基于遥感信息的北京硬化地表格局特征研究
Study on the Spatial Pattern of Impervious Surface Using Remote Sensing Data within the Urban Area of Beijing
- 2008年第4期 页码:603-612
纸质出版日期: 2008
DOI: 10.11834/jrs.20080479
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纸质出版日期: 2008 ,
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[1]李伟峰,欧阳志云,陈求稳,毛劲乔.基于遥感信息的北京硬化地表格局特征研究[J].遥感学报,2008(04):603-612.
LI Wei-feng, OUYANG Zhi-yun, CHEN Qiu-wen, et al. Study on the Spatial Pattern of Impervious Surface Using Remote Sensing Data within the Urban Area of Beijing[J]. Journal of Remote Sensing, 2008,(4):603-612.
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。
The amount of various impervious land surfaces increases in the process of urban development.Accompanying with the fast urbanization
it has been well known that the drastically increasing impervious land surface has serious impacts not only on urban environment but also on regional and global environment
such as changing rainfall runoff process
causing urban heat islands
changing local microclimate and so on.However
due to the complex components of impervious surface
it is difficult to derive the accurate estimates of impervious cover.Thus
the objective of this study was to directly estimate impervious cover based on multi-spectral features from remote sensing image in city center of Beijing.According to the spectral response of different land cover
a new methodology was explored to directly estimate urban land imperviousness.The object oriented method was applied to classify land cover/use into basic land units within similar spectral features and texture.Then
the multiple principal regression model was explored to estimate the relation of surface imperviousness and TM image based spectral response.The results showed that the combination of multi-spectral features could efficiently predict land imperviousness.Totally
twenty-two spectral indicators were identified to indicate the characteristics of surface imperviousness.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 imperviousness.The significant relations of land imperviousness and TM based spectral features could reach 0.851(P
<
0.001).The model validation showed that the estimated imperviousness based on TM image was accurate(R=0.91).It proved that the developed method could efficiently estimate land surface imperviousness.In addition
based on the developed impervious model
the distributed pattern of surface imperviousness within Beijing center was extracted.The results showed that the urbanization degree is very high.More than 70% lands of the city center were estimated as high or middle imperviousness
the index of which was between 50%
7
0% or larger than 70%.The average size of these impervious patches was 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 imperviousness patterns were quite different.For example
the 3rd and 4th rings were 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 impervious patches
mainly old buildings
such as old flat residential built-ups and historic sites
filled up the 2nd ring where the development history is thousands of years and new development was strictly limited.The 5th ring was the urban-rural transitional zone
which is the new developmentregion for the city sprawl in recent years.Large industry district
technology district and residential district with high or middle impervious patches occupied around 68.8%.
遥感硬化地表景观格局目标分割
remote sensingimpervious surfacelandscape patternobject segmentation
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