MODIS Assimilation and Processing Engine
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Updated
Sep 4, 2024 - Python
MODIS Assimilation and Processing Engine
An "R" package for automatic download and preprocessing of MODIS Land Products Time Series
Implementation of RUSLE method in GEE
Project on how to predict agricultural drought conditions using Vegetation Health Index in Google Earth Engine
This python module extracts land use land cover (LULC) type using Copernicus or MODIS LULC products.
Temperature map prediction of the Southeastern United States
Deep learning for Synthetic Aperture Radar(SAR) and Radiometry data. An Ensemble Convolutional Neural Network workflow is implemented with data acquisition, processing, labelling, creating model, training model and launching a model
Spatiotemporal investigation between MODIS fire products and National Oil Spill Detection and Response Agency of Nigeria (NOSDRA) by comparing the matching events in time and location.
Download and extract USA County specific data from NASA MODIS Remote Sensing Dataset
generate masks from Landsat and MODIS land product QA band
generate Lansat 8 image and MODIS land product masks in Node.js
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