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To acquire daytime land surface temperature (LST) in thin cirrus cloudy skies, we have developed a three-channel LST retrieval algorithm based on a widely used two-channel LST retrieval algorithm for the clear-sky conditions. In this algorithm, the LST is expressed as a multiple linear function of MODIS channels 29, 31 and 32 with the coefficients of the linear function dependent on the cirrus optical depth (COD) and cirrus effective radius (R). The influences from land surface emissivities (LSEs) are also considered in this algorithm. The simulated dataset shows that the LST could be estimated using the proposed algorithm with the root mean squire error (RMSE) less than 2.2 K in thin cirrus cloudy skies (COD less than 0.7) when viewing zenith angle (VZA) equivalent to 0°. As VZA is equivalent to 60°, the maximum RMSE are 2.7 K. The widely used generalized split-window (GSW) algorithm proposed for clear-sky conditions are used in cirrus cloudy skies, and the RMSEs of GSW algorithm estimated LST are 16.89 K and 22.32 K for VZA =0° and VZA =60° respectively when COD is 0.7. It indicates that the proposed three-channel algorithm can significantly improve the LST retrieval accuracy using thermal infrared data in cirrus cloudy skies. To estimate the LST errors caused by the uncertainties of COD, R, LSE and instrument noise, a sensitivity analysis was performed. It shows that the accuracy of cirrus COD is more important for the retrieval of LST compared with other parameters. The maximum total LST errors, taking into account all the input parameters’ uncertainty and algorithm error itself, are 3.8 K and 4.3 K when VZA =0° and VZA =60° respectively.

After earthquake, the correct and efficient earthquake emergency evacuation of pedestrian is crucial for reducing casualties. Based on the research on the quantitative of panic coefficient and the calibration of initial desired speed, this research has constructed the revised social force model which could accurately simulate the post-earthquake evacuation process of the crowed. Using the revised social force model, the effects of classroom layout, seismic intensity, the number of safeties exits and the number of students in the classroom on the evacuation efficiency are further studied. And then, according to the research results, the classroom layout has been further optimized to improve the students’ earthquake emergency evacuation efficiency. These research results are scientific bases for the targeted earthquake emergency safety education and the design of classroom layout.

This article focuses on the rapid assessment of possible numbers of casualties after an earthquake. We use data on earthquake casualties to study and verify the relationship between casualties and building types, building anti-lethal levels, seismic intensity and other influencing factors. A rapid assessment method for casualties based on buildings’ anti-lethal level is proposed. The method first uses the anti-lethal level and proportions of various types of buildings to obtain the overall anti-lethal level of the study area. Second, according to historical casualty data, the casualty rate of each intensity in the study area is obtained. On this basis, a rapid assessment matrix of casualties is constructed based on the overall anti-lethal level of the study area and the casualty rate of each intensity. Finally, we make a rapid assessment of casualties based on a matrix model. Through the verification of 7 selected historical earthquakes, we find that the data on casualties obtained based on this method are close to the actual number of casualties. The resulting casualty parameters are described against the overall casualty data from several historical earthquakes in China, and the error rates of earthquakes in Lancang-Gengma, Yushu, Lushan Min county-Zhang county and Changning are 4.1%, 25.27%, 12.75%, 2% and 7.69%, respectively. The error is relatively small, within 50%, and a more accurate evaluation result is obtained. Our findings illustrate the effectiveness and practicability of a rapid assessment method for casualties based on anti-lethal levels.

To identify earthquake-damage areas after an earthquake occurs, a method based on Landsat-8 operational land imager (OLI) surface reflectance (SR) products is proposed. The SR pixels with the influences of clouds, cloud shadows, heavy aerosols, or instrument saturation are eliminated. Then, the mean and standard deviation (STD) images of SR products for two years before an earthquake are acquired; the mean images of the first three post-earthquake images are also obtained. The differences between post- and pre-earthquake mean SR images are taken to reflect the effects of the earthquake on SR. As we focus mainly on the impact of earthquakes on populated areas such as cities or villages, the pixels with Visible Infrared Imaging Radiometer Suite (VIIRS) day and night band annual average nighttime light products greater than 0 or Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data labeled ‘urban and built-up’ are taken as the study area for this work. Next, the areas with post- and pre-earthquake SR mean image differences greater than 0.1 and greater than 2 times the local STD are taken to represent earthquake-damaged areas. Finally, this method is applied to the 2015 Nepal moment magnitude (Mw) 7.8 earthquake. Compared with the actual damage data provided by the Nepal Earthquake 2015: Disaster Recovery and Reconstruction Information Platform (NDRRIP), the results show that the coefficient of determination between NDRRIP fully damaged buildings and Landsat-8 OLI SR data estimated damage pixels is 0.80 for the 69 Nepal districts not heavily influenced by snows.

It is well know that for the same intensity areas, the buildings with different structure types can show different vulnerabilities. Thus, building structure type is one the key parameters for rapid estimation of casualties and injuries after earthquake, which is vital for emergency response and rescue. To estimate building structure types, the buildings are firstly extracted based on the spectrum, texture, and height information of UAV visible images. Then, the structure type of individual extracted buildings is classified using convolution neural network. To evaluate the accuracy of the proposed method, the images of Xuyi county, Huai'an City, Jiangsu Province are acquired using a small rotorcraft UAV. The results show that the user accuracy and cartography accuracy are 80.69% and 78.42%, respectively.

After the earthquake, the correct and efficient earthquake emergency response modes of individuals are crucial for reducing casualties. Based on the keyword database of the earthquake emergency response behaviors of individuals, this research used the machine learning method to construct a decision tree of the earthquake emergency response modes. Through the decision tree, this study extracted decision rules that can predict the emergency response decisions of individuals in future earthquake and also determined the relative importance of six different factors (Seismic intensity > Social context >Location>Action>Age>Gender) in determining response behaviors. The set of rules was quite effective when evaluated using the test individuals with an overall accuracy of 85.23%. And then, combined with the cultural background in China, we had extracted and analyzed the main response modes of individuals at seismic intensities I-V, VI, VII, VIII-IX stricken regions by earthquake. The decision rules and main response modes of individuals were scientific bases for the targeted earthquake emergency safety education and the government emergency rescue.

To rapidly identify earthquake damage areas after earthquakes occur, a method based on Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) images with nearly constant c...

China is one of the most earthquake-prone countries in the world. The highest-priority mission after an earthquake is to rapidly save lives, and to minimize the loss of life. Rapid judgment of the trapped personnel location is the important basis to identify the emergency supply demands and carry out the search and rescue work after the earthquake. Through analyzing the main influencing factors, we constructed an assessment model of people trapped in collapsed buildings caused by the earthquakes. The accuracy of the estimation results from the model was then tested against the actual investigation data in 2014 Ludian earthquake-hit area. Results showed that, the trapped personnel distribution assessed by this model is generally concordant with that obtained by the actual survey in Ludian earthquake. The grid-based assessment of people trapped in earthquakes can meet the requirements of key search and rescue zone identification and rescue forces allocation in the early stage of earthquake emergency. Although there were some limitations in the study, it offers a simple and rapid approach for assessing the trapped people losses based on basic empirical data. The approach can be further improved to provide more information and suggestions for earthquake emergency search and rescue.

Lacustrine sediments on the eastern Tibetan Plateau (TP) contain a wealth of information on local and regional tectonic activity. High-resolution grain-size and magnetic susceptibility measurements were conducted on the 23.4-m-thick Lixian lacustrine sedimentary sequence spanning from 19.3 to 6.0 ka, revealing 70 prehistoric seismic events on the eastern TP. The seismic events caused intermittent increases in source materials that endowed the samples of an individual event layer with a gradual fining trend along the C = M line on a C (one percentile)-M (median diameter) plot. Grain-size distribution and end-member modeling imply that dust particles of

With the booming development of evacuation simulation software, developing an extensive database in indoor scenarios for evacuation models is imperative. In this paper, we conduct a qualitative and quantitative analysis of the collected videotapes and aim to provide a complete and unitary database of pedestrians' earthquake emergency response behaviors in indoor scenarios, including human-environment interactions. Using the qualitative analysis method, we extract keyword groups and keywords that code the response modes of pedestrians and construct a general decision flowchart using chronological organization. Using the quantitative analysis method, we analyze data on the delay time, evacuation speed, evacuation route and emergency exit choices. Furthermore, we study the effect of classroom layout on emergency evacuation. The database for indoor scenarios provides reliable input parameters and allows the construction of real and effective constraints for use in software and mathematical models. The database can also be used to validate the accuracy of evacuation models.

The accuracy of traditional spectral based land surface classification method can be decreased for areas with similarity spectral characters for different land cover types. To extract building distributions in those areas, a method based on the height information using unmanned aerial vehicle (UAV) optical remote sensing data were proposed in this study. With Digital Surface Model (DSM) and Digital Elevation Model (DEM) data produced by EasyUAV software using UAV acquired remote sensing images, the differences between DSM and DEM larger than 2.6 m was taken as a threshold for building extraction. It showed that the user accuracy and mapping accuracy of the building extraction method proposed in this study were 88.69% and 97.42%, respectively. To evaluate the performance of the proposed method, the buildings were also extracted based on traditional supervised classification method using Digital Orthophoto Map (DOM) produced by EasyUAV. The results showed that the new method was more accurate with the user accuracy and mapping accuracy of the supervised classification method of 43.23% and 85.30%, respectively.

The atmospheric aerosols are one of the uncertainties that significantly influence the study of energy balance at regional or global scale. However, few studies focus on the aerosols caused by earthquake induced damage of hazard-affected bodies. To study the influences of earthquakes on the loadings of atmospheric aerosols, the AErosol RObotic NETwork (AERONET) sites retrieved aerosol optical depth (AOD) are used in this study. It showed that the AOD became larger after earthquakes for six cases in this study. After approximately one day, the AOD of the six cases tend to close to the normal range. In addition, the other four cases show that the there is no significant increasement of AOD or the AOD tend to become smaller after earthquake.