Awesome-GEE
awesome-spectral-indices
| Awesome-GEE | awesome-spectral-indices | |
|---|---|---|
| 1 | 4 | |
| 843 | 763 | |
| 0.0% | 2.5% | |
| 0.0 | 5.9 | |
| over 1 year ago | 13 days ago | |
| Python | ||
| Creative Commons Zero v1.0 Universal | MIT License |
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Awesome-GEE
awesome-spectral-indices
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Any tips or resources for vegetation analysis using 8 band imagery compared to 4 band?
You might find this github repo useful: https://github.com/awesome-spectral-indices/awesome-spectral-indices
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Best indices to use for detecting shallow water
Have you tried the augmented NDWI? That link has a ton of other indices too (scroll down for water).
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Vegetation Indices to determine the change in vegetation area using aerial images
How do you define vegetation cover to begin with? You'll need some kind of definition that uses RGB only, if you want to use these images. Have a look at this listto see if there's a vegetation index that uses RGB only.
- Spectral Indices for Remote Sensing Applications
What are some alternatives?
geemap - A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
biodivMapR - biodivMapR: an R package for α- and β-diversity mapping using remotely-sensed images
python-geospatial - A collection of Python packages for geospatial analysis with binder-ready notebook examples
whitebox - WhiteboxTools Python Frontend [Moved to: https://github.com/giswqs/whitebox-python]
wxee - A Python interface between Earth Engine and xarray for processing time series data
whitebox-python - WhiteboxTools Python Frontend
detectree - Tree detection from aerial imagery in Python
ME-GIS - GIS files created by the ME-DEM team.
linqit - Extend python lists operations using .NET's LINQ syntax for clean and fast coding.
manjaro-linux - Shell scripts for setting up Manjaro Linux for Python programming and deep learning
TouchTerrain_for_CAGEO - Touch Terrain: A python app to create 3D printable terrain models (STL/OBJ) from only elevation data (via Google Earth Engine) or from a local geotiff. Has been used for CNC terrain models. Runs as a web app (http://touchterrain.org), as .py file (standalone.py) or as jupyter notebook. Docker image: https://github.com/ChHarding/TouchTerrain_jupyter_docker