https://github.com/rifatsdas/satellite_optical_indices
Mostly used optical indices with satellite images for studying earth surface and different features and their changes in spatio-temporal scale.
https://github.com/rifatsdas/satellite_optical_indices
anaconda3 jupyter-notebook landsat-data optical-indices optical-satellite-data python3 rasterio sentinel-1 sentinel-2 sentinel-3 sentinel-data
Last synced: 3 months ago
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Mostly used optical indices with satellite images for studying earth surface and different features and their changes in spatio-temporal scale.
- Host: GitHub
- URL: https://github.com/rifatsdas/satellite_optical_indices
- Owner: rifatSDAS
- License: agpl-3.0
- Created: 2021-04-17T13:13:55.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-02-23T22:28:09.000Z (over 3 years ago)
- Last Synced: 2024-01-27T03:09:09.287Z (over 1 year ago)
- Topics: anaconda3, jupyter-notebook, landsat-data, optical-indices, optical-satellite-data, python3, rasterio, sentinel-1, sentinel-2, sentinel-3, sentinel-data
- Language: Jupyter Notebook
- Homepage:
- Size: 72.3 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# satellite_optical_indices
### Mostly used optical indices using satellite data
This repo contains available optical indices, including vegetation, soil, and water indices. The indices are tested with Sentinel 2 MSI optical satellite data. All data used for testing is publically available under open source license. For more details look here https://scihub.copernicus.eu/
Any of these indices in this repo can be applied with any optical satellite data, from space-borne or air-borne sensors.
To run any of these jupyter file, user needs:
Anacond installed with Python 3.6 or above
Rasterio python package for working with satellite raster data
To install rasterio see here: https://rasterio.readthedocs.io/en/latest/