2016Unpublished venueRequires access

Red-edge ratio Normalized Vegetation Index for remote estimation of green biomass

Jisung Geba Chang, Maxim Shoshany

Open publisher page 9 citations

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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What this paper is about

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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Available 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).

Key concepts: Enhanced vegetation index, Vegetation Index, Red edge, Vegetation (pathology), Biomass (ecology), Saturation (graph theory), Index (typography), Environmental science

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