Project to investigate and develop spatial data-driven Geo-AI models (Convolutional Neural Network) to identify urban greenspace from Satellite images by integrating multiple data sources (e.g. vector data of urban parks)

Script per l'analisi di foto aeree e immagini satellitari per l'automazione della fotointerpretazione; algoritmi classici e basati su machine learning.

Tool package to download GOES (Geostationary Operational Environmental Satellite) 2nd generation (GOES-8 to GOES-15) data from NOAA's NCEI archive, 4th Generation (GOES-16 to GOES-18) data from NOAA's archive on AWS, and Gridded Satellite B1 (GridSat-B1) Climate Data Record, Version 2, from NOAA's AWS and NCEI archives using Python.

The Analytic Stream Formater is listening agricultural field related (new satellite image, new analytic generated) events coming from <geosys/> platform triggering analytic fetching, formatting and publication to an Azure Blob storage.

Earth Observation Project

Plot delineation using Unet, Mask-RCCN, and Smoothly Blending Patches Algorithm

Jupyter notebook walk-through of doing satellite imagery analysis.

Geo-spatial utilities for Remote Sensing and GIS application

A list of all the scale and offset parameters for each raster dataset in Google Earth Engine.

Train AI models on satellite image dataset to classify different types of land.

The official code repository for paper "Rethinking the Encoding of Satellite Image Time Series".

Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm

Retrieves 3D cloud properties from multi-angle images of reflected solar radiation

Satellite Image Analytics and Earth Data Science Experiments in Python

An introduction to script-based satellite image processing using Python

Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.

Implementation of Machine Learning and Deep Learning techniques to find insights from the satellite data.