期刊文献+

基于不透水地表比例的城市扩展研究 被引量:5

Urban Sprawl Study Based on Impervious Surface Percent
下载PDF
导出
摘要 不透水地表比例是衡量城市化水平的一个重要指标,采用不透水地表比例可以研究城市的空间变化和扩展并定量化城市空间变化和扩展的强度。使用多端元光谱混合分析方法可以从TM影像中提取亚像元尺度的不透水地表比例,用该方法从两个时相的TM影像中提取南京都市发展区不透水地表比例,在此基础上定性和定量地分析该区域的空间变化和扩展。 Impervious surface percent is an important index to indicate urbanization levels it can be used to study the change and spatial extension of urban area quantitatively. Multiple endmember spectral mixture analysis method was used to extract sub-pixel level of impervious surface percent from TM image. This paper applies that method to extract the impervious surface percent of Nanjing Metropolitan development area from two temporal TM images. Then based on impervious surface percent,the change and spatial sprawl of study area was analyzed qualitatively and quantitatively.
出处 《遥感技术与应用》 CSCD 2008年第4期424-427,I0006,共5页 Remote Sensing Technology and Application
关键词 多端元光谱混合分析 不透水地表 城市扩展 Multiple endmember spectral mixture analysis Impervious surfaces Urban sprawl
  • 相关文献

参考文献16

  • 1Xian G,Crane M. Assessments of Urban Growth in the Tampa Bay Watershed Using Remote Sensing Data[J]. Remote Sensing of Environment, 2005,97 : 203-215.
  • 2Yang L, Hung C, Homer C G,et al. An Approach for Mapping Large-area Impervious Surface:Synergistic Use of Landsat 7 ETM+ and High Spatial Resolution Imagery[J]. Canadian Journal of Remote Sensing, 2003,29 (2) : 230-240.
  • 3Yang X. Estimating Landscape Imperviousness Index from Satellite Imagery[J]. Geoscience and Remote Sensing Letters,IEEE,2006,3(1) :6-9.
  • 4Sangbum L, Lathrop R G. Subpixel Analysis of Landsat ETM/sup+/Using Self-organizing Map (SOM) Neural Networks for Urban Land Cover Characterization [J]. IEEE Transactions on Geoseienee and Remote Sensing, 2006, 44 (6) :1642-1654.
  • 5Rashed T,Weeks J R,Roberts D,et al. Measuring the Physical Composition of Urban Morphology Using Multiple Endmember Spectral Mixture Models[J]. Photogrammetric Engineering and Remote Sensing, 2003,69,1011-1020.
  • 6Wu C S, Murray A T. Estimating Impervious Surface Distribution by Spectral Mixture Analysis[J]. Remote Sensing of Environment, 2003,84:493-505.
  • 7Wu C S. Normalized Spectral Mixture Analysis for Monitoring Urban Composition Using ETM+ Imagery[J]. Remote Sensing of Environment, 2004,93 : 480-492.
  • 8Lu D S,Weng Q H. Spectral Mixture Analysis of the Urban Landscape in Indianapolis with Landsat ETM+ Imagery[J]. Photogrammetric Engineering and Remote Sensing, 2004, 70 (9) : 1053-1062.
  • 9Lu D S, Weng Q H. Use of Impervious Surface in Urban Land-use Classification[J]. Remote Sensing of Environment, 2006,102 :146-160.
  • 10Lu D S,Weng Q H. Spectral Mixture Analysis of ASTER Images for Examining the Relationship between Urban Thermal Features and Biophysical Descriptors in Indianapolis, Indiana, USA[J]. Remote Sensing of Environment, 2006,104,157-167.

二级参考文献43

  • 1Ridd,M.K.Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing:comparative anatomy for cities[J].International Journal of Remote Sensing,1995(16):2165~2185.
  • 2Small,C.Estimation of urban vegetation abundance by spectral mixture analysis[J].International Journal of Remote Sensing,2001(22):1305~1334.
  • 3Small,C.Multitemporal analysis of urban reflectance[J].Remote Sensing of Environment,2002 (81):427~442.
  • 4Wu,C.,& Murray,A.T.Estimating impervious surface distribution by spectral mixture analysis[J].Remote Sensing of Environment,2003(84):493~505.
  • 5Weng,Q.,Lu,D.,& Schubring,J.Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies[J].Remote Sensing of Environment,2004(89):467~483.
  • 6Lu,D.,& Weng,Q.Spectral mixture analysis of the urban landscape in Indianapolis city with Landsat ETM + imagery[J].Photogrammetric Engineering & Remote Sensing,2004,70(9):1053~1062.
  • 7Herold,M.,Roberts,D.A.,Gardner,M.E.,& Dennison,P.E.Spectrometry for urban area remote sensing-development and analysis of a spectral library from 350 to 2400 nm[J].Remote Sensing of Environment,2004,91(3~4):304~319.
  • 8Asner,G.P.Biophysical and biochemical sources of variability in canopy reflectance[J].Remote Sensing of Environment,1998(64):234~253.
  • 9Ben-Dor,E.,Levin,N.,& Saaroni,H.A spectral-based recognitionof the urban environment using the visible and near-infrared spectral region (0.4-1.1um).A case study over Tel-Aviv[J].International Journal of Remote Sensing,2001,22(11):2193~2218.
  • 10Tompkins,S.,Mustard,J.F.,Pieters,C.M.,& Forsytth,D.W.Optimization of endmembers for spectral mixture analysis[J].Remote Sensing of Environment,1997 (59):472~489.

共引文献17

同被引文献46

引证文献5

二级引证文献39

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部