About us

The Brazilian Team has been built as a collaborative and multidisciplinary group of biologists, citizen-scientists, communication professionals, ecologists, economists, engineers (agronomists, data, electrical, forestry, mechanical, robotics), environmental managers,  informaticians, and mathematicians from Brazil, Colombia, France, Germany, Spain, Portugal, UK and USA.

The destruction of the tropical rainforests is expanding faster than humans have been able to study the biodiversity. The Brazilian Team devote synergic efforts for improving the knowledge about plant and animal diversity in tropical rainforests worldwide. We use innovative technologies and solutions, carefully designed developed, and tested by us, for rapid and accurate biodiversity assessment, especially from remote or difficult to access geographic areas.

Our technologies and strategies have been applied during the XPRIZE Rainforest, a five-year competition, to enhance our global understanding of the rainforest ecosystem.  In August 2023, the Brazilian Team was announced as one of the 6 finalists of this competition, being the only team based in a tropical country and the only selected from the South Hemisphere.

Schematic Summary of Field Activities
Proposed for the XPRIZE Rainforest

Our strategies include use of drones, flying over the 100-hectare area to obtain high-definition images of plants; bioacoustic tools, to capture the sounds of the forest and identify birds, bats and amphibians; collection of hematophagous insects to identify also their animal hosts (e.g. mammals and birds); collection of water, litter and soil samples to identify fish, frogs, insects, plants and various organisms based on their DNA. Portable sequencers (“MiniONs”) will be used for quick DNA sequences in the field, and artificial intelligence tools to identify sounds and plant images.

Our strategies include:

Use of drones flying over a 100-hectares plot to obtain canopy high-definition images

Bioacoustic tools to capture the sounds of the forest, for identifying mainly insects, birds, bats and amphibians.

Collection of hematophagous insects for taxonomy identification and their animal hosts (e.g. mammals and birds)

Sampling collection of water, litter and soil to identify organisms (e.g. fish, frogs, insects, mammals, plants and others) based on their DNA traces present in the environment, and ground images collection.

Our solutions

Our main innovations rely on the use of existing tools (drones, bioacoustic devices, portable sequencers, mobile apps) and knowledge in an integrated manner, aiming to develop technologies and protocols for the rapid and replicable biodiversity assessment, based on scientific approaches comparable among different environments.

Our approaches do not require human presence inside the study area. They are based on the mobilization of previously collected vast corpus of data coming from citizen science programmes, university databases, and the knowledge of indigenous populations.    Field data collection is always done using devices such as drones and terrestrial robots.

The Brazilian Team focuses on Plants (Angiosperms, Gymnosperms, Ferns, Lycophytes, and Bryophytes) and Animals (Mammals, Birds, Reptiles, Amphibians, Fish, and Arthropods). Our techniques cover three frontlines:

Taxonomic Accuracy and Validation

We aim at generating a final species list and set of occurrences in the target study area, including the presence of exotic or invasive and threatened species, names considered doubtful due to their occurrence, etc.

Visible biodiversity

We focus on field activities using robotic samplers for arthropods and leaf litter collections, and drones for plant identification through artificial intelligence (supervised and unsupervised deep learning models), and remote sensing.

“Invisible” biodiversity

We use DNA metabarcoding from environmental samples (e.g. water, soil, leaf litter, and bulk of insects) and portable sequencers (“MiniONs”) for quick DNA sequencing in the field, and bioacoustic analyses (specially for birds, bats, insects and frogs).

Data collection using innovative technologies:

Cause minimal or no harm to the living beings and the surrounding ecosystem

Allow for a rapid and accurate representation of the multiple habitats, their composition, and structure, and

Allow biodiversity assessments in remote or human inaccessible areas.

