I am passionate about studying forests through the lenses of remote sensing (RS) and uncovering what we can see from above the forest canopy. Amongst the RS data available, I find high-resolution airborne lidar data simply awesome! I am also fascinated by powerful artificial intelligence methods such as deep learning that can help us extract novel and unique information with very high precision!
I am a remote sensing scientist with interdisciplinary background in environmental sciences, tropical ecology and forest systems. I have strong analytical and programming skills, and focus on quantitative empirical research. My main interests and experience are in Earth Observation and Biogeosciences, but more specifically in investigating forest dynamics with remote sensing and ground data to solve questions related with the carbon cycle; understanding how environmental and climate changes can affect these ecosystems; and developing methods to extract novel and exciting geo-information from vegetation.
I am currently working as a Post-doctoral Researcher at University of California Los Angeles (UCLA) in the Institute of the Environment and Sustainability and NASA-JPL, where I am developing machine learning methods to map Tropical Forest Degradation using remote sensing. Check out my Publications to get to know what I have done so far. I also help my colleagues and collaborate in other interesting research using remote sensing. If you have ideas for collaboration, you can find my email in the Contact. 🙂
Employment/Education
2022-
Post-doctoral Researcher
Institute of the Environment and Sustainability
University of California Los Angeles (UCLA)
Los Angeles, USA
2022-
Research Afilliate
NASA-Jet Propulsion Laboratory, California Institute of Technology
Pasadena, USA
2021-
Honorary Research Fellow
University of Manchester, Manchester, UK
2020-2022
Post-doctoral Researcher
Earth Observation and Geoinformatics Division (DIOTG) of National Institute for Space Research (INPE), São José dos Campos, Sao Paulo, Brazil
2016-2020
Postgraduate Researcher (PhD Remote Sensing)
DIOTG / INPE, São José dos Campos, Sao Paulo, Brazil
2018-2019
Visiting Researcher (PhD Remote Sensing)
School of Geography of University of Leeds, Leeds, UK
2014-2016
Research Assistant
Division of Impacts, Adaptation and Vulnerabilities (DIAV) / INPE, São José dos Campos, Sao Paulo, Brazil
2012-2014
Postgraduate Researcher (MSc Remote Sensing)
DIOTG / INPE, São José dos Campos, Sao Paulo, Brazil
2007-2011
BSc. in Environmental Engineering
UNISEP, Dois Vizinhos, Parana, Brazil
2008-2011 (Interrupted)
BSc. in Forest Engineering
Federal University of Technology – Parana (UTFPR), Dois Vizinhos, Parana, Brazil
Research field
- Remote sensing
- Tropical ecology
- Forest dynamics
- Amazonia
- Biomass
- Plant species distribution
- Deep learning
This figure shows palm trees segmented over a LiDAR canopy height model using a Deep Learning model (Convolutional Neural network)
Links
CV – Brazilian Curriculum Lattes (pt-br): http://lattes.cnpq.br/6150479997891841
Google Scholar Publications: https://scholar.google.com.br/citations?hl=pt-BR&user=4ecvtoEAAAAJ
Reviewer profile: https://publons.com/researcher/2459210/ricardo-dalagnol/peer-review/
Ricardo Dalagnol, PhD 