Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/78854
Type: Artigo de periódico
Title: Coffee Crop's Biomass and Carbon Stock Estimation With Usage of High Resolution Satellites Images
Author: Coltri, PP
Zullo, J
Goncalves, RRD
Romani, LAS
Pinto, HS
Abstract: Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee's biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created.
Subject: Biophysical properties measurement
coffee Arabica
GeoEye-1
vegetation index
Country: EUA
Editor: Ieee-inst Electrical Electronics Engineers Inc
Rights: fechado
Identifier DOI: 10.1109/JSTARS.2013.2262767
Date Issue: 2013
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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