Our technology

Unmanned Flying Laboratory

This system consists of obtaining data through drones, which fly over and collect information about tree canopies, branches, leafs, fruits flowers, nests, and eggs, allowing their identification through artificial intelligence – as well as spatially locating and quantifying them. Our solution is a novel combined hardware system and custom algorithm workflow, which collects and then, in post-processing, generates unique data fusion product deliverables incorporating several remote sensors.

DNA barcoding and metabarcoding

Allow taxa identification using  short fragments of DNA, while comparing it to a library of reference sequences. Although these approaches are more efficient for animals, it is currently being improved for plants, with satisfactory results using larger stretches of DNA and some prior knowledge of the local flora. DNA extraction and sequencing techniques are performed using backpack laboratories, including the “MinION” sequencer (measuring just a few centimeters and connecting to a computer through a USB port). We work with multiple MinIONs simultaneously for providing robust data in the field

Brazilian Team Semifinal Summary – Support from Total Energies

Brazilian Team solutions developed for the XPRIZE Rainforest

Brazilian Team Semifinal Submission for the XPRIZE Rainforest

Our team

The Brazilian Team is structured on two pillars: the scientific and the technological crew, including experts and recognized professionals, with a large experience in ecosystem restoration and scientific computational platform projects, and early career fellows (future leaders in tropical biodiversity research) and the local community citizen-scientists.

Coordinator: Vinicius Castro Souza. Researcher and professor at the Universidade de São Paulo (ESALQ-USP).

Vice-coordinator: Rafaela Campostrini Forzza. Researcher at Instituto de Pesquisas Jardim Botânico do Rio de Janeiro (JBRJ).

Meet our team members



Marco H. Terra

Marco H. Terra is the coordinator of the robotics group within the Brazilian Team. He received the Ph.D. degree in electrical engineering from the University of São Paulo (USP), São Carlos, Brazil, in 1995. He is currently a Full Professor of Electrical Engineering with USP. He has authored over 270 conference and journal papers. He has coauthored the book Robust Control of Robots: Fault-Tolerant Approaches (Springer). He is an ad hoc Referee for the Research Grants Council of Hong Kong. His research interests include filtering and control theories, fault detection and isolation problems, and robotics. He has experience in the area of Electrical Engineering, system control, mainly focusing on the following topics: robust control, robust filtering, and robotics. Prof. Terra was the Coordinator of the Robotics Committee and Brazilian Institute of Science and Technology for Cooperative Autonomous Systems Applied to Security and Environment. He is the President of the Brazilian Automation Society. He has reviewed papers for over 30 journals and to the Mathematical Reviews of the American Mathematical Society.

Gilvanio Sousa

Gilvanio Sousa is a Mechatronic Engineer who has worked for 10 years as an automation and design engineer in industrial facilities. In 2019, he obtained his MBA in industrial automation from the Polytechnic School at the University of São Paulo. He is currently working towards an M.S. degree at the Laboratory of Intelligent Systems (LASI) in the São Carlos School of Engineering at the University of São Paulo. He is interested in the following research areas: Artificial Intelligence, Robots Control, Ground Robots, Legged Robots, Model Predictive Control (MPC), and Optimal Control.


Kenny Caldas

Kenny Caldas is a researcher specializing in autonomous mobile robots. He obtained his M.S. in Electrical Engineering from the University of São Paulo in 2018 and is currently working towards a Ph.D. at the Laboratory of Intelligent Systems. During this time, he actively took part in several robotics competitions as a member of the Flying U2 team, achieving victory in the 2021 SARC – BARINet Aerospace Competition by CISB and SAAB, as well as the 2021 Petrobras’ Innovation Challenge within the Open Flying Robot Trial League at RoboCup. Kenny’s research is centered around visual-inertial odometry, 3D reconstruction, and autonomous UAV navigation.


