Concept of Computer Vision Based Algorithm for Detecting Thermal Anomalies in Reinforced Concrete Structures

In Hong Kong, there is great abundancy of aged buildings and infrastructures for which a re-assessment of the current status is needed. Water exfiltrations/infiltrations, deteriorating insulations, thermal bridges and regions of failure are among the most recurrent symptoms to be found in existing Reinforced Concrete (RC) structures. Diagnosis of such symptoms, in the form of thermal infrared anomalies, is usually performed through infrared (IR) image capturing, followed by qualitative assessment. This paper presents a novel automated computer-vision-based method for detecting thermal anomalies. Such Computer-Vision (CV) algorithm is tested on different thermal scenarios including beam elements, roofs and entire façades of RC buildings. Thermal anomalies related to cases of water leakages, moisture trapping and debonding are successfully detected. The authors intend to undertake further research for successfully implementing the method for detecting also other thermal dissimilarities.

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 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.

A Statistical Analysis of TIR Anomalies extracted by RST in Relation with Earthquake in Sichuan Area with Use of MODIS LST Data

There is a long history for research of earthquake prediction, but weakness of traditional approaches to study seismic hazard have been more and more evident. Remote sensing and earth observation technology, which is a new method that can instantly acquire a large area of abnormal information caused by earthquakes, is believed to be the key to the breakthrough of the bottleneck in the study of earthquake prediction. A multi-parametric approach seems, instead, to be the most promising approach in order to increase reliability and precision of short-term seismic hazard forecast, and Thermal Infrared (TIR) anomaly is an important part of the earthquake precursors. Though many scientists have studied the correlation among TIR anomalies identified by the Robust Satellite Techniques (RST) methodology and single earthquake, there is few study to extract the TIR anomalies in long period and large study area. Moreover, a statistical analysis of TIR anomalies in relation with earthquake is needed to determine whether there is the existence of TIR anomalies before earthquake. In this paper, a refined RST data analysis and Robust Estimator of TIR Anomalies (RETIRA) index were used to extract the TIR anomalies from 2002 to 2018 in Sichuan area with use of Moderate-resolution Imaging Spectro-radiometer (MODIS) Land Surface Temperature (LST), and the earthquake catalog were also used to study the correlation between TIR anomalies and occurrences of earthquake. Most of the thermal infrared anomalies correspond to earthquakes, and statistical methods are used to prove that there is a correlation between the extracted thermal infrared anomalies and earthquakes. And this is the first time to evaluate earthquakes prediction ability with use of PPV, FDR, TPR and FNR, the statistical result shows that the prediction ability of RST in Sichuan area is limited.

Thermal Infrared Anomalies of Several Strong Earthquakes

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up toMs7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of “time-frequency relative power spectrum.” (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting.