Remote sensing operations from space using satellite imageries is a huge boon to study different domains like agriculture, climatic changes, aerial mapping, weather prediction, disaster management ...

Abstract: In this paper, we demonstrated how machine learning can be integrated in the oil spill monitoring field for thickness estimation. A support vector regression model was trained on ...

fusion optical and radar images to classify vegetation cover, and calibration of machine learning algorithms, among others, are not available yet. Therefore, scikit-eo is a Python package that ...

In recent years, machine learning and pattern recognition methods have become common in Earth and space sciences. This is especially true for remote sensing applications, which often rely on ...

The main goal of this Research Topic is to cover research regarding the latest methodologies and novels and machine learning in the following remote sensing applications: Important note: All ...

Clouds have for decades been a bugbear for remote sensing of land surface ... that incorporates a novel radar technique, better elevation models and machine learning looks set to be a game-changer.