Red-edge ratio Normalized Vegetation Index for remote estimation of green biomass
Jisung Geba Chang, Maxim Shoshany
Abstract
Jisung Geba Chang, Maxim Shoshany
Abstract
Many vegetation indices have been developed for the estimation of green biomass over the last three decades. The Normalized Vegetation Index is the most well-known index; however, it has a saturation problem at moderate to high vegetation densities. The red-edge region (700-740nm) has been introduced to increase sensitivity at these moderate to high vegetation densities. We propose a new vegetation index for biomass estimation of short vegetation, to improve the saturation problem using the red-edge bands. By using the Hyper-spectral image data of Maize and Soybean, the nine well-known vegetation indices are evaluated and compared with the proposed index. For validation of the proposed model using Sentinel-2 data, Pereira allometric data is used (r-square is 0.765).
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Many vegetation indices have been developed for the estimation of green biomass over the last three decades. The Normalized Vegetation Index is the most well-known index; however, it has a saturation problem at moderate to high vegetation densities. The red-edge region (700-740nm) has been introduced to increase sensitivity at these moderate to high vegetation densities. We propose a new vegetation index for biomass estimation of short vegetation, to improve the saturation problem using the red-edge bands. By using the Hyper-spectral image data of Maize and Soybean, the nine well-known vegetation indices are evaluated and compared with the proposed index. For validation of the proposed model using Sentinel-2 data, Pereira allometric data is used (r-square is 0.765).
Key concepts: Enhanced vegetation index, Vegetation Index, Red edge, Vegetation (pathology), Biomass (ecology), Saturation (graph theory), Index (typography), Environmental science