Study On The Temperature Inversion Model Of Surface Composition In Urban Fringe Area

Land surface temperature is a key factor to study the global and regional surface air energy exchange and climate change.It is also the main factor characterizing the phenomenon of urban heat island.But,at present,the estimated surface temperature of satellite is the mean temperature of mixed pixel on a certain scale.lt can not replace the true temperature of the component in the pixel.Therefore,in this paper,the inversion of surface component temperature in the urban fringe of the rapid urbanization area is taken as the insertion point.A physical retrieval model of surface component temperature is constructed.This will help solve the key problem of component temperature inversion in the complex urban area of the urban fringe.And it also plays an important role in deepen the understanding of urban sustainable development.This paper takes Nanjing as the research area,based on GIS and RS technology,taking Landsat image as data source.The spectral mixture model with constrained least sqUares method is used to decompose the remote sensing image and decompose the surface component temperature at different times.Through the study,the following conclusions are drawn.(1)In 2006-2010,the urban fringe is wider than that in 2006.The south part of the Yangtze River was mainly composed of the outer boundary of the main urban area and the northern part of the Jiangning district.The north part of the Yangtze River was mainly composed of the southeastern part of Pukou district and the southwest part of Liuhe district.In 2010-2017,the south of the Yangtze River was mainly the ring area formed by the periphery of the main urban area and the northern part of Jiangning.The north of the ring extended slightly.The change in the north of the Yangtze River was more obvious.(2)In the bare soil abundance map,the high value area was mainly distributed in the rural area of farmland and urban periphery.And some construction land had similar spectra.So it also had relatively high value in the bare soil abundance image.In the image of impervious layer abundance,the high value area was mainly distributed along the south of Bagua island.And the RMSE value in the period of time is studied by statistical analysis,which can be found that the mixed pixel decomposition error is relatively small in this study.So the precision of the mixed pixel decomposition is high.(3)In the bare soil component temperature distribution map,the temperature of bare soil was higher.The impervious layer showed a higher temperature.A similar phenomenon appeared in the temperature distribution map of water and vegetation components.The average component temperature of the three images was:impervious layer>bare soil>vegetation>water.And by comparing with the measured temperature data,The results show that the surface component inversion model has high accuracy and meets the requirements of this research.(4)There is a correlation between land surface temperature and four kinds of endmember temperatures.The correlation between bare soil component temperature and land surface temperature is 0.92.Next is the water,and the correlation between vegetation component temperature and land surface temperature is relatively weak.And the correlation of each endmemeber is weak.