Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

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

Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light... <jats:p>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.</jats:p> http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Remote Sensing CrossRef

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

Remote Sensing , Volume 12 (12): 2009 – Jun 23, 2020

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


Abstract

<jats:p>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.</jats:p>

Loading next page...
 
/lp/crossref/post-earthquake-night-time-light-piecewise-pnlp-pattern-based-on-npp-dt5Ogg2rmj

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
CrossRef
ISSN
2072-4292
DOI
10.3390/rs12122009
Publisher site
See Article on Publisher Site

Abstract

<jats:p>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.</jats:p>

Journal

Remote SensingCrossRef

Published: Jun 23, 2020

There are no references for this article.