Projects sharing features with Xarray Sentinel

Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors

Automated DORIS Environment (adore) is a set of bash scripts to ease use of TU-DELFT's DORIS software.

GPU accelerated earth observation data processors

🛰️ List of satellite image training datasets with annotations for computer vision and deep learning

There is a need to design specialized networks that are inherently computationally efficient to enable there use in resource contraint devices such as UAVs. The design space can be explored by focusing on the layer configurations, type and connectivity. An architecture is poropsed that allows…

Building Analysis Ready Data of Sentinel-1 time series

ee-fastapi: Flood Detection System

A curated list of resources focused on Machine Learning in Geospatial Data Science.

Check our Breizhcrops Tutorial Colab Notebook for quick hands-on examples.

Synthetic Aperture Radar (SAR) Image Processing Toolbox for Python

ServiceNow completed its acquisition of Element AI on January 8, 2021. All references to Element AI in the materials that are part of this project should refer to ServiceNow.

General Inversion of Phase Technique (GIPhT)

A curated list of awesome tools, tutorials and APIs related to data from the Copernicus Sentinel Satellites.

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Overview about state-of-the-art land-use classification from satellite data with CNNs based on an open dataset

framework for large-scale SAR satellite data processing

Auto-updating Landsat 8 mosaics from AWS SNS notifications.

Create Cloud Optimized GeoTIFF mosaics from AWS Public datasets.

Using SNAP as InSAR processor for StaMPS

Microsoft Maps is releasing country wide open building footprints datasets in United States. This dataset contains 129,591,852 computer generated building footprints derived using our computer vision algorithms on satellite imagery. This data is freely available for download and use.

PyGMTSAR (Python InSAR): Powerful and Accessible Satellite Interferometry

Code for 3rd place solution in Kaggle Understanding Clouds from Satellite Images Challenge.

A basic Python library to demonstrate reading, writing, display, and simple processing of complex SAR data using the NGA SICD standard.