基于遥感信息的北京硬化地表格局特征研究

地表硬化是城市发展的重要特征之一,识别地表硬化程度对认识城市景观格局、物流、能流等社会、经济、自然过程具有重要意义.研究利用TM遥感影像,发展城市地表硬化度的遥感分析方法,提出地表硬化度指数,应用主成分回归方法,有效地拟合了地表硬化度和多光谱因子的关系(RTM=0.851,p<0.001).经统计检验:基于TM拟合的地表硬化度和真实的地表硬化度的相关性达到0.91(R=0.91).在此基础上,应用地表硬化度指数和基于目标分割的遥感分类方法,研究了北京市建城区(5环内)地表硬化度和建设密度的空间格局.结果表明:北京市城区中等(地表硬化度在50%-70%)和高密度建设用地(地表硬化度大于70%)总体比例大于70%,占绝对优势,其景观斑块的大小、形状等格局特征主导了北京城区景观格局的总体特征.但2-5环不同环带内硬化地表的格局特征明显不同.3-4环带是近20年城市发展的核心区,地表硬化格局综合体现了城市不同发展阶段的土地利用特征;2环带是老城区,以老北京胡同和文化古迹为主,高密度建设用地比例最高;5环带是城乡过渡区,以村镇、开发区为主体的高密度和中等密度建设覆盖比例为68.8%,斑块异质性较其他环带低,以林地、耕地等为主的硬化度较低的土地覆盖比例是31.2%,斑块异质性更低.

Study on the Spatial Pattern of Impervious Surface Using Remote Sensing Data within the Urban Area of Beijing

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 smi 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< 0. 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%.