A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities
The monitoring of earthquake events is a very important and challenging task. Remote sensing technology has been found to strengthen the monitoring abilities of the Earth’s surface at a macroscopic scale. Therefore, it has proven to be very helpful in the exploration of some important anom...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-12-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/10/12/1941 |
| _version_ | 1828128770813329408 |
|---|---|
| author | Dongmei Song Ruihuan Xie Lin Zang Jingyuan Yin Kai Qin Xinjian Shan Jianyong Cui Bin Wang |
| author_facet | Dongmei Song Ruihuan Xie Lin Zang Jingyuan Yin Kai Qin Xinjian Shan Jianyong Cui Bin Wang |
| author_sort | Dongmei Song |
| collection | DOAJ |
| description | The monitoring of earthquake events is a very important and challenging task. Remote sensing technology has been found to strengthen the monitoring abilities of the Earth’s surface at a macroscopic scale. Therefore, it has proven to be very helpful in the exploration of some important anomalies, which cannot be seen in a small scope. Previously, thermal infrared (TIR) anomalies have been widely regarded as indications of early warnings for earthquake events. At the present time, some classic algorithms exist, which have been developed to extract TIR anomaly signals before the onset of large earthquakes. In this research study, with the aim of addressing some of the deficiencies of the classic algorithm, which is currently used for noise filtering during the process of extracting tectonic TIR anomalies signals, a novel TTIA (tectonic thermal infrared anomalies) algorithm was proposed to characterize earthquake TIR anomalies using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature dataset (MOD11A2). Then, for the purpose of determining the rule of the TIR anomalies prior to large earthquake events, the Qinghai-Tibet Plateau in China was chosen as the study area. It is known that tectonic movements are very active in the study area, and major earthquakes often occur. The following conclusions were obtained from the experimental results of this study: (1) The TIR anomalies extracted using the proposed TTIA method showed a very obvious spatial distribution characteristic along the tectonic faults, which indicated that the proposed algorithm had distinctive advantages in removing or weakening the disturbances of the atectonic TIR anomalies signals; (2) The seismogenic zone was observed to be a more effective observation scale for assisting in the deeper understanding and investigations of the mid- and short-term seismogenic and crust stress change processes; (3) The movement trace of the centroids of the TIR anomalies on the Tibetan Plateau three years prior to earthquake events contributed to improved judgments of dangerous regions where major earthquakes may occur in the future. |
| first_indexed | 2024-04-11T16:09:26Z |
| format | Article |
| id | doaj.art-46ad0770f91e40b681225548d796b40e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T16:09:26Z |
| publishDate | 2018-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-46ad0770f91e40b681225548d796b40e2022-12-22T04:14:43ZengMDPI AGRemote Sensing2072-42922018-12-011012194110.3390/rs10121941rs10121941A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic ActivitiesDongmei Song0Ruihuan Xie1Lin Zang2Jingyuan Yin3Kai Qin4Xinjian Shan5Jianyong Cui6Bin Wang7The School of Geosciences, China University of Petroleum (East China), Qingdao 266580, ChinaThe School of Geosciences, China University of Petroleum (East China), Qingdao 266580, ChinaThe State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaShanghai Earthquake Administration, Shanghai 200062, ChinaThe School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, ChinaThe State Key Laboratory of Earthquake Dynamics, Beijing 100029, ChinaThe School of Geosciences, China University of Petroleum (East China), Qingdao 266580, ChinaThe School of Geosciences, China University of Petroleum (East China), Qingdao 266580, ChinaThe monitoring of earthquake events is a very important and challenging task. Remote sensing technology has been found to strengthen the monitoring abilities of the Earth’s surface at a macroscopic scale. Therefore, it has proven to be very helpful in the exploration of some important anomalies, which cannot be seen in a small scope. Previously, thermal infrared (TIR) anomalies have been widely regarded as indications of early warnings for earthquake events. At the present time, some classic algorithms exist, which have been developed to extract TIR anomaly signals before the onset of large earthquakes. In this research study, with the aim of addressing some of the deficiencies of the classic algorithm, which is currently used for noise filtering during the process of extracting tectonic TIR anomalies signals, a novel TTIA (tectonic thermal infrared anomalies) algorithm was proposed to characterize earthquake TIR anomalies using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature dataset (MOD11A2). Then, for the purpose of determining the rule of the TIR anomalies prior to large earthquake events, the Qinghai-Tibet Plateau in China was chosen as the study area. It is known that tectonic movements are very active in the study area, and major earthquakes often occur. The following conclusions were obtained from the experimental results of this study: (1) The TIR anomalies extracted using the proposed TTIA method showed a very obvious spatial distribution characteristic along the tectonic faults, which indicated that the proposed algorithm had distinctive advantages in removing or weakening the disturbances of the atectonic TIR anomalies signals; (2) The seismogenic zone was observed to be a more effective observation scale for assisting in the deeper understanding and investigations of the mid- and short-term seismogenic and crust stress change processes; (3) The movement trace of the centroids of the TIR anomalies on the Tibetan Plateau three years prior to earthquake events contributed to improved judgments of dangerous regions where major earthquakes may occur in the future.https://www.mdpi.com/2072-4292/10/12/1941tectonic thermal infrared anomalieswavelet transformTTIA algorithmearthquake events |
| spellingShingle | Dongmei Song Ruihuan Xie Lin Zang Jingyuan Yin Kai Qin Xinjian Shan Jianyong Cui Bin Wang A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities Remote Sensing tectonic thermal infrared anomalies wavelet transform TTIA algorithm earthquake events |
| title | A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities |
| title_full | A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities |
| title_fullStr | A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities |
| title_full_unstemmed | A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities |
| title_short | A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities |
| title_sort | new algorithm for the characterization of thermal infrared anomalies in tectonic activities |
| topic | tectonic thermal infrared anomalies wavelet transform TTIA algorithm earthquake events |
| url | https://www.mdpi.com/2072-4292/10/12/1941 |
| work_keys_str_mv | AT dongmeisong anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT ruihuanxie anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT linzang anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT jingyuanyin anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT kaiqin anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT xinjianshan anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT jianyongcui anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT binwang anewalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT dongmeisong newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT ruihuanxie newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT linzang newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT jingyuanyin newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT kaiqin newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT xinjianshan newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT jianyongcui newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities AT binwang newalgorithmforthecharacterizationofthermalinfraredanomaliesintectonicactivities |