Building Damage Detection Based on OPCE Matching Algorithm Using a Single Post-Event PolSAR Data

Synthetic aperture radar (SAR) is an effective tool in detecting building damage. At present, more and more studies detect building damage using a single post-event fully polarimetric SAR (PolSAR) image, because it permits faster and more convenient damage detection work. However, the existence of non-buildings and obliquely-oriented buildings in disaster areas presents a challenge for obtaining accurate detection results using only post-event PolSAR data. To solve these problems, a new method is proposed in this work to detect completely collapsed buildings using a single post-event full polarization SAR image. The proposed method makes two improvements to building damage detection. First, it provides a more effective solution for non-building area removal in post-event PolSAR images. By selecting and combining three competitive polarization features, the proposed solution can remove most non-building areas effectively, including mountain vegetation and farmland areas, which are easily confused with collapsed buildings. Second, it significantly improves the classification performance of collapsed and standing buildings. A new polarization feature was created specifically for the classification of obliquely-oriented and collapsed buildings via development of the optimization of polarimetric contrast enhancement (OPCE) matching algorithm. Using this developed feature combined with texture features, the proposed method effectively distinguished collapsed and obliquely-oriented buildings, while simultaneously also identifying the affected collapsed buildings in error-prone areas. Experiments were implemented on three PolSAR datasets obtained in fully polarimetric mode: Radarsat-2 PolSAR data from the 2010 Yushu earthquake in China (resolution: 12 m, scale of the study area: ); ALOS PALSAR PolSAR data from the 2011 Tohoku tsunami in Japan (resolution: 23.14 m, scale of the study area: ); and ALOS-2 PolSAR data from the 2016 Kumamoto earthquake in Japan (resolution: 5.1 m, scale of the study area: ). Through the experiments, the proposed method was proven to obtain more than 90% accuracy for built-up area extraction in post-event PolSAR data. The achieved detection accuracies of building damage were 82.3%, 97.4%, and 78.5% in Yushu, Ishinomaki, and Mashiki town study sites, respectively.

The very low-frequency transmitter radio wave anomalies related to the 2010 Ms 7.1 Yushu earthquake observed by the DEMETER satellite and the possible mechanism

Earthquakes may disturb the lower ionosphere through various coupling mechanisms during the seismogenic and coseismic periods. The VLF (very low-frequency) signal radiated from ground-based transmitters will be affected when it penetrates the disturbed ionosphere above the epicenter area, and this anomaly can be recorded by low-Earth orbit satellites under certain conditions. In this paper, the temporal and spatial variation of the signal-to-noise ratio (SNR) of the VLF transmitter signal in the ionosphere over the epicenter of 2010 Yushu Ms 7.1 earthquake in China is analyzed using DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquake Regions) satellite observation. The results show that SNR over the epicenter of the Yushu earthquake especially in the southwestern region decreased (or dropped) before the main shock, and a GPS–TEC (Global Positioning System; total electron content) anomaly accompanied, which implies that the decrease in SNR might be caused by the enhancement of TEC. A full-wave method is used to study the mechanism of the change in SNR before the earthquake. The simulated results show SNR does not always decrease before an earthquake. When the electron density in the lower ionosphere increases by 3 times, the electric field will decrease about 2 dB, indicating that the disturbed-electric-field decrease of 20 % compared with the original electric field and vice versa. It can be concluded that the variation of electron density before earthquakes may be one of the important factors influencing the variation of SNR.

The VLF transmitters' radio wave anomalies related to 2010 Ms 7.1 Yushu earthquake observed by DEMETER satellite and the possible mechanism

Earthquakes may disturb the lower ionosphere through various coupling mechanisms during their seismogenic and coseismic periods. The VLF signal radiated from ground-based transmitters will get affected when it penetrates the disturbed region in the ionosphere above the epicenter area, and this anomaly can be recorded by low earth orbit satellite under certain conditions. In this paper, the temporal and spatial variation of the Signal to Noise Ratio (SNR) of the VLF transmitter signal in the ionosphere over the epicenter of 2010 Yushu Ms 7.1 earthquake in China is analyzed. The results show that the SNR over the epicenter of Yushu earthquake especially in the southwestern region decreased (or dropped)revealed by one satellite revisit period before the main shock, which is consistent with the observed TEC anomaly at same time, implying that the decrease of SNR might be caused by the enhancement of TEC. A full-wave method was used to study the mechanism of the change of SNR before the earthquake. When the electron density in the lower ionosphere increases by four times, the electric field will decrease about 1 dB, indicating that the disturbed electric field decrease 20 % compared with the original electric field and vice versa. It can be concluded that the variation of electron density before earthquakes may be one important factor influence the variation of SNR.

A Dynamic Shelter Location and Victim Resettlement Model Considering Equitable Waiting Costs

Catastrophic natural disasters cause devastating damage and leave a huge number of homeless people. Waiting for resettlement in a post-disaster environment brings human suffering, which is defined by waiting cost in this paper. Taking into account waiting cost and fairness consideration simultaneously, a mixed integer linear programming model is constructed for the multiperiod location-allocation process. Two fairness indicators are incorporated to guarantee both the whole-process equity and the periodic equity. The model is implemented in the General Algebraic Modeling System (GAMS) and solved by the CPLEX solver. An illustrative example is provided to explain the model characteristics. Furthermore, a case study of the Yushu earthquake is conducted to demonstrate the applicability of the model to practical problems.

Post-Traumatic Stress and School Adaptation in Adolescent Survivors Five Years after the 2010 Yushu Earthquake in China

(1) Background: The devastating Ms 7.1 earthquake struck Yushu city, China, in 2010, leading to serious consequences and damage in the central Tibetan Plateau. This study aimed to assess school adaptation and post-traumatic stress disorder (PTSD) symptoms of adolescent survivors five years after the Yushu earthquake. (2) Methods: A large-scale, school-based mental health survey was conducted 5 years after the earthquake among Tibetan students in the city of Yushu using the Adolescent’s School Adaptation Scale (ASAS) and the PTSD Checklist. (3) Results: A total of 1976 questionnaires were collected. A total of 30.7% of Tibetan adolescents had poor school adaptation and 19.5% were estimated as having probable PTSD. Logistic regression showed that females (OR = 0.73, 95% CI: 0.60–0.89), senior students (OR = 0.48, 95% CI: 0.39–0.59), and those who participated in post-disaster reconstruction (OR = 0.68, 95% CI: 0.54–0.85) were less likely to have poor school adaptation, while a positive association was observed among those buried under a collapsed building (OR = 1.47, 95% CI: 1.04–2.09) and those who experienced bereavement (OR = 1.77, 95% CI: 1.27–2.45). Students who had experienced bereavement were also more likely to have PTSD (OR = 1.60, 95% CI: 1.12–2.28). (4) Conclusions: The post-traumatic effects of the Yushu earthquake on Tibetan adolescents were severe and long-lasting. Sustainable long-term mental health services to help adolescents to restructure their mental health are necessary.