Study On The Prediction Of Urban Thermal Landscape Based On Improved CA-Markov Model

The response of urban ecological environment to the process of urbanization has always been a heat topic in urban research.The urban thermal landscape is the result of applying the landscape classification method to the surface heat field,and it can fully demonstrate the effect of human activities on the distribution of urban heat island in the process of urbanization.As the economic center and the National Central City in Bohai Rim,Tianjin is one of the most significant urbanization areas in China in recent decades.Especially after the Binhai New Area is incorporated into the national strategic plan,the problem of thermal environment in city is becoming more and more serious.In this paper,a total of 11 administrative districts in center city,surrounding city and Binhai New Area in Tianjin are selected as the study objects.Firstly,the land surface temperature of the 1992,2006,2014 and 2016 period was retrieved by Landsat satellite images.Secondly,based on the classification of the thermal landscape level,we quantitatively analyzed the spatiotemporal evolution characteristics of the thermal landscape pattern in the main urban areas of Tianjin in recent twenty years based on the area transfer matrix,the cross section method and the transfer centroid method.The results show that,in general,the land surface temperature of urban area in Tianjin is gradually rising while the land surface temperature in central urban area is decreasing.The total area of the high temperature region(high temperature area and sub high temperature area)in the surrounding city area has changed little,and the overall land surface temperature in Binhai New Area is rising.Thirdly,the linear fitting and trend analysis between land surface temperature and surface parameters were carried out.The results show that:(1)NDVI has a positive correlation with land surface temperature overall owing to the large water area,but the relationship between them can not well explained by linear fitting.(2)MNDWI has a highly significant negative correlation with land surface temperature,and the relationship between them can be explained by linear fitting to a certain extent.(3)The surface temperature has a highly significant positive correlation with NDISI,and the relationship between them is not suitable to be explained linearly.Besides,combining with the geostatistical methods with landscape pattern indices to analyze the thermal landscape,results show that:(1)Binhai New Area show the strongest spatial autocorrelation in land surface temperature,followed by the surrounding urban area,while the central city is weak.(2)The variety of patches in the central city is single,and there is a dominant temperature area that occupies most of the total area.The edge of patches in the surrounding city is the most complex.There are many kinds of patches with scattered distribution and common complexity of edges in each temperature area in Binhai New Area.(3)The resident population has a very significant positive correlation with PLAND and LPI.Therefore,controlling population quantity is very important for solving the problem of thermal environment.Last but not least,by introducing the idea of data assimilation based on the previous research,we improved the CA-Markov model and predicted the thermal landscape in Tianjin in 2020.According to the analysis results,the countermeasures and suggestions for mitigating the heat island effect are put forward.