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#

modis

Here are 128 public repositories matching this topic...

awesome-spectral-indiceseodag

An R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.

  • UpdatedJul 10, 2023
  • R
cubospectral

An "R" package for automatic download and preprocessing of MODIS Land Products Time Series

  • UpdatedMay 16, 2025
  • R

cuSTARFM is a GPU-enabled Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)

  • UpdatedJun 1, 2021
  • Cuda

cuESTARFM is a GPU-enabled enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM)

  • UpdatedJul 26, 2022
  • Cuda

Download and processing framework for MODIS imagery. The package provides automated access to the global online data archives LP DAAC, LAADS and NSIDC as well as processing capabilities such as file conversion, mosaicking, subsetting and time series.

  • UpdatedJul 15, 2025
  • R

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

  • UpdatedFeb 22, 2021
  • Python
EO-Climate-Hazard-Analysis-App

A Google Earth Engine API (interactive dashboard) for satellite-based global climate hazard analysis (urban heat, landcover changes, etc). Project under World Bank Group. ⬇️ ⬇️

  • UpdatedJul 15, 2023

Package designed to detect and quantify water quality and cyanobacterial harmful algal bloom (CHABs) from remotely sensed imagery

  • UpdatedMar 25, 2024
  • R

ActiveModel + Redis

  • UpdatedSep 9, 2024
  • Ruby

Command-line application for visualizing data from CloudSat and CALIPSO satellites

  • UpdatedMar 26, 2025
  • Python

Sentinel 2 and Landsat 8 Atmospheric correction

  • UpdatedFeb 19, 2024
  • C
modisfast

Fast and efficient access to MODIS, VIIRS and GPM Earth Observation data with R

  • UpdatedJul 17, 2025
  • R

卫星遥感-数据处理、分析与反演-Python实现

  • UpdatedNov 7, 2019
  • Python

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 Bloghttps://kaflekrishna.com.np will be uploaded here.https://google-earth-engine.com/

  • UpdatedAug 7, 2022
  • Jupyter Notebook

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