Edson Hernandes Francelino

Obtained a bachelor’s degree in electrical engineering from Central Paulista University – UNICEP. Has a master’s degree in electrical engineering from the Federal University of São Carlos – UFSCar, specializing in Digital Signal Processing, focusing on determining absolute and articulatory angles in lower limb exoskeletons. Currently a Ph.D. student in electrical engineering at the University of São Paulo – USP, specializing in Dynamic Systems, extending the scope of the master’s research to develop solutions for monitoring and rehabilitating daily activities for post-stroke patients. Collaborates with the UFSCar Physiotherapy Department, focusing on identifying and quantifying daily activities in post-stroke patients to enhance motor rehabilitation. Has 22 years of professional experience in maintaining electronic audio and video equipment, as well as repairing switch-mode power supplies and computers.


Jacó Dias Domingues

I am pursuing a Ph.D. in Electrical Engineering at the University of São Paulo (USP – EESC), with my research focused on Computer Vision, Deep Learning, and Robotics. I obtained my undergraduate degree in Automation and Control Engineering from the Federal University of Ouro Preto (UFOP) in 2020 and completed my master’s in Instrumentation, Control, and Automation of Mining Processes at UFOP/ITV in 2022. Since 2018, I have been working at the Vale Institute of Technology (ITV-MI), where I am dedicated to researching, developing, and testing state-of-the-art technologies for industrial environments.


Raphael Montanari 

Researcher at USP Center for Robotics (CROB/USP). He has experience in Computer Science, focusing on Artificial Intelligence, acting on the following subjects: robotics, artificial intelligence, simulation and artificial neural networks. He currently works as a laboratory specialist at the São Carlos Robotics Center. For the XPRIZE Rainforest competition, he is interested on the development of the mobile robots and robots communication.

Paulo Galvão

Paulo Galvao is a Ph.D. student in Electrical Engineering at the University of São Paulo. Paulo received a master’s degree in Electrical Engineering from the University of São Paulo (USP), São Carlos, Brazil in 2021 and a bachelor’s degree in Mechatronics Engineering at Tiradentes University Center, Maceió, Brazil, 2018. He is currently developing research in the Laboratory of Intelligent Systems focused on applying perception algorithms and control systems to improve the performance of autonomous aerial and ground vehicles operating in hostile environments. He worked in the FlyingU2 control team, where he developed innovative solutions presented in three different competitions, winning first place in the 1st SARC-BARINet Aerospace Collaborative UAVs Competition and the Petrobras Innovation Challenge. He is currently Part of the Brazilian team in the Xprize Rainforest competition, aiming to promote innovative technologies for the rapid, accurate, and low-cost characterization of biodiversity in rainforests. His research interests include Control Systems, Unmanned Aerial Vehicles, Robotics Perception, Artificial Intelligence, and Robot Motion Planning.

Roberto S. Inoue

Roberto S. Inoue 

Roberto S. Inoue is an Associate Professor at the Federal University of São Carlos in the Computer Science Department. Advisor in the Graduate Program in Computer Science (PPGCC-UFSCar) and the Graduate Program in Electrical Engineering (PPGEE-UFSCar). His research interests include Engineering field, focusing mainly on the following topics: robust filtering, Kalman filter, GPS-aided inertial navigation system, position, attitude and orientation reference system, inertial measurement unit, robotics, unmanned aerial vehicles, wheeled mobile robots, robust control, adaptive control, fuzzy systems, and neural networks. Inoue is the coordinator of the Robótica e Sistema group at UFSCar and of the Laboratory of Autonomous Robots and Intelligent Systems (LARIS).
Robson Rogério Dutra Pereira

