Raian V. Maretto is PhD in Applied Computing (2020) and MSc in Remote Sensing (2011) by the Instituto Nacional de Pesquisas Espaciais (Brazilian National Institute for Space Research, INPE), and Bachelor's in Computer Science (2008) by the Universidade Federal de Ouro Preto (Federal University of Ouro Preto, UFOP). With the main expertise in the application of Deep Learning, Machine Learning, and Data Mining methods to the analysis of geospatial data. He worked as a consultant and research assistant at INPE, in the context of the FIP (Forest Investment Program) Cerrado and the MSA (Monitoring the Amazon through Satellite Imagery) projects, developing methods based on Deep Learning to automatically map deforested areas, agriculture and vegetation types in the Brazilian Cerrado and Amazon biomes. He has more than 10 years of experience in the development of Geographic Information Systems (GIS) and Remote Sensing image processing algorithms and software, participating on large software development teams following agile software development methods and working with languages like C++, Python, Lua, R, and Java. He also has participated in the development of the following systems: TerraLib library, TerraView, TerraME, GeoDMA, and recently the DeepGeo package. Main research interests are on Remote Sensing data analysis, integration of images from different sensors and natures, computer vision, machine learning, data mining, and pattern recognition.
Expertise
Earth and Planetary Sciences
- Cerrado
- Cartography
- Time Series
- Learning
- Biome
- Map
- Model
Computer Science
- Models
Organisations
I am PhD in Applied Computing (2020) and MSc in Remote Sensing (2011) by the Instituto Nacional de Pesquisas Espaciais (Brazilian National Institute for Space Research, INPE), and a Bachelor's in Computer Science (2008) by the Universidade Federal de Ouro Preto (Federal University of Ouro Preto, UFOP). With the main expertise in the application of Deep Learning, Machine Learning, and Data Mining methods to the analysis of geospatial data. He worked as a consultant and research assistant at INPE, in the context of the FIP (Forest Investment Program) Cerrado and the MSA (Monitoring the Amazon through Satellite Imagery) projects, developing methods based on Deep Learning to automatically map deforested areas, agriculture, and vegetation types in the Brazilian Cerrado and Amazon biomes. He has more than 10 years of experience in the development of Geographic Information Systems (GIS) and Remote Sensing image processing algorithms and software, participating on large software development teams following agile software development methods and working with languages like C++, Python, Lua, R, and Java. He also has participated in the development of the following systems: TerraLib library, TerraView, TerraME, GeoDMA, and recently the DeepGeo package. My main research interests are on Remote Sensing data analysis, integration of images from different sensors and natures, computer vision, machine learning, data mining, and pattern recognition.
Publications
2025
2024
2023
Research profiles
Affiliated study programs
Courses academic year 2024/2025
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses academic year 2023/2024
Address

University of Twente
Langezijds (building no. 19), room 1320
Hallenweg 8
7522 NH Enschede
Netherlands
University of Twente
Langezijds 1320
P.O. Box 217
7500 AE Enschede
Netherlands