Earthquake disasters and postdisaster reconstruction have profound impacts on human society. We use time series nighttime light images collected by the defense meteorological satellite program-operational linescan system sensors as a proxy data source for human activities (HAs). After calibration, a time series analysis method is used to study the distribution and intensity of the changes in HAs after an earthquake. We consider the Haiti earthquake an example to analyze the HA sequence patterns and the aggregation patterns of the HA centers. The results show the following: (1) postearthquake recovery and reconstruction efforts led to increases in the long-term HAs, but the level of increased HA was usually low. (2) The level of postearthquake HAs in the most affected areas (seismic intensity zone VIII+) increased, whereas the postearthquake HAs in severely affected areas (seismic intensity zones VI and VII) were more fragmented. (3) The recovery of HAs in seismic intensity zone VIII+ (mainly Port-au-Prince) required 2 years, but the actual time may be far longer.
In this paper, a fast correlation matching method in frequency domain was presented to extract the vehicle speed from a single QuickBird (QB) satellite image. Suppose the vehicles had been extracted from 0.6m resolution panchromatic image, we transformed the panchromatic and multispectral images into frequency domain and found the maximum correlation position to determine the exact coordinates of vehicles. Then the speed of moving vehicles were calculated using the shift between the two coordinates and the time gap between the two images. The novelty of this work is that the time consumption can be significantly reduced compared with the conventional area correlation matching method. This method makes it feasible to use satellite images for traffic statistics in large scale of road network.