🌱 Researcher in remote sensing, evapotranspiration, agricultural monitoring, machine learning.
📍 Belo Horizonte, MG, Brazil
🔗 www.filgueirasr.com.br
I am an Agricultural Engineer and researcher focused on modeling evapotranspiration, remote sensing, and meteorological data analysis. I develop computational solutions to optimize water use in agriculture by combining satellite data, machine learning, and climate time series.
An R package to download and process data from INMET's Automatic Weather Stations (AWS) in Brazil, with a focus on estimating reference evapotranspiration (ETo). Available on CRAN.
A R package for performing crop water balance analyses based on the Thornthwaite and Mather (1955) methodology. The cropDemand package allows customization of the available water capacity (AWC) parameter to reflect different crop requirements, and supports applications across all regions of Brazil. It integrates TerraClimate data (http://www.climatologylab.org/terraclimate.html). Available on CRAN.
An R package that enables climate-based crop zoning in Brazil by analyzing air temperature patterns using TerraClimate data. Available on CRAN.
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Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing
PLOS ONE, 2021
Monthly ETo estimation across Brazil using machine learning and NASA’s MOD16 remote sensing product.
Read the article -
ETo-Brazil: A Daily Gridded Reference Evapotranspiration Data Set for Brazil
Water Resources Research, 2020
Development of a daily, spatially distributed reference evapotranspiration dataset for Brazil.
Read the article
More publications are available in the articles section of my website.
- ETo-Brazil Dataset
A daily ETo dataset for Brazil, developed using machine learning and remote sensing.
Available on Mendeley Data
This profile is continuously updated with my latest open-source projects and publications.