indices were removed because they have non-significant relationship with the biomass. Accuracy assessment shown the red-edge index has highest R² (0.64) and least error of (31.29 t/ha) and therefore the study concluded that narrowband indices performed better to estimate biomass and thus final model contained only red-edge index to predict biomass over the study area. The study suggests that more in-depth research should be conducted to explore further properties of red-edge indices for vegetation parameters prediction.

Graphical Abstract

Highlights

Above ground biomass can be efficiently quantified by use of sentinel-2 sensor which provides high spatial and temporal resolution and frequent revisit time;
Sentinel-2 spectral indices computed from red-edge wavelength region can provide best proxy information for Above ground biomass prediction;
Red edge bands of sentinel-2 to estimate forest AGB should contribute to the regional estimates of carbon emissions measurement, reporting and verification.

Keywords

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Global Journal of Environmental Science and Management

Narrow band based and broadband derived vegetation indices using Sentinel-2 Imagery to estimate vegetation biomass

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Volume 6, Issue 1 - Serial Number 21
January 2020
Pages 97-108

Narrow band based and broadband derived vegetation indices using Sentinel-2 Imagery to estimate vegetation biomass

References

References

Letters to Editor

Send comment about this article

Volume 6, Issue 1 - Serial Number 21January 2020Pages 97-108

Volume 6, Issue 1 - Serial Number 21
January 2020
Pages 97-108