• 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