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Analysis Of Remote Sensing Estimation Of Urban Impervious Surface And Its Climatic Effect In Arid Area

Posted on:2019-08-03Degree:MasterType:Thesis
Country:ChinaCandidate:H J YuFull Text:PDF
GTID:2370330566466872Subject:Science
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Under the background of global urbanization,urban roads,roofs,squares and other impermeable water surfaces are growing rapidly,and the dynamic changes of impervious surfaces can reflect the spatial changes of urban development.Impermeable surface coverage is of great significance in evaluating the level of urbanization and the quality of urban ecological environment.Urumqi,the city with important influence along the route of"Belt and Road",has a certain degree of influence on the regional ecological climate because of the rapid expansion of impervious surface.As one of the most representative cities in arid areas,there are a lot of bare land in Urumqi.Soil drought,surface temperature and humidity have become important factors that affect the urban ecological climate and the degree of habitatants'comfort.This article takes the main urban area of Urumqi,a typical city in arid area,as the research area,uses Landsat TM/OLI image as the data source and uses the index method of impermeable surface and the mixed analysis method of linear spectrum to estimate impervious surfaces and the accuracy of different methods is compared and analyzed.Meanwhile,the surface temperature and humidity were extracted using a single-window algorithm and a cap conversion.On the basis of the above,this article conducts relevant research on the study area to explore the dynamic characteristics of the impermeable surface and its correlation with the urban climate effects so as to provide the decision basis for"urban double repair",the ecological restoration and urban repair to promote urban green development.The main conclusions of this article are as follows:(1)Compared with the ISA index,there is a higher degree of correlation between the estimated impervious surface coverage of the LSMA index and the actual value.among which,the estimation accuracy of Landsat 8 image is slightly better than that of Landsat TM.The statistical analysis of error distribution shows that the two methods are mostly overestimated.(2)The expansion of impervious surface in the main urban area of Urumqi is obvious,and the built-up area showed a significant exponential growth.from 1985 to2016.The high coverage area of impervious surface increased from 55.85 km~2 in 1994to 207.89 km ~2 in 2015.The coverage of impervious surface in the new urban area is higher and the increase is larger.The distribution of impermeable surface is mainly in the shape of"T"on the northwest-southeast direction.The cover of impermeable surface has the phenomena that the north and the west are high while the south and the east are low.(3)From 1994 to 2015,the heat island effect and dry island effect in the study area increased obviously.The average value of surface temperature increased greatly,and the urban high-temperature zone has a sheet-like discrete distribution and developed into a large-area sheet covering phenomenon..There is a heat island effect in the main urban area and a cold island effect in the central urban area sometimes.From 1994 to2015,the average surface humidity decreased obviously.Combined with the actual climate data statistics,it was found that the precipitation increased in the period of the study area but the average relative humidity decreased.(4)There is a positive correlation between the coverage of the impermeable surface and the urban heat island effect,and the influence of the coverage of the impervious surface on the heat island effect is weakened in the extremely high temperature region.The impact of impervious surface coverage on surface temperature is a critical value of 0.46.Besides,there is a negative correlation between the coverage of impermeable surface and the urban heat island effect.And passed the significance test of P<0.01.
Keywords/Search Tags:Impervious surface, ISA index, Linear spectral mixing analysis model, Surface temperature, Surface humidity
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