DocumentCode :
2227232
Title :
Carbon stock estimation in coffee crops using high resolution satellites
Author :
Coltri, P.P. ; Zullo, J., Jr. ; Gonçalves, R. R V ; Romani, L.A.S. ; Pinto, H.S.
Author_Institution :
Center of Meteorol. & Climate Researches Appl. to Agric. (CEPAGRI), Univ. of Campinas (UNICAMP), Campinas, Brazil
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
6657
Lastpage :
6660
Abstract :
According to IPCC, the increase of greenhouse gases emissions (GHG) in atmosphere is causing global warming, and this phenomenon could increase global temperature. In tropical areas of Brazil, the air temperature is supposed to increase from 1.1°C to 6.4°C causing large impacts in agricultures areas, including coffee production regions. The main objective of this paper was quantify the biomass of Arabica coffee trees above-ground (and carbon stock) using the vegetation index NDVI based on a high resolution image (Geoeye-1) and biophysical measures of coffee trees. In addition, the study aimed to establish an empirical relationship between biophysical measures of Arabica coffee trees, remote sensing data and dry biomass. The study was conducted in the south of Minas Gerais, which is the main producing region of Arabica coffee in Brazil. It was conclude that NDVI based on images of high spatial resolution, such as from Geoeye-1 satellite, has a strong correlation with dry biomass and carbon sink, showing that it is possible to estimate the carbon stock of coffee crops using remote sensing data without destructive methods.
Keywords :
crops; vegetation mapping; Arabica coffee tree biomass; Brazil; Geoeye-1; Minas Gerais; NDVI; above ground biomass; carbon stock estimation; coffee crops; coffee production regions; coffee tree biophysical measures; dry biomass; global warming; greenhouse gases emissions; high resolution images; high resolution satellites; normalized difference vegetation index; remote sensing data; Biomass; Carbon; Correlation; Remote sensing; Satellites; Vegetation; Vegetation mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352072
Filename :
6352072
Link To Document :
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