Stars
OpenLayers-based web application to track and visualize live flight data
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days, follow your own pace. These videos m…
User-friendly, commercial-grade software for processing aerial imagery.
Example data for OpenDroneMap: https://OpenDroneMap.org sourced from a variety of sources
A small collection of scripts on how to perform OBIA with open source software
Jupyter Notebooks with the very basics of scraping with BeautifulSoup library
The GeoDataViz Toolkit is a set of resources that will help you communicate your data effectively through the design of compelling visuals. In this repository we are sharing resources, assets and o…
Collection of resources to take your QGIS cartography to the next level
Ctrl+F (Fire) 🌍🔥🌧️🌡️ Explore and visualize climate data to monitor wildfire risks with ease! Ctrl+F (Fire) is your go-to tool for tracking atmospheric variables such as temperature and precipitatio…
Interactive visualization dashboard in Python with Panel
Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.
Segment Anything Model applied to satellite imagery, selected in a dynamic way from an interactive map
Sample Jupyter notebooks for EOdal
Repository containing presentations made during the Copernicus Earth Observation Data Visualisation workshop series (16 May to 20 June 2023), including links to the resulting best practice guide.
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
Solving the Traveling Salesman Problem using Self-Organizing Maps
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
🛰️ List of earth observation companies and job sites
🌐 List & Map of 700+ companies for geospatial jobs (GIS, Earth Observation, UAV, Satellite, Digital Farming, ..)