Earth Observation & Data Analysis

Active imaging systems, particularly Synthetic Aperture Radar (SAR), offer notable advantages such as the ability to operate in diverse weather conditions and provide day and night observations of Earth’s surface. These attributes are especially valuable when monitoring regions consistently obscured… Read More »Super-resolution of Sentinel-1 Imagery Using an Enhanced Attention Network and Real Ground Truth Data

This paper presents a principled approach for detecting shadows in satellite imagery at a large scale. We propose a two-stage process, starting with the generation of a training set based on an airborne LiDAR point cloud and a target satellite… Read More »Automatic shadow detection in high-resolution optical satellite imagery

Spiking Neural Networks (SNN) have received a lot of attention as an energy-efficient alternative to Artificial Neural Networks (ANN). They are particularly useful for machine learning applications in space. Many learning algorithms have been developed to build energy-efficient SNNs and… Read More »Initialization Methods Lower Energy Needs of Spiking Neural Networks for Land Cover Classification

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial… Read More »A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Safe operation of machine learning models requires architectures that explicitly delimit their operational ranges. We evaluate the ability of anomaly detection algorithms to provide indicators correlated with degraded model performance. By placing acceptance thresholds over such indicators, hard boundaries are… Read More »Operational range bounding of spectroscopy models with anomaly detection