The amountofvarious mi pervious land surfaces increases in the processofurban development. Accompanying with the fast urbanization, it has been well known that the drastically increasing mi pervious land surface has serious mi pacts not only on urban environment but also on regional and global environment, such as changing rainfall runoff process, causing urban heat islands, changing localmicroclmi ate and so on. However, due to the complex components of mi pervious surface, it is difficult to derive the accurate estmi ates of mi pervious cover. Thus, the objective of this study was to directly estmi ate mi pervious cover based on multi-spectral features from remote sensing mi age in city center of Beijing. According to the spectral response of different land cover, a newmethodologywas explored to directly estmi ate urban land mi perviousness. The objectorientedmethodwas applied to classify land cover/use into basic land unitswithin\nsmi ilar spectral features and texture. Then, themultiple principal regressionmodelwas explored to estmi ate the relation of surface mi perviousness and TM mi age based spectral response. The results showed that the combination ofmulti-spectral features could efficiently predict land mi perviousness. Totally, twenty-two spectral indicatorswere identified to indicate the characteristics of surface mi perviousness. Among the spectral indicators, it showed that the four indicators among others, Band 1, Band 5, Band 6 and the Standard Deviation of Band 6, have the closest relation with surface mi perviousness. The significant relations of land mi perviousness andTM based spectral features could reach 0.851 (P<\n0. 001). Themodelvalidation showed that the estmi ated mi perviousnessbased onTM mi agewas accurate (R=0.91).It proved that the developed method could efficiently estmi ate land surface mi perviousness. In addition, based on the developed mi perviousmode,l the distributed pattern of surface mi perviousnesswithin Beijing centerwas extracted. The results showed that the urbanization degree is very high. More than 70% lands of the city centerwere estmi ated ashigh or middle mi perviousness, the index ofwhich was between 50%~70% or larger than 70%.The average size of these mi pervious patcheswas large and the distribution pattern was heterogeneous and fragmented. Moreover, from the core center (within the 2nd ring road) to the urban-rural edge (the 5th ring road) the surface mi perviousness patternswere quite different. For example, the 3rd and 4th ringswere fast developed in recent decades, containing diverse land use/cover types such as large commercial center, shopping center and residential district. In contrast, more high mi pervious patches, mainly old buildings, such as old flat residential built-ups and historic sites, filled up the 2nd ringwhere the developmenthistory is thousands of years and new developmentwas strictly lmi ited. The 5th ring was the urban-rural transitional zone, which is the new development region for the city sprawl in recent years. Large industry district,technology district and residential districtwith high ormiddle mi pervious patches occupied around 68.8%.