I am a biologist and I hold a PhD in Biological Sciences and an MSc in Remote Sensing and GIS applications. I work as an assistant researcher for CONICET at the Mario Gulich Institute of the Argentinian Space Agency (CONAE) in Córdoba, Argentina. My research is focused on uncovering environmental drivers of vector-borne disease outbreaks. I am mostly interested in those environmental features that can be derived by means of satellite image analysis, remote sensing time series and GIS-based techniques.

I am a strong advocate for OSGeo and free and open source software for geo-spatial (FOSS4G). Moreover, I am part of the GRASS GIS Development team. I have also volunteered as a mentor for GRASS GIS in the Google Code-In contest introducing high school students into the Open Source world.


  • Remote sensing time series
  • Image analysis
  • GIS
  • SDM
  • Vector-borne diseases
  • Free and Open Source Software


  • MSc in Spatial Applications for Early Warning and Response to Emergencies, 2015

    National University of Córdoba

  • PhD in Biological Sciences, 2012

    National University of Río Cuarto

  • Biologist (5-year course of studies), 2005

    National University of Río Cuarto


Remote sensing










Scientific writing


Recent Publications

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Spatial analysis of Aedes aegypti activity for public health surveillance

In Córdoba city the surveillance of Aedes aegypti, the vector of Dengue, Zika and Chikungunya in Argentina, has been done regularly …

Time Series Clustering Applied to Eco-Epidemiology: the case of Aedes aegypti in Córdoba, Argentina

Dengue fever is one of the most widespread vector-borne diseases in the world. The virus causing it is transmitted by Aedes aegypti …



Assistant Researcher


July 2018 – Present Córdoba, Argentina

Responsibilities include:

  • Research on the environmental drivers of vector-borne diseases
  • Supervision of MSc and PhD students
  • Teaching

Postdoc researcher

ITC - University of Twente

July 2016 – June 2018 Enschede, The Netherlands

Responsibilities include:

  • Research in image analysis for Health Geography
  • Supervision of MSc and PhD students

Recent & Upcoming Talks

Analyzing space-time satellite data for disease ecology applications with GRASS GIS and R stats

Workshop at OpenGeoHub Summer School 2019 about the analysis of space-time satellite data for disease ecology applications with GRASS GIS and R stats.

Recent Posts

pymodis, GDAL and GRASS GIS: A FOSS4G example to build time series of MODIS data

Recently, the National Aeronautics and Space Administration (NASA) has re-processed all the MODIS archive and made available the sixth version for all land products. In this post, I share a script that combines different FOSS4G tools to download, mosaic, re-project, subset, import, apply quality assessment flags and build a time series of MODIS LST daily products. First, we use the pymodis tool modis_download to automatically download 4 tiles of the MOD11A1 product for the period 2010-2016.

How to aggregate daily data into MODIS-like 8 day aggregation pattern?

Several MODIS products come in “8-day” compositions. Suppose we have daily data and we want to aggregate it with this MODIS-like granularity. How can we achieve that? First idea would be to use the great t.rast.aggregate module in GRASS GIS with granularity="8 days”. But this presents a problem. It does not re-start every year, but aggregates the whole series with 8-day granularity, not considering the year. Meanwhile, MODIS 8-day products re-start the aggregation every January 1st.