The Importance of Smartphones as Public Earthquake-Information Tools and Tools for the Rapid Engagement with Eyewitnesses: A Case Study of the 2015 Nepal Earthquake Sequence

2015 ◽  
Vol 86 (6) ◽  
pp. 1587-1592 ◽  
Author(s):  
Rémy Bossu ◽  
Maud Laurin ◽  
Gilles Mazet-Roux ◽  
Frédéric Roussel ◽  
Robert Steed
Keyword(s):  
Earthquake Sequence ◽  
Nepal Earthquake ◽  
Information Tools ◽  
2015 Nepal Earthquake

scholarly journals Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light Data: A Case Study of the 2015 Nepal Earthquake

2020 ◽  
Vol 12 (12) ◽  
pp. 2009 ◽  
Author(s):  
Shengjun Gao ◽  
Yunhao Chen ◽  
Long Liang ◽  
Adu Gong
Keyword(s):  
Infrared Imaging ◽  
Random Noise ◽  
Development Rate ◽  
Night Time ◽  
Nepal Earthquake ◽  
Decomposition Procedure ◽  
Spatiotemporal Changes ◽  
Reconstruction Rate ◽  
2015 Nepal Earthquake

Earthquakes are unpredictable and potentially destructive natural disasters that take a long time to recover from. Monitoring post-earthquake human activity (HA) is of great significance to recovery and reconstruction work. There is a strong correlation between night-time light (NTL) and HA, which aid in the study of spatiotemporal changes in post-earthquake human activities. However, seasonal and noise impact from National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) data greatly limits their application. To tackle these issues, random noise and seasonal fluctuation of NPP/VIIRS from January 2014 to December 2018 is removed by adopting the seasonal-trend decomposition procedure based on loess (STL). Based on the theory of post-earthquake recovery model, a post-earthquake night-time light piecewise (PNLP) pattern is explored by employing the National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) monthly data. PNLP indicators, including pre-earthquake development rate (kp), recovery rate (kr1), reconstruction rate (kr2), development rate (kd), relative reconstruction rate (krp) and loss (S), are defined to describe the PNLP pattern. Furthermore, the 2015 Nepal earthquake is chosen as a case study and the spatiotemporal changes in different areas are analyzed. The results reveal that: (1) STL is an effective algorithm for obtaining HA trend from the time series of denoising NTL; (2) the PNLP pattern, divided into four phases, namely the emergency phase (EP), recovery phase (RP-1), reconstruction phase (RP-2), and development phase (DP), aptly describes the variation in post-earthquake HA; (3) PNLP indicators are capable of evaluating the recovery differences across regions. The main socio-economic factors affecting the PNLP pattern and PNLP indicators are energy source for lighting, type of building, agricultural economy, and human poverty index. Based on the NPP/VIIRS data, the PNLP pattern can reflect the periodical changes of HA after earthquakes and provide an effective means for the analysis and evaluation of post-earthquake recovery and reconstruction.

Utilizing a 3D Global P‐Wave Tomography Model to Improve Backprojection Imaging: A Case Study of the 2015 Nepal Earthquake

2017 ◽  
Vol 107 (5) ◽  
pp. 2459-2466 ◽  
Author(s):  
Zhipeng Liu ◽  
Chao Song ◽  
Lingsen Meng ◽  
Zengxi Ge ◽  
Qinghua Huang ◽  
...  
Keyword(s):  
P Wave ◽  
Nepal Earthquake ◽  
Wave Tomography ◽  
2015 Nepal Earthquake

Resource mapping during a natural disaster: A case study on the 2015 Nepal earthquake

2017 ◽  
Vol 24 ◽  
pp. 24-31 ◽  
Author(s):  
Moumita Basu ◽  
Saptarshi Ghosh ◽  
Arnab Jana ◽  
Somprakash Bandyopadhyay ◽  
Ravikant Singh
Keyword(s):  
Natural Disaster ◽  
Resource Mapping ◽  
Nepal Earthquake ◽  
2015 Nepal Earthquake
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