sentinel-2-data

Classical and quantum machine-learning framework for detecting and mapping natural hydrogen prospectivity in Kazakhstan using Sentinel-2 satellite imagery.

Multimodal Accessibility and Place Profiling Engine for arbitrary Regions

We are using Sentinel-2 satellite imagery and a specialized U-Net deep learning model to detect changes in landscapes before and after flood events. Using the OMBRIA dataset, the model reliably identifies flooded areas to support disaster management and response efforts.

Hybrid ML + GIS pipeline for wildfire vegetation risk: U-Net segmentation on Sentinel-2 with Dynamic World labels, fused with line-distance and slope to produce a tunable risk raster. Validated across three external California AOIs.

Data analysis and object detection to assess Hurricane Maria's impact using NDVI analysis and YOLO modeling for disaster relief planning.

GRASS addon to download Sentinel-2 scenes by S2 scene ID using EODAG.

Given a desired extent, resolution, and desired analyses, downloads Sentinel 2 imagery from planetary-computer, downloads DEM tiles from Copernicus, and then analyzes them through NDVI, NDWI, MNDVI, MNDWI, and SAVI.

Piattaforma self-hosted per l'analisi comparativa di immagini satellitari. Confronta riprese nel tempo (Sentinel-2, Esri World Imagery o caricamento manuale), rileva automaticamente i cambiamenti con filtri anti-rumore, enhancement e soglie regolabili, e offre zoom, annotazioni, libreria ed export completo di report.

An end-to-end GeoAI platform for agricultural monitoring using satellite foundation model embeddings, AlphaEarth, Galileo representations, NDVI-based vegetation analysis, and machine learning based crop classification.

Extension to read from Earth Observation data archives

An analysis of seasonal NDVI changes using the imagery from Sentinel-2 mission. Includes plots and stats for insights into vegetation health.