A Python package for installing commonly used packages for geospatial analysis and data visualization with only one command.
Geo Assist is a spatial library to manage spatial data in-memory.
Earth Engine and Geemap: Geospatial Data Science with Python
A collection of 300+ examples for using Earth Engine and the geemap Python package
A collection of Jupyter notebooks for GEE Courses
A streamlit app template based on streamlit-option-menu
Interactive web apps created using geemap and streamlit
A Python package for installing optional dependencies for geemap and leafmap.
A streamlit multipage app template for geospatial applications
Python tools for agricultural analysis powered by Google Earth Engine.
A collection of Earth Engine Apps created using geemap and voila
Python scripts for deploying Earth Engine Apps to heroku
Assessed the performance of Random Forest (RF) and Support Vector Machines (SVM) machine learning algorithms for land cover classification in a predominant agricultural landscape using the fusion of time-series Sentinel-1 and Sentinel-2.
Evaluate Wildfire Environmental Impact and Assess Burn Severity Consequences using Cloud Based Geoprocessing via Earth Engine Streamlit App.
This course introduces beginners to Google Earth Engine using Python in Google Colab. Explore remote sensing, process geospatial data, create dynamic visualizations, and understand drought indices. Develop skills for environmental monitoring and decision-making without needing local installations.
Spatial Data Management with Google Earth Engine
A template for building a mkdocs website
An Earth Engine web app developed using Solara and geemap
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