Abstract
Evacuation plans are critical in case of natural disaster to save people’s lives. The priority of population evacuation on coastal areas could be useful to reduce the death toll in case of tsunami hazard. In this study, the population density remote sensing mapping approach was developed using population records in 2013 and Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) night-time light (NTL) image of the same year for defining the coastal densest resident areas in Pearl River Estuary (PRE), China. Two pixel-based saturation correction methods were evaluated for application of population density mapping to enhance DMSP/OLS NTL image. The Vegetation Adjusted NTL Urban Index (VANUI) correction method (R2 (original/corrected): 0.504, Std. error: 0.0069) was found to be the better-fit correction method of NTL image saturation for the study area compared to Human Settlement Index (HSI) correction method (R2 (original/corrected): 0.219, Std. error: 0.1676). The study also gained a better dynamic range of HSI correction (0~25 vs. 0.1~5.07) compared to the previous one [27]. The town-level’s population NTL simulation model is built (R2 = 0.43, N = 47) for the first time in PRE with mean relative error (MSE) of 32% (N = 24, town level), On the other side, the tsunami hazard map was produced based on numerical modeling of potential tsunami wave height and velocity, combining with the river net system, elevation, slope, and vegetation cover factors. Both results were combined to produce an evacuation map in PRE. The simulation of tsunami exposure on density of population showed that the highest evacuation priority was found to be in most of Zhuhai city area and the coastal area of Shenzhen City under wave height of nine meters, while lowest evacuation priority was defined in Panyu and Nansha Districts of Guangzhou City, eastern and western parts of Zhongshan City, and northeast and northwest parts of Dongguan City. The method of tsunami risk simulation and the result of mapped tsunami exposure are of significance for direction to tsunami disaster-risk reduction or evacuation traffic arrangement in PRE or other coastal areas in the world.
Highlights
A tsunami can severely influence coastal areas in many countries worldwide
Data Collection The latest available cloud-free DMSP/Operational Line-scan Systems (OLS) night-time light (NTL) composite image provided by the American
The DMSP satellites are in low-altitude (830 km) sun-synchronous polar orbits and carry oscillating scan radiometers—Operational Line-scan Systems (OLS)—with low-light visible and thermal infrared imaging capabilities
Summary
A tsunami can severely influence coastal areas in many countries worldwide. It is one of the most devastating natural coastal disasters. Submarine earthquakes occurring in subduction zones generate most of the large tsunamis. Tsunamis can be triggered by volcanic eruptions and massive landslides [1,2]. The population evacuation plan is critical for coastal people safety in case of a tsunami hazard. Reliable information on population distribution is essential to help decision-makers to reduce the death toll of the disaster occurring. It is crucial to map population distribution in coastal areas and include it in evacuation planning to give the government a chance to take the right decision in evacuation prioritization and rescue operations
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