Robson Rogério Dutra Pereira 

Robson Rogério Dutra Pereira is a Ph.D. candidate in Computer Science at the Federal University of São Carlos (UFSCar). Robson received a Master of Science’s Degree in Mechanical Engineering at the Engineering School of São Carlos – University of São Paulo (EESC-USP, 2009), and Bachelor’s Degree in Electrical Engineering at the Federal University of Mato Grosso (UFMT, 2005). Since 2015, he is a professor in the Bachelor’s Degree in Control and Automation Engineering, at the Department of Electrical Engineering and Automation (DEEA), at the Federal Institute of Mato Grosso (IFMT) Cuiabá campus, Robson taught the following courses: Performance Evaluation of Systems (60 hours), Discrete Control Systems (90 hours), Industrial Instrumentation (90 hours), and Continuous Control Systems (90 hours). I also served as the coordinator of this program from May 2017 to March 2019. Currently, I am pursuing a Ph.D. Degree at the UFSCar in Computer Science, focusing on topics related to Digital Image Processing, Geoprocessing, Remote Sensing, UAVs (Unmanned Aerial Vehicles), Machine Learning, Deep Learning, Mobile Robots, Robotics, and UAVs Motion Planning. He collaborated with the FlyingU2 control team, where he with the IFMT workgroup GEOTEC provided an aerial image dataset of Pantanal Mato-Grossense, winning first place in the 1st SARC-BARINet Aerospace Collaborative UAVs Competition (2021). He also worked in the UFSCar-LARIS team, where he contributed to the development of a mobile differential robot with 2D SLAM mapping, Deep Learning object localization and autonomous navigation, at the ROBOVISOR Tech Challenge AGV 1.0 (2022).

Fernanda Martins Luna

Fernanda Martins Luna 

Fernanda Martins Luna is a Master of Science’s candidate in Computer Science at the Federal University of São Carlos (UFSCar). Fernanda received a Bachelor’s Degree in Information Systems at the Federal University of Mato Grosso (UFMT, 2023), where she obtained a certification of outstanding student, issued by the Brazilian Computing Society. During her undergraduate studies, she participated as a full stack software developer at the junior company Infocorp, located at the Computing Institute of UFMT, participating in the development of a website for the experimental production company for the UFMT’s undergraduate program of Cinema and Audiovisual. Additionally, she worked as an intern at the UFMT Information Technology Center, developing a web system for the Official Expertise and Technical Identification (POLITEC-MT). She also participated as a web development intern at Invillia, working as part of a team that works on the Pagseguro payment system. Furthermore, she worked as a volunteer in Scientific Initiation at the Laboratory of Interactive Virtual Environments (LAVI), at the UFMT’s Computing Institute, with its main concentration in Data Security and Penetration Testing in web systems. Finally, she participated in Scientific Initiation at the Computational Bioacoustics Research Unit (CO.BRA), also located at the UFMT’s Computing Institute, where the main area of concentration consisted of Audio Processing, Convolutional Neural Networks, where the main goal was on performing an acoustic monitoring of bird sounds in brazilian swamps. Currently, she aims to obtain a Master of Science Degree in Computer Science, with main concentration in topics related to Signal Processing, Sensor Fusion, Multi-Sensor Systems, Unmanned Aerial Vehicles, Machine Learning, Mobile Robots and Robotics.

Igor Araujo Dias

Igor Araujo Dias

Igor holds a bachelor’s degree in Computer Engineering from the Faculdade Independente do Nordeste (2015) and a master’s degree in Computer Science from the Federal University of São Carlos (2019). He has experience in Robotics, Mechatronics, and Automation, with emphasis on Computer Engineering.
Roseli Aparecida Francelin Romero

