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PYTAF: A Python Tool for Spatially Resampling Earth Observation Data
Earth observation data have revolutionized Earth science and significantly enhanced the ability to forecast weather, climate and natural hazards. The storage format of the majority of Earth observation data can be classified into swath, grid or point structures. Earth science studies frequently invo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392697/ https://www.ncbi.nlm.nih.gov/pubmed/36003900 http://dx.doi.org/10.1007/s12145-020-00461-w |
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author | Zhao, Guangyu Yang, Muqun Gao, Yizhao Zhan, Yizhe Lee, H. Joe Di Girolamo, Larry |
author_facet | Zhao, Guangyu Yang, Muqun Gao, Yizhao Zhan, Yizhe Lee, H. Joe Di Girolamo, Larry |
author_sort | Zhao, Guangyu |
collection | PubMed |
description | Earth observation data have revolutionized Earth science and significantly enhanced the ability to forecast weather, climate and natural hazards. The storage format of the majority of Earth observation data can be classified into swath, grid or point structures. Earth science studies frequently involve resampling between swath, grid and point data when combining measurements from multiple instruments, which can provide more insights into geophysical processes than using any single instrument alone. As the amount of Earth observation data increases each day, the demand for a high computational efficient tool to resample and fuse Earth observation data has never been greater. We present a software tool, called pytaf, that resamples Earth observation data stored in swath, grid or point structures using a novel block indexing algorithm. This tool is specially designed to process large scale datasets. The core functions of pytaf were implemented in C with OpenMP to enable parallel computations in a shared memory environment. A user-friendly python interface was also built. The tool has been extensively tested on supercomputers and successfully used to resample the data from five instruments on the EOS-Terra platform at a mission-wide scale. |
format | Online Article Text |
id | pubmed-9392697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-93926972022-08-22 PYTAF: A Python Tool for Spatially Resampling Earth Observation Data Zhao, Guangyu Yang, Muqun Gao, Yizhao Zhan, Yizhe Lee, H. Joe Di Girolamo, Larry Earth Sci Inform Software Article Earth observation data have revolutionized Earth science and significantly enhanced the ability to forecast weather, climate and natural hazards. The storage format of the majority of Earth observation data can be classified into swath, grid or point structures. Earth science studies frequently involve resampling between swath, grid and point data when combining measurements from multiple instruments, which can provide more insights into geophysical processes than using any single instrument alone. As the amount of Earth observation data increases each day, the demand for a high computational efficient tool to resample and fuse Earth observation data has never been greater. We present a software tool, called pytaf, that resamples Earth observation data stored in swath, grid or point structures using a novel block indexing algorithm. This tool is specially designed to process large scale datasets. The core functions of pytaf were implemented in C with OpenMP to enable parallel computations in a shared memory environment. A user-friendly python interface was also built. The tool has been extensively tested on supercomputers and successfully used to resample the data from five instruments on the EOS-Terra platform at a mission-wide scale. Springer Berlin Heidelberg 2020-04-22 2022 /pmc/articles/PMC9392697/ /pubmed/36003900 http://dx.doi.org/10.1007/s12145-020-00461-w Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Software Article Zhao, Guangyu Yang, Muqun Gao, Yizhao Zhan, Yizhe Lee, H. Joe Di Girolamo, Larry PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title | PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title_full | PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title_fullStr | PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title_full_unstemmed | PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title_short | PYTAF: A Python Tool for Spatially Resampling Earth Observation Data |
title_sort | pytaf: a python tool for spatially resampling earth observation data |
topic | Software Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392697/ https://www.ncbi.nlm.nih.gov/pubmed/36003900 http://dx.doi.org/10.1007/s12145-020-00461-w |
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