Earth Observation Open Science and Innovation

Abstract

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Deriving Exclusion Maps From C-Band Sar Time-Series: An Additional Information Layer for Sar-Based Flood Extent Mapping

“…The EODC uses the high-performance computing platform provided by the third generation of the Vienna Scientific Cluster (VSC-3), preparing easy access to EO data (Naeimi et al, 2016). In addition, EODC users can process EO data with their own algorithms and extract the results (Mathieu and Aubrecht, 2018). The Sentinel-1 data cube from TU Wien is derived by geocoding the SAR backscatter imagery using the python-based SAR Geophysical Retrieval Toolbox (SGRT) and the Sentinel-1 time-series from this data cube can be analysed directly in our study.…”

Monitoring sustainable development by means of earth observation data and machine learning: a review

“…In the last decade, there have been some major contributions to a wide range of Earth Science applications, from analysing gases, soil, vegetation, climate and, more recently, to ocean [60,61]. Recent advances on Machine Learning (ML) field are creating unprecedent opportunities to evaluate and monitor policy decisions as well as humanitarian initiatives [62,63].…”

On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification

“…At the same time, advances in computational technologies and analysis methodologies have also progressed to accommodate larger and higher-resolution datasets. Image classification techniques are constantly being improved to keep up with the ever expanding stream of Big Data, and as a consequence Artificial Intelligence (AI) techniques are becoming increasingly necessary tools [5], [6].…”