@inproceedings{0e3c7d2959e446d9a75d026f61b0e4be,
title = "Red-edge ratio Normalized Vegetation Index for remote estimation of green biomass",
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).",
keywords = "Green Biomass, Hyper Spectral imagery, Red-edge Ratio, Sentinel-2",
author = "Jisung Chang and Maxim Shoshany",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7729340",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "1337--1339",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "United States",
}