30 open-source projects similar to bopen/xarray-sentinel, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Xarray Sentinel alternative.
TorchGeo is a PyTorch library designed for deep learning on geospatial data, providing a framework for building and training neural networks for tasks such as semantic segmentation, object detection, and change detection. It serves as a comprehensive pipeline for remote sensing, featuring specialized dataset loaders and multispectral image preprocessing tools. The library is distinguished by a dedicated remote sensing model zoo and extensive support for transfer learning, allowing users to integrate pre-trained weights optimized for specific satellite sensors. It also includes support for sel
This example demonstrates a few ways to get data into your binder.
🛰️ 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…
A curated list of resources focused on Machine Learning in Geospatial Data Science.
Check our Breizhcrops Tutorial Colab Notebook for quick hands-on examples.
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.
A curated list of awesome tools, tutorials and APIs related to data from the Copernicus Sentinel Satellites.
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.
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.
Code for 3rd place solution in Kaggle Understanding Clouds from Satellite Images Challenge.