Roseli Aparecida Francelin Romero 

Currently, she is a Full Professor at the Department of Computer Science, ICMC, University of São Paulo, working in both undergraduate and graduate programs. She is a member of the Bioinspired Computing group at ICMC-USP and coordinates the LAR – Robotics Learning Laboratory at ICMC-USP. From 2016 to 2018, she served as Head of the SCC Department/ICMC-USP and coordinator of the Robotics Center of USP in São Carlos-SP (CRob-SC/USP). She also served as vice-coordinator of the Robotics Center of USP in São Carlos-SP (CRob-SC/USP) from 2011 to 2015 and vice-head of the SCC Department/ICMC/USP from 2014 to 2016. She is a Senior Member of the INNS – International Neural Networks Society and a member of the SBC – Brazilian Computing Society and the SBA – Brazilian Society of Automation. She has served as a reviewer for various journals including IEEE Trans. on Neural Networks and Learning Systems and Neurocomputing. She is the mentor of the Warthog Robotics group, two-time champion of the Brazilian Robotics Competition (CBR), and also the local coordinator of the Brazilian Robotics Olympiad Regional in São Carlos-SP. She received the Jabuti Award 2015 for second place in the category: Engineering, Technologies, and Informatics. She is currently the Vice-Chair of the IEEE South RAS Chapter. Her areas of interest include artificial neural networks, fuzzy systems, computer vision, machine learning, and robotics.
Guilherme Nardari

Guilherme Nardari 

Guilherme holds a Bachelor’s degree in Information Systems from the Institute of Mathematical and Computer Sciences (ICMC-USP) with a focus on intelligent systems. He has worked on the development of natural language processing and image processing systems. He holds a Ph.D. from the Graduate Program in Computer Science and Computational Mathematics at ICMC-USP. Among his research interests are topics related to machine learning, computer vision, and robotics.




Simone Dena

Coordinator of the Bioacoustics group of the Brazilian Team. I’m a biologist and audiovisual collections manager at the Museu de Diversidade Biológica (Museum of Biological Diversity) of Unicamp (University of Campinas). I have experience in the areas of audiovisual collections, bioacoustics, biodiversity acoustic monitoring, animal communication, taxonomy, population, and community ecology. I also work on the development and implementation of educational and university outreach actions.


Luís Felipe Toledo

Assistant coordinator of the Bioacoustics group of the Brazilian Team. I’m a zoologist with a focus on Herpetology, working in natural history, taxonomy, ecology, communication, behavior, and conservation of amphibians. Currently, I’m a Full Professor of Vertebrates at Universidade Estadual de Campinas (Unicamp), curator of vertebrates at the Museu de Diversidade Biológica (MDBio), coordinator and curator of the Fonoteca Neotropical Jacques Vielliard, and a professor in the Graduate Programs in Ecology and Animal Biology at Unicamp.
Diego Llusia

Diego Llusia

Researcher at Universidad Autónoma de Madrid. I was awarded the world-renowned Marie Curie Post-doctoral Fellowship (MCSA, H2020), and my research is focused on the role of environmental factors in the evolution of animal acoustic communication and the impacts of global change on species’ communicative strategies. I hold a PhD in Ecology from the Universidad Autónoma de Madrid (UAM), and I was granted the Extraordinary Doctoral Prize 2013-2014. Additionally, I am a collaborating professor at the Federal University of Goiás (UFG, Brazil), where I supervise and lecture students and coordinate research projects.


Juan Sebastián Ulloa Chacón

Researcher at Instituto de Investigación de Recursos Biológicos Alexander von Humboldt. As a scientist and engineer, I am driven by the pursuit of creating smart tools to preserve biodiversity. My research focuses on combining acoustic monitoring and artificial intelligence to assess and predict the impact of global change on tropical ecosystems. With a PhD in Ecology from the University Paris-Saclay, France, my strong background in signal processing and pattern recognition has equipped me with the skills to adapt these technologies for biodiversity monitoring.

Sylvain Haupert

Sylvain Haupert

Research Engineer in Ecoacoustics at CNRS (Centre National de la Recherche Scientifique). I’m a data scientist in ecoacoustics, specially developing frameworks in R and Python for analyzing large audio dataset recorded in terrestrial environment. I have a PhD in Acoustics and Biomedical Engineer (M.S). Engineer at Muséum National d’Histoire Naturelle. Member of the Ecoacoustics Research project (ear.cnrs.fr) dedicated to biodiversity monitoring by acoustics.


