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Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis

It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated s...

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Detalles Bibliográficos
Autores principales: Wen, Tao, Wei, Congxin, Wang, Zhenyi, Wang, Linzhu, Yang, Zihan, Gu, Tingting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610790/
https://www.ncbi.nlm.nih.gov/pubmed/37896539
http://dx.doi.org/10.3390/s23208446
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author Wen, Tao
Wei, Congxin
Wang, Zhenyi
Wang, Linzhu
Yang, Zihan
Gu, Tingting
author_facet Wen, Tao
Wei, Congxin
Wang, Zhenyi
Wang, Linzhu
Yang, Zihan
Gu, Tingting
author_sort Wen, Tao
collection PubMed
description It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination.
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spelling pubmed-106107902023-10-28 Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis Wen, Tao Wei, Congxin Wang, Zhenyi Wang, Linzhu Yang, Zihan Gu, Tingting Sensors (Basel) Article It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination. MDPI 2023-10-13 /pmc/articles/PMC10610790/ /pubmed/37896539 http://dx.doi.org/10.3390/s23208446 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wen, Tao
Wei, Congxin
Wang, Zhenyi
Wang, Linzhu
Yang, Zihan
Gu, Tingting
Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title_full Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title_fullStr Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title_full_unstemmed Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title_short Regional Thermal Radiation Characteristics of FY Satellite Remote Sensing Based on Big Data Analysis
title_sort regional thermal radiation characteristics of fy satellite remote sensing based on big data analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610790/
https://www.ncbi.nlm.nih.gov/pubmed/37896539
http://dx.doi.org/10.3390/s23208446
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