Anderson Soares

Anderson Soares

PhD | Senior Geospatial data scientist | Earth Monitoring | Spatiotemporal Analysis | Python

Cognizant

Bayer Crop Science

Biography

Hi! I am Dr. Anderson Soares, a senior geospatial data scientist with extensive experience in remote sensing with focus in image processing. I hold a Master of Science in Geodetic Sciences and Geoinformatics (UFPE, 2015) and a PhD in Remote Sensing (INPE, 2019).

I have experience in using optical remote sensing data such as LANDSAT, Sentinel, Planet, CBERS, and Venμs to extract valuable insights for agricultural practices. My expertise encompasses:

  • Spatiotemporal analysis of remote sensing data for vegetation studies.
  • Development of predictive models for mapping and monitoring vegetation health.
  • Automation of spatial analysis processes using tools such as Python, geopandas, pandas, gdal, rasterio, and pysal.

I am a highly motivated professional with a thirst for knowledge. Currently, I focus on exploring new technologies such as spatiotemporal analysis, Artificial Intelligence (AI), geospatial Big Data, time series analysis, and radiometric and atmospheric corrections.

Interests
  • Remote Sensing
  • Artificial Intelligence
  • Geospatial Analysis
  • Earth observation Big Data
  • Python
Education

  • PhD in Remote Sensing, 2019

    Brazilian Institute for Space Research

  • Master in Geodetic Sciences and Geoinformation Technology, 2015

    Federal University of Pernambuco

  • Advanced Course in Geoprocessing, 2012

    Federal Institute for Education Science and Technology of Paraíba

Skills

Technical
Python
Data Science
SQL
Time Series Analysis
Hobbies
Biking
Photography
Movies

Experience

 
 
 
 
 
Senior Data Scientist
Bayer Crop Science Per Cognizant Brazil
January 2021 – Present Remote
Responsible for the development of workflows and frameworks for subfield monitoring to provide agronomic insights and precriptive actions.
 
 
 
 
 
Research Collaborator
Brazilian National Institute For Space Research (INPE)
June 2019 – December 2020 São José dos Campos
Developed and explored new techniques for land use and land cover mapping based on satellite imagery time series. Developed the stmetrics package.
 
 
 
 
 
CO-Founder / CKO
Nitentech Tecnologia Da Informação Ltda
December 2018 – November 2020 São Paulo
Chief of knowledge operations, responsible for the development of the system, from database modelling to UI design
 
 
 
 
 
GIS SPECIALIST
INCITI – Pesquisa e inovação para as cidades
November 2013 – April 2014 Recife
Responsible to provide spatial analysis and data management to support urban planning decisions.

Recent Publications

Anderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca, Hugo Bendini (2020). Simple Nonlinear Iterative Temporal Clustering. TGRS.

Cite DOI

Anderson Reis Soares, Hugo Bendini, Daiane Vaz, Tatiana Dias Tardelli Uehara, Alana Kasahara Neves, Sarah Lechler, Thales Sehn Körting, Leila Maria Garcia Fonseca (2020). Stmetrics: A Python Package for Satellite Image Time-Series Feature Extraction. In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium.

Cite Code DOI

Anderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca, Alana Kasahara Neves (2020). An Unsupervised Segmentation Method For Remote Sensing Imagery Based On Conditional Random Fields. In 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS).

Cite DOI

Anderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca (2018). Improvements of the divide and segment method for parallel image segmentation. Brazilian Journal of Cartography.

Cite DOI

Anderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca (2013). First experiments using the image foresting transform (IFT) algorithm for segmentation of remote sensing imagery. In GEOBIA 2016 Conference.

Cite DOI

Contact

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