A gallery of interesting Jupyter Notebooks based on Brazil Data Cube data and technologies
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Updated
Oct 7, 2025 - Jupyter Notebook
A geographic information system (GIS) is a conceptualized framework that provides the ability to capture and
analyze spatial and geographic data. GIS applications (or GIS apps) are computer-based tools that allow the
user to create interactive queries (user-created searches), store and edit spatial and non-spatial data,
analyze spatial information output, and visually share the results of these operations by presenting them as
maps.
A gallery of interesting Jupyter Notebooks based on Brazil Data Cube data and technologies
Jupyterlab extension for EODAG search
Intergrate functions of ArcGIS Desktop and ENVI/IDL via python script packages/APIs. Use Jupyter Notebook for codeblock management.
ODI Starter: Remote Sensing in 3 Days. Zero-install Earth Engine + Colab notebooks to build an NDVI map, cloud-masked NDVI + histogram, and a seasonal NDVI chart. Beginner-friendly, portfolio-ready.
In this series, I have explained everything step by step to teach GIS, Remote Sensing, and Machine Learning in Bangla. The lessons are demonstrated using Python with Jupyter Notebooks, where I have explained the concepts through practical coding examples.
An interactive Jupyter/IPython widget for accessign data from any public ERDDAP server
Jupyter Notebooks documenting the use of 3RWW and related data services
Lexcube: 3D Data Cube Visualization in Jupyter Notebooks
This project demonstrates how to extract geospatial features (e.g., fire hydrants) from OpenStreetMap (OSM) and convert them to ArcGIS-compatible formats (ESRI Shapefiles). It includes an automated Jupyter Notebook workflow for reading OSM data, filtering objects, and exporting to .shp.
Docker image for GDAL and jupyter-notebook
🌏 Master Python Geocoding: From addresses to coordinates! Interactive notebooks covering geocoding essentials, API integration, and real-world applications with Tokyo locations. Perfect for developers and GIS enthusiasts. 📍✨
Notebooks used or made in development of prediksicovidjatim
A collection of Python packages for geospatial analysis with binder-ready notebook examples
Explore a diverse collection of freely available geospatial datasets in this repository. Whether you're working with Shapefiles, GeoJSON, KML, or other formats, these datasets are ready to enrich your geospatial analyses. Dive into Python notebooks from other repositories to see how you can integrate and leverage these datasets seamlessly