Accurate data on the spatial distribution and potential growth estimation of human population are playing pivotal role in addressing and mitigating heavy lose caused by earthquake. Traditional demographic data is limited in its spatial resolution and is extremely hard to update. With the accessibility of massive DMSP/OLS night time imagery, it is possible to model population distribution at the county level across China. In order to compare and improve the continuity and consistency of time-series DMSP night-time satellite imagery obtained by different satellites in same year or different years by the same satellite from 2002-2010, normalized method was deployed for the inter-correction among imageries. And we referred to the reference F162007 Jixi city, whose social-economic has been relatively stable. Through binomial model, with average R2 0.90, then derived the correction factor of each year. The normalization obviously improved consistency comparing to previous data, which enhanced the correspondent accuracy of model. Then conducted the model of population density between average night-time light intensity in eight-economic districts. According to the two parameters variation law of consecutive years, established the prediction model of next following years with R2of slope and constant typically 0.85 to 0.95 in different regions. To validate the model, taking the year of 2005 as example, retrieved quantitatively population distribution in per square kilometer based on the model, then compared the results to the statistical data based on census, the difference of the result is acceptable. In summary, the estimation model facilitates the quick estimation and prediction in relieving the damage to people, which is significant in decision-making.
In this study, the wireless communication data obtained after the earthquake are introduced to rapidly assess the
earthquake disaster. Firstly, the wireless communication data including the real-time signaling data and the base station
data are used to analyze the activities and the relationship of the mobile phones and the base stations. Based on the
analysis results, five signaling parameters are selected and the Apriori algorithm is used to judge the damaged status of
the stations. All the base stations within the affected area of the earthquake are divided into several categories according
to the damage levels. Each category will produce a range of earthquake damage in the spatial domain within the affected
area. Finally, when the earthquake disaster-stricken areas are located, the extent of the damage will be estimated. The
Wenchuan earthquake, happened on May 12, 2008 in Sichuan Province of China reflects that the method discussed in the
paper is feasible. The Wenchuan EQ also shows that the wireless communication data is very useful when we assess the
damage soon after the disaster occurred, especially when there is no other way to get the field disaster information.
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