Estimating NDVI from SAR Images Using Conditional Generative Adversarial Networks

@Article {
author = {Saglia, Pietro},
title = {Estimating NDVI from SAR Images Using Conditional Generative Adversarial Networks},
pages = {4},
keywds = {
Abstract The Normalized Difference Vegetation Index (NDVI), an indicator of vegetation health, is derived from the visible and near-infrared light reflected by vegetation, which can be measured with multi-spectral sensors. However, clouds can often obstr
}
abstract = {

The Normalized Difference Vegetation Index (NDVI), an indicator of vegetation health, is derived from the visible and near-infrared light reflected by vegetation, which can be measured with multi-spectral sensors. However, clouds can often obstruct land areas, making it challenging to obtain NDVI maps of the surface. This study explores the possibility of estimating NDVI from synthetic aperture radar (SAR) images using a Conditional Generative Adversarial Network (cGAN). Results encourage using a cGAN to address the task and provide valuable insights for future improvements

}
isbn = {979-835032010-7},
date = {2023-07-01},
}