| With global warming and the fast pace of urbanization,flood disaster risk in cities has become a hot issue worldwide and a cutting-edge research subject.With a high frequency of sudden rainstorms in Shanghai,the dynamic spatial-temporal pattern of population is an urgent problem to be solved in the study of population risk.With reference to the systematic previous studies,based on the urban intensive data containing census data,floating car data and basic geographic data etc,using the methods of population estimation models and scene simulation,this thesis discusses the hourly spatial-temporal patterns of population distribution in Shanghai,and analyzes the urban population and the risk of flooding in the 100 a rainstorm water logging situation,mainly concerning hazard-formative factors,exposure and vulnerability risk analysis,and population risk assessment.The main work and conclusions of this research are as follows:(1)The processing and integration of intensive data.In the processing of floating car data,supported by the Postgre SQL database,the original data are structured in order to be stored,and floating car data at the drop-off points and the pick-up points are retrieved with a cleaning program.The area weight model is adopted for intensive data to generate 1 km × 1 km grid in Arc GIS,and thus data integration is carried out.(2)To reveal the trends in the changes of floating car data at the drop-off points and the pick-up points within 24 hours through floating car data analysis.There is a consistent trend in the change of the drop-off points and the pick-up points in the 24-hour period of 5 working days,and there is also a consistent trend in the change of the net inflow of floating car in the 24-hour period of 5 working days.The spatial distribution of drop-off points and the pick-up point basically has coherent characteristics of variation.Hot spots mainly distribute in the core urban area within the inner ring,including Jing'an District,Huangpu District and Luwan District,with a decreasing trend from the center to the outward.According to the spatial changes of net inflow of the floating car,the urban core area at night(from 18:00 to 4:00)is dominated by outflow.The intensity of outflow shows a process of increasing and then decreasing,and the area shows a process of increasing and then decreasing with time.The daytime period(from 5:00 to 12:00)is dominated by inflow.The intensity of inflow shows a process of increasing and then decreasing,and the area shows a process of increasing and then decreasing with time.The rest of the daytime is mainly dominated by outflow.(3)The population estimation model is constructed based on the floating car data,population census data and employed population data from the economic censuses,and the model is further improved,being verified by cellular signaling data.Based on cellular signaling data,the results of the population estimation model are positively associated with the cellular data(P<0.01)and the correlation is significant.In the analysis of relative errors,it is found that within a margin of error of ±10%,the percentage of relative errors over 50% occurs only in 7 periods;within the error of ±15%,it is found in 10 periods and within the error of ±20%,in 15 periods.According to the proportion of overestimation and underestimation of population in the results estimated by cellular data,the proportion of overestimation and underestimation in the nighttime are very close.While during the daytime,underestimation occurs more often in most regions.Based on the correlation analysis and the error analysis of cellular signaling data,it is considered that the population estimation model based on intensive data can be applied to population estimation.(4)To observe the hourly population of the studied areas using the population estimation model constructed according to the intensive data,and to reveal the dynamic trends of the spatial distribution of population within 24 hours.The findings are as follows.For the spatial distribution of population from 0:00 AM to 23:00 PM,the high and below high levels of population density mainly distribute within the inner ring to the west of the Huangpu River and at the outer edge of the western and northern inner ring;the low and above low levels of population density mainly distribute near the outer ring,namely the outer peripheral areas of this research.There exists a rather distinctive single-centered pattern.For the mobility of population from 0:00 AM to 23:00 PM,in most places of the core urban area,the population mobility is characterized by inflow during the period from 2:00 AM to 13:00 PM and by outflow during the period from 14:00 PM to 1:00 AM.While in the outer peripheral areas,the population mobility is characterized by outflow between from 5:00 AM to 15:00 PM and by inflow from 16:00 PM to 4:00 PM.There are two periods with the strongest population mobility,which are the morning peak time from 6:00 AM to 9:00 AM and the period from 19:00 PM to 22:00 PM.The proportion of population distribution in each type of land use in different districts basically changes little.According to statistics in all the districts being studied,residential land,among all the land use types,is the one with the largest inflow and outflow of population.(5)To obtain the inundation scenarios of four rain peak locations using the rainstorm intensity formula and the Chicago rain pattern formula to calculate the rainfall process,the SCS model to calculate the runoff process,and the iso-volume method to simulate the process of the three inundation scenarios.The characteristics of the spatial distribution of population in the four flood scenarios are as follows.The population affected by the rainstorm water logging at the four rain peak locations mainly concentrates in the core urban areas,with a decreasing trend from the single center to the outward.When the rain peak reaches 0.5,the number of people affected rises to its highest,3.288 million,and this occurs at noon(12:00 PM and 13:00 PM).Then the number falls to 2.890 million in the evening(17:00 PM),and continues to fall to 2.518 million in the morning(8:00 AM)and then to 2.272 million at night(3:00 AM and 4:00 AM).The analysis of population vulnerability is carried out by constructing the population vulnerability curve.There is an exponential correlation between the submersion depth and the population density,with a c orrelation coefficient of 0.896(R).There is also an exponential correlation between the submersion volume and the number of population affected,with a correlation coefficient of 0.855(R).(6)The core urban areas along the Suzhou River are most likely to be attacked by water logging in hundred-year rainstorms,with the most risky period at 17:00 PM when the rain peak reaching to 0.7.Other high risk periods include 8:00 AM when the rain peak reaching 0.3,12:00 to 13:00 PM when the rain peak coming to 0.5,and 3:00 to 4:00 AM when the rain peak arrives at 0.1.The population risk varies most obviously during the period of 3:00 to 4:00 AM,dropping quite distinctively,and shows a slight decrease during the period of 12:00 to 13:00 PM. |
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