Study On Remote Sensing Extraction And Influence Mechainsm Of Heat Island Effect In Sanya City

With the accelerated development of urbanization,the urban heat island effect has gradually spread to most of the world's urban areas,seriously affecting the production and living of urban residents.In the previous urban heat island effect study,there are few researches on the characteristics of urban heat island effect change over a long time series.The methods are more complex and theorized.It is impossible to carry out the long-term multi-zone urban heat island monitoring application,based on Landsat data and nighttime.In light of the data,a complete set of surface urban heat island intensity(SUHII)monitoring operations including surface temperature inversion and suburban separation technology was established.Meanwhile,in view of the lack of heat island influence mechanism in the research of traditional heat island research,this paper was based on multi-source data and used multivariate regression analysis of principal components.The multivariate regression analysis of principal components method was used to study the comprehensive relationship between vegetation coverage,proportion of construction land,nighttime light intensity,density of road network,population density,area of built-up areas,number of buses,proportion of residential land,average precipitation and urban heat islands.This study can provide technical support for remote sensing monitoring of urban heat islands and provide a reasonable basis for sustainable urban development.In view of the above problems,this paper took Sanya city as a research area.The main research contents include:Using the radiation transmission equation method to perform surface temperature inversion based on Landsat thermal infrared data,and using IDL to calculate the surface temperature of Sanya city from 2000 to 2018.A new type of vegetation index:product normalized vegetation index(PNDVI)was proposed based on NDVI index.The vegetation coverage of Sanya was calculated using PNDVI with high accuracy,and the impervious surface information of Sanya from 2000 to 2018 was extracted based on the vegetation coverage.Based on the IDL program and CCA urban clustering algorithm,the impervious surface information was taken as input,and the boundary of the main built-up area of the city was extracted by operations.Using landsat data and nighttime lighting data to separate urban and suburban areas,and to establish separation rules and extract effective suburban areas.Finally,urban heat island intensity was calculated,and the time variation characteristics of heat island intensity in Sanya city from 2000 to 2018 were studied.The influence mechanism of multiple factors on the urban heat island effect was analyzed in depth.research results showed:IDL-based radiative transfer equation method for inversion of surface temperature can better meet the needs of long-term heat island monitoring research with higher speed and precision.It ensures the correctness of a series of processing such as data preprocessing and waveband operation.Systematically,it guarantees the integrity of the heat island effect monitoring.The new vegetation index PNDVI,which can better separate buildings and vegetation information,can be effectively applied to the extraction of sparse vegetation information within the urban construction area.Hence,results of impervious surface area calculated using PNDVI-based vegetation coverage are in good agreement with that of BCI index.Based on the nighttime lighting and MODIS land cover data,the establishment of rules for the separation of urban and suburban areas had yielded effective results,simplifying issues such as the inability and inaccuracy to extract existing suburbs and urban construction areas.During the 19 years,the change of heat islands in Sanya was relatively slow.The heat islands are mainly concentrated in the main impervious areas such as the airport business district,and tend to ease year by year.Impact mechanism analysis results showed that impervious surface factors(the proportion of construction land,built-up area,and residential land share)had the greatest promoting effect on SUHII,17.3%higher than urban transportation factors,and significantly larger than inhibiting effects of natural factors(vegetation)and climatic factors(average precipitation).From a single factor,the number of buses has the greatest contribution to promoting urban heat islands,and the density of road networks that are closely linked to the number of cars ranks second.For Sanya,the degree of impervious effect(1.494)is 3.6 times that of natural and climatic effects(0.407),only the further expansion of natural effects can play a role in reduction of SUHII.