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Multi-Mission Earth Observation Data Processing System
The surge in the number of earth observation satellites being launched worldwide is placing significant pressure on the satellite-direct ground receiving stations that are responsible for systematic data acquisition, processing, archiving, and dissemination of earth observation data. Growth in the n...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766842/ https://www.ncbi.nlm.nih.gov/pubmed/31487970 http://dx.doi.org/10.3390/s19183831 |
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author | Mhangara, Paidamwoyo Mapurisa, Willard |
author_facet | Mhangara, Paidamwoyo Mapurisa, Willard |
author_sort | Mhangara, Paidamwoyo |
collection | PubMed |
description | The surge in the number of earth observation satellites being launched worldwide is placing significant pressure on the satellite-direct ground receiving stations that are responsible for systematic data acquisition, processing, archiving, and dissemination of earth observation data. Growth in the number of satellite sensors has a bearing on the ground segment payload data processing systems due to the complexity, volume, and variety of the data emanating from the different sensors. In this paper, we have aimed to present a generic, multi-mission, modularized payload data processing system that we are implementing to optimize satellite data processing from historical and current sensors, directly received at the South African National Space Agency’s (SANSA) ground receiving station. We have presented the architectural framework for the multi-mission processing system, which is comprised of five processing modules, i.e., the data ingestion module, a radiometric and geometric processing module, atmospheric correction and Analysis Ready Data (ARD) module, Value Added Products (VAPS) module, and lastly, a packaging and delivery module. Our results indicate that the open architecture, multi-mission processing system, when implemented, eliminated the bottlenecks linked with proprietary mono-mission systems. The customizable architecture enabled us to optimize our processing in line with our hardware capacities, and that resulted in significant gains in large-scale image processing efficiencies. The modularized, multi-mission data processing enabled seamless end-to-end image processing, as demonstrated by the capability of the multi-mission system to execute geometric and radiometric corrections to the extent of making it analysis-ready. The processing workflows were highly scalable and enabled us to generate higher-level thematic information products from the ingestion of raw data. |
format | Online Article Text |
id | pubmed-6766842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67668422019-10-02 Multi-Mission Earth Observation Data Processing System Mhangara, Paidamwoyo Mapurisa, Willard Sensors (Basel) Article The surge in the number of earth observation satellites being launched worldwide is placing significant pressure on the satellite-direct ground receiving stations that are responsible for systematic data acquisition, processing, archiving, and dissemination of earth observation data. Growth in the number of satellite sensors has a bearing on the ground segment payload data processing systems due to the complexity, volume, and variety of the data emanating from the different sensors. In this paper, we have aimed to present a generic, multi-mission, modularized payload data processing system that we are implementing to optimize satellite data processing from historical and current sensors, directly received at the South African National Space Agency’s (SANSA) ground receiving station. We have presented the architectural framework for the multi-mission processing system, which is comprised of five processing modules, i.e., the data ingestion module, a radiometric and geometric processing module, atmospheric correction and Analysis Ready Data (ARD) module, Value Added Products (VAPS) module, and lastly, a packaging and delivery module. Our results indicate that the open architecture, multi-mission processing system, when implemented, eliminated the bottlenecks linked with proprietary mono-mission systems. The customizable architecture enabled us to optimize our processing in line with our hardware capacities, and that resulted in significant gains in large-scale image processing efficiencies. The modularized, multi-mission data processing enabled seamless end-to-end image processing, as demonstrated by the capability of the multi-mission system to execute geometric and radiometric corrections to the extent of making it analysis-ready. The processing workflows were highly scalable and enabled us to generate higher-level thematic information products from the ingestion of raw data. MDPI 2019-09-04 /pmc/articles/PMC6766842/ /pubmed/31487970 http://dx.doi.org/10.3390/s19183831 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mhangara, Paidamwoyo Mapurisa, Willard Multi-Mission Earth Observation Data Processing System |
title | Multi-Mission Earth Observation Data Processing System |
title_full | Multi-Mission Earth Observation Data Processing System |
title_fullStr | Multi-Mission Earth Observation Data Processing System |
title_full_unstemmed | Multi-Mission Earth Observation Data Processing System |
title_short | Multi-Mission Earth Observation Data Processing System |
title_sort | multi-mission earth observation data processing system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766842/ https://www.ncbi.nlm.nih.gov/pubmed/31487970 http://dx.doi.org/10.3390/s19183831 |
work_keys_str_mv | AT mhangarapaidamwoyo multimissionearthobservationdataprocessingsystem AT mapurisawillard multimissionearthobservationdataprocessingsystem |