Thiago Gouvea

Researcher and professor at the German Research Center for Artificial Intelligence (DFKI). I work on the development of interactive machine learning solutions for acoustic monitoring of wild animals and the creation of a software tool that can be used for annotating acoustic data.


Bengt Lüers

I am a researcher at the German Research Center for Artificial Intelligence (DFKI), focusing on machine learning for classification and representation learning of audio data. For the XPRIZE Rainforest competition, I am developing an interactive tool for passive acoustic monitoring (PAM) of wild animals. My tool is designed to leverage automatically generated labels by large pre-trained artificial neural networks to streamline the manual annotation process of bioacoustic data.


Hannes Berthold Kath

Researcher at German Research Center for Artificial Intelligence (DFKI). I work on the development of interactive machine learning solutions for acoustic monitoring of wild animals and the creation of a software tool that can be used for annotating acoustic data.

Maria João Ramos Pereira

Maria João Ramos Pereira

Assistant Professor at the Zoology Department, UFRGS. In my research I integrate studies in population and community ecology of mammals and birds, to understand ecological and evolutionary patterns of vertebrate diversity. I am also interested in methodological aspects of non-invasive monitoring methods, particularly acoustic monitoring, and camera-traps. My studies are applied in conservation and management of populations and ecosystems, and human dimensions of wildlife, under a logic of sustainability. https://www.ufrgs.br/bimalab

Moise Leance Sagbohan

Moise Leance Sagbohan

Research collaborator at the Mathematical-Statistical Modeling Laboratory of UFPA (Federal University of Para). In my research, I use machine learning techniques to predict habitat changes based on acoustic indices and develop automated algorithms to detect bird-specific signals to investigate anthropogenic impacts on their vocal communication. Apart from bioacoustics and ecoacoustics, I am also interested in applied statistics, data science, climate change and its ecological consequences.

Remote Sensing

Remote Sensing

Paulo Guilherme Molin

Paulo Guilherme Molin

Molin is coordinator of the Remote Sensing subgroup within the Brazilian Team. He holds a faculty position at UFSCar-CCN and is a researcher in the field of environmental management, specializing in forest restoration planning and monitoring. He earned his doctoral degree in Forest Resources from ESALQ-USP, a master’s degree in Geospatial Technologies from the Erasmus Mundus program, jointly offered by the University of Muenster (Germany), Universidade Nova de Lisboa (Portugal), and Universidade Jaume I (Spain). He also holds a bachelor’s degree in Environmental Management from ESALQ-USP. He has completed two postdoctoral fellowships at USP. His research primarily centers around the application of geotechnologies (remote sensing, modeling, GIS, drones, and GNSS) as tools for territorial and natural resource management.
Danilo Almeida

Danilo R. A. de Almeida

Danilo coordinates the Remote Sensing subgroup within the Brazilian Team. He is a specialized researcher in ecology, forest management, and restoration. His academic background comprises a doctoral degree in Forest Resources from ESALQ-USP in collaboration with Michigan State University, a master’s degree in Tropical Forest Sciences from INPA, and a bachelor’s degree in Forest Engineering from UFV. He has completed postdoctoral research at the University of São Paulo, University of Florida, and Bangor University. Having authored over 60 scientific articles, his primary research focuses on forest monitoring through remote sensing. In addition to his academic engagement, Danilo holds the position of Director of REDD+ Carbon Projects at BrCarbon and is also a managing partner at Bioflore, a company specializing in innovative forest monitoring technologies.
01-Herbert Lincon Rodrigues Alves dos Santos

Herbert Lincon Rodrigues Alves dos Santos

Herbert Lincon is an environmental technologist, specialist in geoprocessing and postgraduating in project management. With operations in the second and third sectors of the economy, with geoprocessing and data analysis activities, he joins the team as co-coordinator to unify the efforts of all team members.

