Study On Urban Impervious Surface Retrieval And Correlation Between Urban Heat Island And Precipitation Based On Remote Sensing

The expansion of impervious surface is one of the most important indices which can represent the degree of urbanization.Impervious surface include building,roads,commercial facilities and public service facilities,et al.The increase of impervious surface in an urban area can influent the urban water circle and cause urban heat island,urban rain island and urban dry island.The objective of sponge city is to reduce the influence of urban development to hydrological cycle,and reduce urban heat island,Urban Rain Island and urban dry island and so on.Urban impervious surface also can be an important index of sponge city planning,so the accurate calculation of urban impervious surface is of great significance to the planning and design of sponge City,especially to the reconstruction of sponge city in built-up area.At the same time,how to assess the impact of urban impervious mats on urban heat island and precipitation also have a great significance to evaluate the construction of sponge city.Information richness and temporal scale of remote sensing images are better than traditional data.The impervious surface information can have a relatively accurate inversion based on the performance of satellite remote sensing sensor,which can break through the limit of the human eye observation,and can receive the spectral information of different wavelengths.In this study,an area which is located in northern Henan province was chose as the study area.The study area include three main urban area namely Anyang,Tangyin and Qibin area.Landsat 5 TM images from 1993 ~ 2011 were chose for impervious surface extraction.Temperature data in China of MODIS from 2000 ~ 2015 and meteorological station precipitation data of Anyang were chose for the analysis of heat island and precipitation.In addition,a 1:1000 topographic map of Qibin area was chose as the validation data of impervious surface extraction.At first,we build a BP artificial neural network to do a classification in Qibin area and got the impervious coverage map.After the GIS conversion from AutoCAD,the1:1000 topographic map was used to verify classification accuracy.The results showed a good classification consistency based on the overall accuracy of the classification is79.82%,the user accuracy of impervious surface is 82.31%,the producer accuracy of impervious surface is 83.49%,and the Kappa coefficient is 0.65.On the basis of theabove,impervious surface of Qibin area were extracted in a long time series and the expansion pattern was analyzed.Impervious surface of whole study area also were extracted from 2000 to 2011 for analyzing the extent of urban development in the study area.For studying the influence of urban expansion on the temperature and precipitation,some method as follows were used and some relationships were got from data:1.We chose a year as a node to divide the precipitation data into two parts.Before and behind this year,Degree of urbanization was quite different.Student's T test and Mann-Kendall trend tests were applied to analyze the change and trend of precipitation data,and the results showed no significant change in precipitation data during 1951 ~2014.2.Urban summer night temperature must be analyzed because the significant heat island effect in summer and lasting temperature holding capacity of building in night.Accordingly,the temperature in the urban and suburban areas is separately calculated and contrasted,the results showed an obvious heat island effect in the study area.3.In order to test the correlation between urban heat island and precipitation,Pearson product moment correlation coefficient method was used to do a correlation test between summer night temperature data and precipitation data from 2000 ~ 2014 and the result showed a significant correlation.The innovations and findings of this study are as follows:1.Using self created BP neural network classifier to interpret remote sensing images can obtain reliable results.2.Trying to use the Mann-Kendall trend test and the student T test to study the impacts of urbanization on precipitation and temperature.3.A significant correlation between urban summer night temperature and annual precipitation was got by Pearson product moment correlation coefficient method.