I am Francesco, WUR graduate passionate about geospatial data, satellite imagery and data science. My work focuses on satellite data analysis, computer vision, and deep learning techniques for Earth Observation. Here you will find some projects I have worked on that I can publicly share.
- ML/DL for Earth Observation with Python (PyTorch, PyTorch Lightning, scikit-learn, Jupyter Lab)
- Computer Vision with Python (OpenCV, scikit-image, Pillow)
- Geoscripting with Python and R (NumPy, GeoPandas, rasterio, terra, sf)
- Data analysis and manipulation with Python and R (Numpy, Pandas, statsmodels, scipy, dplyr)
- Google Earth Engine and geemap
- Data visualization with Python and R (matplotlib, seaborn, ggplot)
- GIS desktop applications (ArcGIS, QGIS) and related APIs (ArcPy, PyQGIS)
- Artisanal mining mapping with Deep Learning and high-res satellite imagery - Detecting artisanal mining activities using neural networks and optical-SAR data fusion
- Deep Learning for image classification - University course project involving coding and training a CNN to classify images from the UCM dataset
- GADM data download - R script to quickly download data from GADM, with the desired administration level of the country of interest
- OEMC hackathon: EU Land Cover classification - my submission for this hackathon, I placed 18th.
- Raster inspection with PyQGIS - tool to manually review satellite images and related ground truth masks with QGIS