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Land Surface Temperature Inversion Of Xi’an And The Urban Thermal Environment Research Based On RS

Posted on:2016-02-20Degree:MasterType:Thesis
Country:ChinaCandidate:L WangFull Text:PDF
GTID:2191330476450853Subject:Surveying and mapping engineering
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With the rapid development of urbanization and industrialization, land use/ types of cover and landscape pattern have changed as well as urban thermal environment so that a series of issues of environments and zoology. Urban thermal environment issue has gradually been taken seriously since urban heat island effect was brought firstly in 1988. Nowadays, urban thermal environment issue is not only the focus of academic research, but the one must to be dealt with for establishing new modern city. Xi’an is lying in Guanzhong Plain locating in the medium Yellow River. In advance by the West Development and strategy of international metropolis these years, the scope of Xi’an has been expanding and the problem of thermal environment stands out day by day. This article uses the data of Landsat-5 TM and Landsat-8 TIRS-OLI on 7.17.1992, 7.24.2006 and 6.25.2013 backscattered the surface temperature of six districts in Xi’an by mono-window algorithm and analyses and estimates surface temperature of Xi’an in different times; introduces landscape ecological theory, and uses landscape pattern index to analyze and estimate the thermal landscape pattern dynamic evolution of six districts in Xi’an; extracts NDVI,NDBI and NDWI in researching area and uses extracting feature section to study the relation of urban heat island effect, vegetation, building coverage and water body, as well as discussing the quantitative relation of bare land, urban building areas, green land, water body and surface temperature combining the result of supervised classification. And below are the conclusions:(1) From 1992 to 2013, the heat island effect showed a trend of increase in Xi’an. The result of grading by temperature normalization method shows: the percentage of the area of ultra-heat island district increases from 0.03% to 9.76%, heat island district increases from 0.56% to 54.76%, and the middle district expand from 11.93% to 30.09%, while the green island decreases from 84.19% to 4.45%, and the ultra-green island decreases from 3.28% to 0.95%. Among these, heat island has a substantial increase with the extension from the centre of city to outer city; while the area of green island is reducing. The heat island effect shows a trend of increase.(2) Thermal landscape spatial distribution changes. The heat island in Xi’an presents a changing feature of dot-, sheet-, transfer-like in late 21 years. The heat islands distributed in main city zones in 1992, covered them sheet-like in 2006, and expanded from city to country in 2003.(3) Time and space differences of thermal landscape pattern are large, but gradually stabilize. As for the plaque area, the dominant type in landscape pattern was green island in 1992, ultra-heat island in 2006, heat island the largest in 2013; as for aggregation degree, landscape features was gathering gradually from 1992 to 2013; as for landscape level, the fragmentation of landscape features was reducing and the patchiness tended to be stable.(4) Surface temperature and land cover types have relation. LST and NDVI have obviously negative correlations; LST and NDBI are positively related; LST and NDWI are negatively related, which means green land and water body have a good cooling effect. The land cover types through supervising classification overlaid with surface temperature and we get the results: the surface covering various types of average temperature for the order from high to low is building districts in cities> bare land> green land> water body, in 2003: bare land> building districts in cities> green land> water body. As a result, reasonable control of urban construction and bare land area, and effectively increase of green and water area plays a positive role to alleviate urban heat island effect.
Keywords/Search Tags:Xi’an, surface temperature, thermal environment, landscape pattern, remote sensing
PDF Full Text Request
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