02-Carlos Alberto Silva

Carlos Alberto Silva

Carlos Alberto Silva is an Assistant Professor of Quantitative Forest Science in the School of Forest, Fisheries, and Geomatics Sciences (SFFGS) at the University of Florida (UF) where he directs the Forest Biometrics and Remote Sensing Lab (Silva Lab). He is interested in understanding how forest ecosystems changes over time due to natural and anthropogenic disturbances and their impact on the carbon cycle. Previously, he has worked as a research scientist at the USDA Forest Service, University of Maryland, NASA Jet Propulsion Laboratory and NASA Goddard Space Flight Center. His core research consists of developing statistical frameworks and open-source tools, such as rGEDI, TreeTop, rLiDAR, ForestGapR, and leafR for remote sensing data processing and forest resources monitoring. He is particularly interested in using lidar (light detection and ranging) data, from airborne (ALS), terrestrial (TLS), and satellite platforms (e.g. GEDI, ICESat-2), combined with multi- and hyperspectral satellite data and advanced statistical methods to address ecological questions related to forest ecosystem structure, function, and composition dynamics at a variety of spatial scales. Dr. Silva is member of both NASA’s Carbon Monitoring System (CMS) and Ice, Cloud and land Elevation Satellite (ICESat-2) Science Teams.


Eben North Broadbent

Eben N. Broadbent is an assistant professor of forest ecology and geomatics in the School of Forest, Fisheries, and Geomatics Sciences at the University of Florida where he co-directs the Spatial Ecology and Conservation Lab and the GatorEye Unmanned Flying Laboratory Project with Dr. Almeyda Zambrano (Prof. of tropical conservation and development, TRSM, UFL) and is an affiliated researcher with the Woods Institute for the Environment at Stanford University. Over the last decades he has conducted research focusing on the tropics, including in the Brazilian, Bolivian, and Peruvian Amazon, Papua Indonesia, Hawaii, Costa Rica, and Mexico, and also including work in California and in his childhood forests of New England. He has worked as a research ecologist in the Department of Global Ecology of the Carnegie Institution for Science at Stanford University, at the Instituto Boliviano de Investigación Forestal in Santa Cruz, Bolivia, and at Hudsonia Ltd. at Bard College. He is involved in projects linking social sciences with forest ecology, conservation biology and remote sensing, including current projects investigating feedbacks between soil fertility and land use decision making in the context of rapid infrastructure development in the Amazon and linking land use change with water quality and biodiversity in Costa Rica.

04-Gabriel Gualda

Gabriel Gualda

Environmental manager at ESALQ/USP. Has worked in the following areas: Geoprocessing applied to basin analysis watersheds and Forest Restoration; Water quality; stream ecology


05-Giulio Brossi Santoro

Giulio Brossi Santoro

Giulio is an environmental engineer graduated from UFSCar and a specialist in forest restoration from the same institution. He completed his master’s degree in environmental sciences at ESALQ/USP and is currently working with geotechnologies applied to natural ecosystems as a phD student in the forest resources program at the same institution. He has extensive experience working with environmental modeling, remote sensing, GIS, GNSS and drones.


06-José Matheus Segre Moneva Viveiros_

José Matheus Segre Moneva Viveiros

José Matheus is a member of the Remote Sensing subgroup of the Brazilian team. He holds a Bachelor’s degree in Environmental Engineering from UFSCar-CCN and is currently a Master’s student in Forest Resources at ESALQ-USP. During his career, he has been actively involved in research, development and innovation projects that utilize Remotely Piloted Aircraft for Sustainable Management and Monitoring of Forest Restoration. At the moment, José holds the position of Jr. Research and Development Analyst at Bioflore, a company specialized in creating innovative technologies for forest monitoring. At Bioflore, he research focus on biodiversity, employing Remote Sensing techniques to monitor and detect tree species.


07-Laura Barbosa Vedovato

Laura Barbosa Vedovato 

Laura is an ecologist with a master´s degree in Remote Sensing from INPE and a PhD in Geography from the University of Exeter. Currently is a PosDoc Researcher working in carbon modelling. She has expertise in tropical forest dynamics, forest fragmentation, fires and forest restoration.


