A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
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Updated
May 16, 2024 - Python
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
An R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.
An "R" package for automatic download and preprocessing of MODIS Land Products Time Series
Earth Observation Data Access Gateway
Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).
cuSTARFM is a GPU-enabled Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)
cuESTARFM is a GPU-enabled enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM)
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python
Access data from the MODIS web service and perform quality filtering in Python
Sentinel 2 and Landsat 8 Atmospheric correction
FIRECAM: Fire Inventories - Regional Evaluation, Comparison, and Metrics
All the code in this branch will be python based, upon jupyter notebook. You will be able to find all codes for Google Earth Engine(GEE) on this repository. You will be able to link code with each post blog on readme file for each folders. Content from the Blog https://kaflekrishna.com.np will be uploaded here. https://google-earth-engine.com/
A ninja python package that unifies the Google Earth Engine ecosystem.
Submit a batch of MODIS Global Subset Tool orders via the MODIS Web Service
On-Demand Earth System Data Cubes (ESDCs) in Python
cuSTNLFFM is a GPU-enabled Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM)
Package designed to detect and quantify water quality and cyanobacterial harmful algal bloom (CHABs) from remotely sensed imagery
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