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

Jisung Chang, Maxim Shoshany

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus 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).

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages1337-1339
Number of pages3
ISBN (Electronic)9781509033324
DOIs
StatePublished - 1 Nov 2016
Externally publishedYes
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • Green Biomass
  • Hyper Spectral imagery
  • Red-edge Ratio
  • Sentinel-2

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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