Integrating Pre-Processing Pipelines in ODC Based Framework

@Article {
title = {Integrating Pre-Processing Pipelines in ODC Based Framework},
pages = {4094-4097},
keywds = {
SNAP, Sentinel, data exploitation, management, optimization, machine learning, data processing
}
abstract = {

Using on-demand processing pipelines to generate virtual geospatial products is beneficial to optimizing resource management and decreasing processing requirements and data storage space. Additionally, pre-processed products improve data quality for data-driven analytical algorithms, such as machine learning or deep learning models. This paper proposes a method to integrate virtual products based on integrating open-source processing pipelines. In order to validate and evaluate the functioning of this approach, we have integrated it into a geo-imagery management framework based on Open Data Cube (ODC). To validate the methodology, we have performed three experiments developing on-demand processing pipelines using multi-sensor remote sensing data, for instance, Sentinel-1 and Sentinel-2. These pipelines are integrated using open-source processing frameworks.

}
isbn = {978-1-6654-2792-0},
date = {2022-09-28},
}