Geospatial
Forest Conservation and Management 🌳 | Satellite Data Analysis Engineer 🛰️
I have strong expertise in
satellite-based remote sensing applications for forest conservation and management, particularly in tropical forests. Background in environmental
science and forest engineering.
Skills
geospatial data science cloud computing
satellite data scientific computing
geographic information systems
data visualization google earth engine
Programming: Python, R, Javascript
Cloud computing: Google Earth Engine, Colab
Experience
Oct 2025 - now, Tokyo, Japan
- Working as Satellite Data Analysis Engineer (R&D) in varios REDD+ projects
Technologies used: Google Earth Engine, Google Cloud Platform, Google Colab
Research Assistant, The University of Tokyo
2022-2025, Tokyo, Japan
- Combined remote sensing data, such as
climate data, sea surface temperature, salinity, and chlorophyll a data for
application in fisheries predictions
Technologies used: Google Earth Engine, QGIS
PhD.
Candidate, The University of Tokyo
Apr 2022 - Sep 2025, Tokyo, Japan
- Combining Sentinel 2, random forest and object-based image classification for local application of satellite imagery to understand deforestation dynamics in the Amazon
Technologies used: Google Earth Engine, QGIS,ArcGIS Pro
Selected peer-reviewed
publications
Lopes, D.N., Tsuyuki, S.: Deforestation and
Forest Degradation Detection in the Brazilian Amazon: A
Comparative Analysis of Two Areas and Their Conservation Units.
Appl. Sci. 2024, 14, 10504.
Contributions
Authored
Check my github for more info
Education
PhD.,
Environmental Science, The University of Tokyo
Thesis: Towards Localized Solutions for Sustainable Management of Heterogeneous
Amazon Rainforest: Case Studies in Porto Velho and Manaus, Brazil
M.Sc.,
Environmental Science, The University of Tokyo
Thesis: Spatial time-series analysis of the impacts of Urban Expansion on Forest Areas in Manaus city, Brazil
B.Sc.,
Federal University of Amazonas, Brazil
Major: Forest Engineering
Danielle Nogueira Lopes, PhD