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It contains Google Earth Engine codes (JavaScript API) to process Sentinel-1 and Landsat 8 images to compute SAR and optical vegetation indices.

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eupassarinho/GoogleEarthEngine-sentinel1-vegetation-indices

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googleearthengine-thesis-codes

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This repository contains only the codes written in JavaScript to process Sentinel-1 and Landsat 8 images, in Google Earth Engine JavaScript API, to generate optical and radar vegetation indices. My dissertation was written in the Department of Agricultural Engineering, at the Universidade Federal de Viçosa, Brazil. From that, two scientific papers were derived, which are:

It is the first paper:

SANTOS-SILVA-AMARAL_2021_DPSVIm

Vegetation cover monitoring in tropical regions using SAR-C dual-polarization index: seasonal and spatial influences. It was published in the International Journal of Remote Sensing, and can be accessed through the DOI: https://doi.org/10.1080/01431161.2021.1959955

It is the second paper:

dosSantos_etal_2022_MachineLearningNDVISentinel-1Landsat8

A Machine Learning approach to reconstruct cloudy affected vegetation indices imagery via data fusion from Sentinel-1 and Landsat 8. It was published in the Computers and Electronics in Agriculture journal and can be accessed through the DOI: https://doi.org/10.1016/j.compag.2022.106753

Follows also a graphical abstract of the second paper:

Graphical_Abstract

If any of the codes published here seems useful for your, please consider citing the corresponding paper!

Erli Pinto dos Santos Agronomy Engineer PhD candidate in Agricultural Engineering Department of Agricultural Engineering Universidade Federal de Viçosa (Viçosa, Minas Gerais, Brazil)

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It contains Google Earth Engine codes (JavaScript API) to process Sentinel-1 and Landsat 8 images to compute SAR and optical vegetation indices.

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