Estimating Urban Impervious Surface Distribution With RS By Spectral Mixture Analysis

The impervious surface is one of the most basic components of the city. Its cover conditions, changing with urban development, have a great impact on the local climate, hydrology and the surface energy flux of the city, and in turn make an influence on the urban living environment quality and watershed health condition. As one of the key technical indicators for the ecological environment monitoring by remote sensing, it has been applied in urban hydrology simulating, non-point pollution of water quality, urban heat island effect and urban thematic mapping.The research object of this article supported by key project is about the urban ecological environment treatment and optimization in Beijing city area, using remote sensing techniques, experimental and observational methods. It takes the urban impervious surfaces structure characteristics as the background and start of the study, do researches on spatial distribution of the impervious surfaces, spatial expansion and its intrinsic relationship with urban heat island and urban ecological environment in Beijing city area by analyzing the relations of urban interior landscape features, seeking after the accurately calculating methods for abstracting urban impervious surfaces.The main work and result of this thesis are list as follows:1. Four kinds of SMA models,which are Wu&Murray model , Normalized V-I-S model , Four endmember SMA model and Normalized four endmember SMA model, are compared and further analyzed, and evaluates the applicability of each SMA model properly .The final result indicates that the overall accuracy of Wu&Murray model is optimum, four endmember SMA model is worst .however, normalized spectral mixture analysis has no obvious improvement to estimate impervious surface fractional image.2. By comparison, the paper chooses the Wu&Murray SMA model to estimated Beijing urban impervious surface spatial pattern using Landsat TM data. The results of this study reveal that estimative impervious surface distribution can be derived with a promising accuracy; the root mean square (RMS) error was 8.6% and correlation coefficient R~2 was 0.932 , by comparing to the corresponding true impervious surface digitized through interpreting spot-5 images and the area of imperviousness measured from the digitized map. through the map of Beijing urban impervious surface in 2004,we can find the average percent of impervious surface is 41.3%,the highest level of ISP is 70.3% while into the inner part of second ring. the ISP is 45.3% between second ring and third ring, With the fact that city construction faces outside radiation, do impervious surface specific gravity diminish gradually. the ISP is 33.53% between four ring and five ring. the ISP reduced to 25.83% between third ring and four ring. However, the number decreases to 21.3% between fifth ring to sixth ring.3. It conducts a research on impervious surfaces expansion in Beijing city area using multi-year, multi-temporal RS data, obtains the overall distribution characteristics and the evolvement trends of impervious surfaces in Beijing city area, reveals the influences of urban development and landscape classes changes on impervious surfaces. The overall percent of impervious surfaces in Beijing test site has increased from 41.04 percent in 2004 to 46.57 percent in 2007. The same term among them, percent of impervious surfaces in built up area increasing to 50.19% from 47.91%, having increased by 2.28%, built up area having also increased by 4.6%.4. With the thermal infrared imagery data from Landsat satellite, it obtains an overalls distribution characteristics of urban heat island in Beijing city, analyzes the changes of the urban heat island at different seasons using Landsat thermal infrared imagery data. It carries on green space transformation, makes a research on the growth-decline relations between impervious surfaces percentage spatial changes and heat island effect by analyzing LST, urban vegetation cover and impervious surfaces jointly. Relevance modulus R of NDVI and the land surface temperature (LST) is -0.8069, both display the negative relevance. The NDVI each rise by 0.1 , average land surface temperature reduces 1.495℃with that. However, Relevance modulus R Impervious surface percentage (ISP) and the Land surface temperature (LST) is 0.752, Both display the positively related. The average land surface temperature small advantages elevates 0.86℃while ISP rises by 0.1. Based on the heat environment response analyses of impervious surfaces in Beijing city, it also provides suggestions and measures to alleviate Beijing heat island effect, including urban greening, building greenbelt in large scales, distributing greenbelts symmetrically, utilizing suitable pattern of planting structure and increase urban water surface area reasonably, etc.