Based On Heat Island Effect's Green Space Quality Optimization In The Main City Of Fuzhou

In recent years,with the accelerated process of urbanization in Fuzhou,the city heat island problem has become increasingly prominent.Urban green space as an important part of urban ecosystem is a key factor to adjust the urban thermal environment,while through reasonable optimization of urban green space can effectively alleviate the problem of urban heat island.Based on the Landsat8 image data of July 24,2016,extraction of city green space,temperature and other information,correlation analysis of 40 typical city green patches and green cooling capacity of the main city of Fuzhou,and combined with the random forest algorithm to determine the green plaque index weight,to build urban green space cooling system,while based on population density,heat island intensity and distribution pattern of green space cooling,and combined with the P-median optimization model,proposes a scheme to optimize the urban green space in Fuzhou city based on mitigating heat island effect,the main conclusions are as follows:(1)The surface temperature of Fuzhou,which is inversion by using the radiation transport equation method,has a good linear correlation with the corresponding observation point temperature,and has a good spatial distribution of the urban heat island.The mean standard deviation method(?±?,?±0.5?)is used to divide the urban temperature pattern into lower temperature,low temperature,medium temperature,secondary high temperature,high temperature and extra high temperature zone,the results show that the urban core heat island is clustered in the urban commercial,residential and industrial areas,the urban heat island effect is obvious.(2)Based on the principle of landscape ecology,using Landsat remote sensing image,combined with Google Earth image of high precision,extracted 40 typical urban green space in Fuzhou city,and used buffer zone method to analyze the cooling effect of urban green space.The results showed that there were significant differences in the cooling rate of different urban green spaces,mainly distributed in 1 to 4.By comparing the area,perimeter,shape index,vegetation coverage and greening rate of 40 urban green areas,the area,perimeter,shape index and vegetation coverage index of green patches have a obvious effect on the temperature reduction of green space,the relationship of determine coefficient is:vegetation coverage(R2=0.6505)>area(R2=0.5209)>perimeter(R2=0.5011)>shape index(R2=0.4097),and the area,Perimeter,shape index and vegetation coverage were logarithmic model positive correlation,the effect of the index is obvious,that is,with the increase of the index,the effect of the greening rate is gradually weakened,while the vegetation coverage is linearly correlated with the greening rate,and it's has no obvious upper limit.(3)Based on green space cooling range,Random forest method was used to determine the green patch index of 40 typical urban green space in Fuzhou,according to the weight value of the 94 main cities of Fuzhou city green space cooling coefficient,to achieve the city center of Fuzhou city green space cooling effect evaluation.The results showed that the intensity of green patch index of 40 typical urban green space in Fuzhou city is,vegetation coverage(0.4253)>perimeter(0.2690)>area(0.1815)>shape index(0.1242);Fuzhou city green elements is complete,the city core cooling green overall bias in southern Cangshan district and Gulou district,and near the city center city fringe,lack of primary cooling green space in city center,urban green space cooling pattern problem highlights.(4)To ease the city heat island and improve the living environment of urban residents as the starting points,analysis of the layout of urban cooling demand,the results showed that the higher level city cooling demand areas are mainly located in the area of the core area of the city's commercial,financial and Gulou living district,Jinan district and Taijiang district,as well as intersection of industrial district and linving district of southern Tainan Road of Cangshan,therefore,it is possible to improve the urban thermal environment by optimizing the urban green space with More targeted.(5)Consider the city green cooling characteristics,economic and population needs and other issues,Select the city core cooling demand area is greater than 5ha regional role for the improvement of the object,using P-middle model as the city median potential cooling node green space optimization model to determine the optimal intensity of city green space node.The results show that the number of city primary grade optimization of Greenland is 6,mainly for the city center cooling ability of the poor city park and scenic forest,need priority,focus on optimization;second grade optimization green is 13,including city park,small mountain,attached green space and Scenic forest space should be affiliated to idle,at third grade and fourth grade optimization;optimization green was 3,mainly for the city with waterfront greenbelt,the cooling capacity is better than the or second grade of green space,need selective optimization.