Angelica Giarolla

Dr. Angelica Giarolla

orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 February 2017 in Theoretical and Applied Climatology
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Journal Article
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ALAndre Lyra
Andre Lyra
Priscila TavaresPriscila Tavares
Priscila Tavares
Sin Chan ChouSin Chan Chou
Sin Chan Chou
GSGustavo Sueiro
Gustavo Sueiro
CDClaudine Dereczynski
Claudine Dereczynski
AGAngelica Giarolla
Angelica Giarolla

1 November 2018 in Energy Research & Social Science
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Journal Article
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Lira Luz Benites LazaroLira Luz Benites Lazaro
Lira Luz Benites Lazaro
Leandro Luiz GiattiLeandro Luiz Giatti
Leandro Luiz Giatti
AGAngelica Giarolla
Angelica Giarolla

6 November 2017 in Regional Environmental Change
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Priscila TavaresPriscila Tavares
Priscila Tavares
AGAngelica Giarolla
Angelica Giarolla
Sin Chan ChouSin Chan Chou
Sin Chan Chou
ASAdan Juliano de Paula Silva
Adan Juliano de Paula Silva
ALAndré de Arruda Lyra
André de Arruda Lyra

27 August 2012 in Remote Sensing
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Journal Article
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TBTiago Bernardes
Tiago Bernardes
MMMaurício Alves Moreira
Maurício Alves Moreira
MAMarcos Adami
Marcos Adami
AGAngelica Giarolla
Angelica Giarolla
BRBernardo Rudorff
Bernardo Rudorff
Coffee is the second most valuable traded commodity worldwide. Brazil is the world’s largest coffee producer, responsible for one third of the world production. A coffee plot exhibits high and low production in alternated years, a characteristic so called biennial yield. High yield is generally a result of suitable conditions of foliar biomass. Moreover, in high production years one plot tends to lose more leaves than it does in low production years. In both cases some correlation between coffee yield and leaf biomass can be deduced which can be monitored through time series of vegetation indices derived from satellite imagery. In Brazil, a comprehensive, spatially distributed study assessing this relationship has not yet been done. The objective of this study was to assess possible correlations between coffee yield and MODIS derived vegetation indices in the Brazilian largest coffee-exporting province. We assessed EVI and NDVI MODIS products over the period between 2002 and 2009 in the south of Minas Gerais State whose production accounts for about one third of the Brazilian coffee production. Landsat images were used to obtain a reference map of coffee areas and to identify MODIS 250 m pure pixels overlapping homogeneous coffee crops. Only MODIS pixels with 100% coffee were included in the analysis. A wavelet-based filter was used to smooth EVI and NDVI time profiles. Correlations were observed between variations on yield of coffee plots and variations on vegetation indices for pixels overlapping the same coffee plots. The vegetation index metrics best correlated to yield were the amplitude and the minimum values over the growing season. The best correlations were obtained between variation on yield and variation on vegetation indices the previous year (R = 0.74 for minEVI metric and R = 0.68 for minNDVI metric). Although correlations were not enough to estimate coffee yield exclusively from vegetation indices, trends properly reflect the biennial bearing effect on coffee yield.

1 October 2018 in Journal of Cleaner Production
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Journal Article
Closed access
Lira Luz Benites LazaroLira Luz Benites Lazaro
Lira Luz Benites Lazaro
LGLeandro Giatti
Leandro Giatti
AGAngelica Giarolla
Angelica Giarolla

1 February 2018 in Agricultural Systems
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Journal Article
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Minella MartinsMinella Martins
Minella Martins
JTJavier Tomasella
Javier Tomasella
DRDaniel Andrés Rodríguez
Daniel Andrés Rodríguez
RARegina C.S. Alvalá
Regina C.S. Alvalá
AGAngelica Giarolla
Angelica Giarolla
GPGustavo L.N. Pinto
Gustavo L.N. Pinto