Leo Eiti Haneda

Leo Eiti Haneda 

Leo is a Forest Engineer with a Master’s degree in Forest Resources at the University of São Paulo. Currently, he is a PhD candidate at the Forest Resources and Conservation Program at University of Florida. His work is focused on the use of remote sensing and GIS technologies applied on forest ecology and management. At the Brazilian Team, he supports the remote sensing team with LiDAR data processing, analyses and final products.


09-Leonardo Gonçalves Belli

Leonardo Gonçalves Belli

Studying forestry engineer in ESALQ/USP. He carried out activities in the field of forest restoration, leading and applying projects carried out within the environmental adaptation group. Currently, his focus is on specializing in monitoring forest diversity using remote sensing technologies.


10-Matheus Pinheiro Ferreira

Matheus Pinheiro Ferreira

Matheus has over ten years of experience using remote sensing data to monitor tropical ecosystems, especially forests. He has led forest monitoring projects in both the public and private sectors, focusing on biodiversity and carbon storage assessments. His current research focuses on using remote sensing and artificial intelligence methods to map essential characteristics of tropical forests, such as tree species diversity and biomass. He has experience in imaging spectroscopy and LiDAR. Matheus works as a Professor of Forest Inventory and Data Science in the Department of Forest Science at the Luiz de Queiroz College of Agriculture (ESALQ) from the University of São Paulo (USP)
11-Matheus Santos Fuza

Matheus Santos Fuza

Forestry Engineer and Master’s student in the Graduate Program in Forest Resources at ESALQ/USP. Has worked in the following areas: Forest Restoration; Forest Monitoring; Geoprocessing Analyst and BigData of the thematic project NewFor – Lastrop; Developer of Deep Learning architectures applied to forest ecosystems.
12-Silvio Henrique Menezes Gomes

Silvio Henrique Menezes Gomes

Silvio is a forest engineer with a doctoral degree in fores resources and applied modeling from the University of São Paulo. He has experience in forest biometrics, and advanced modeling applied to develop analytic methodologies for carbon stock quality protocols in tropical forests, ground-based forest inventory data, remote sensing, and drone-LiDAR systems.


13-Vinicius Moura Costa_

Vinicius Moura Costa 

Vinicius is an environmental engineer and is currently working with environmental modelling and landscape dinamics as a master’s student at ESALQ/USP Forest Resources program. He has extensive experience working with modeling, remote sensing, GIS, GNSS and drones.


Gabriel Prata

Gabriel Prata, PhD, is a post-doctoral associate and Research Scientist in the SPEC Lab at the University of Florida (UF). He is a forest engineer who earned his bachelor’s, master’s, and PhD degrees, all specializing in Forestry, from the University of Sao Paulo, ESALQ in Brazil. His focus lies in remote sensing and its application in forest ecology, specifically with various sources of LiDAR data and its integration with other sensors such as radar, hyperspectral, multispectral, and visual data. Currently at UF, his primary project centers on assessing forest damages and recovery after Hurricane Michael in the northern region of Florida State in 2018, in collaboration with the US Forest Service and Florida Agricultural and Mechanical University (FAMU). Additionally, Gabriel is the director/founder of Prata Florestal, a forestry consultancy company in Brazil, specialized in silviculture and forest insurance.

Vlamir José Rocha

Vlamir José Rocha

I am a zoologist specializing in Mastozoology. My interests include studying the natural history, ecology, behavior, conservation, and management of neotropical mammals using various direct and indirect techniques. I currently hold the position of Associate Professor of Zoology at the Federal University of São Carlos, Araras campus (UFSCar), and I am a professor in the Postgraduate Program in Fauna Conservation. Additionally, I serve as the coordinator of the Fauna Laboratory. I am enthusiastic about applying new technologies to biodiversity studies.