Please wait a minute...
img

Wechat

Remote Sensing Technology and Application  2015, Vol. 30 Issue (2): 321-330    DOI: 10.11873/j.issn.1004-0323.2015.2.0321
    
Impervious Surface Dynamic Quantification based on Multiple Endmember Spectral Mixture Analysis(MESMA)and Landsat Imagery Data:A Case Study in Beijing
Zhang Wenting1,2,Jin Keyi1,Song Kaishan2,Hang Yanhong1
(1.College of Resources and Environment,Northeast Agricultural University,Harbin 150030,China;
2.Northeast Institute of Geography and Agricultural Ecology,CAS,Changchun 130012,China)
Download:  PDF (11944KB) 
Export:  BibTeX | EndNote (RIS)      
Abstract  

China is experiencing rapid urbanization process,timely and accurate quantification of the urbanization process is pivotal for the currently social and economic development in China.This study used Multiple Endmember Spectral Mixture Analysis(MESMA)model to extract impervious surface information from a time series of Landsat TM and ETM+ images data under the framework of Ridd’s Vegetation\|Impervious Surface\|soil(V\|I\|S)model.For MESMA implementation,minimum noise fraction transform(MNF)was applied to transform the TM or ETM six spectral bands into the MNF space and four endmembers representing vegetation,high\|albedo surface,low\|albedo surface and soil were determined for images acquired over the Beijing City.The results show that MESMA yielded relative accurate estimate vegetation,soil and impervious surface for the Beijing city.Accuracy assessment indicates that MESMA resulted in the lowest RMSEs for impervious surface,vegetation and soil are 14.6%,17.3% and 11.9%,respectively.Further,the MESMA model generated the low Mean Absolute Error(MAE)value.This work demonstrates that applied MESMA to a time series of the moderate\|resolution multispectral remote sensing image can be an effective way to monitor the dynamics of urban environment variables dynamics and urban expansion,which has great potential for urbanization monitoring with MESMA modeling under the V\|I\|S framework.

Key words:  Beijing      Endmember      Impervious      V-I-S model      MESMA     
Received:  04 December 2013      Published:  08 May 2015
TP 79  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Zhang Wenting
Jin Keyi
Song Kaishan
Hang Yanhong

Cite this article: 

Zhang Wenting,Jin Keyi,Song Kaishan,Hang Yanhong. Impervious Surface Dynamic Quantification based on Multiple Endmember Spectral Mixture Analysis(MESMA)and Landsat Imagery Data:A Case Study in Beijing. Remote Sensing Technology and Application, 2015, 30(2): 321-330.

URL: 

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2015.2.0321     OR     http://www.rsta.ac.cn/EN/Y2015/V30/I2/321

[1]Turner II B L,Clark W C,Kates R W,et al.The Earth as Transformed by Human Action:Global and Regional Change in the Biosphere over the Past 300 Years[M].Cambridge:Cambridge University Press,1990:103-120.

[2]Voogt J.A,Oke T R.Thermal Remote Sensing of Urban Climates[J].Remote Sensing of Environment,2003,87(3):295-309.

[3]Shi Huichun,Liu Wei,He Jian,et al.An Evaluation of the Current Situation of City Ecological System Method and Its Application[J].Acta Ecologica Sinica,2012,12(17):5543-5544.[石惠春,刘伟,何剑,等.一种城市生态系统现状评价方法及其应用[J].生态学报,2012,12(17):5543-5544.]

[4]Forster B C.An Examination of Some Problems and Solutions in Monitoring Urban Areas from Satellite Platforms[J].International Journal of Remote Sensing,1985,6(1):139-151.

[5]Ridd 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(12):2165-2185.

[6]Mather P M.Land Cover Classification Revisited[C]//Advances in Remote Sensing and GIS Analysis,P.M.Atkinson and N.J Tate(Eds),New York:John Wiley & Sons.1999:7-16.

[7]Weng Q,Lu D.Landscape as a Continuum:An Examination of the Urban Landscape Structures and Dynamics of Indianapolis City,1991-2000,by Using Satellite Images[J].International Journal of Remote Sensing,2009,30(10):2547-2577.

[8]Small C.High Spatial Resolution Spectral Mixture Analysis of Urban Reflectance[J].Remote Sensing of Environment,2003,88(1-2):170-186.

[9]Ji M,Jensen J R.Effectiveness of Subpixel Analysis in Detecting and Quantifying Urban Imperviousness  from Landsat Thematic Mapper Imagery[J].Geocarto International,1999,14(4):31-41.

[10]Wu C.Normalized Spectral Mixture Analysis for Monitoring Urban Composition Using ETM+  Imagery[J].Remote Sensing of Environment,2004,3(4):480-492.

[11]Roberts D A,Gardner M,Church R,et al.Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models[J].Remote Sensing of Environment,1998,65(3):267-279.

[12]Rashed 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(9):1011-1020.

[13]State Council of China Office of Population Census.China Population Census[M].Beijing:Statistical Press of China,2010.

[14]Furby S L,Campbell N A.Calibrating Images from Different Dates to ‘Like Value’ Digital Counts[J].Remote Sensing of Environment,2001,77(2):186-196.[15]Souza C M,Roberts D,AmCochrane M A.Combining Spectral and Spatial Information to Map Canopy Damage from Selective Logging and Forest Fires[J].Remote Sensing of Environment,2005,98(2-3):329-343.

[16]Markham B L,Barker J L.Thematic Mapper Bandpass Solar Exoatmospheric Irradiances[J].International Journal of Remote Sensing,1987,8(3):517-523.

[17]Irish R.Chapter 11:Data Product[S].Landsat-7 Science Data User’s Handbook,1998:31-39.

[18]Foody G M.Status of Land Cover Classification Accuracy Assessment[J].Remote Sensing of Environment,2002,80(1):185-201.

[19]Luo Cailian,Chen Jie,Le Tongchao.The Correction of Atmospheric Landsat ETM+ Satellite Images based on FLAASH Model[J].Protction Forest Science and Technology,2008,5(86):46-47.[罗彩莲,陈杰,乐通潮.基于FLAASH模型的Landsat ETM+卫星影像大气校正[J].防护林科技,2008,5(86):46-47.]

[20]Zhang Xuexia,Ge Quansheng,Zheng Jingyun.The Application of the Study on Vegetation Phenology based on Remote Sensing Technology[J].Advances in Earth Science,2003,18(14):535-537.[张学霞,葛全胜,郑景云.遥感技术在植被物候研究中的应用综述[J].地球科学进展,2003,18(4):535-537.]

[21]Xu Qianxiang,Sheng Hui,Liao Mingsheng.Study on City Expansion Combined MNF with MAD[J].Remote Sensing for Land & Resources,2006,4(70):43-44.[徐前祥,盛辉,廖明生.MNF与MAD变换相结合的城市扩展研究[J].国土资源遥感,2006,4(70):43-44.]

[22]Yang Yetao,Gong Jianya,Zhou Qiming,et al.The Research of Effect of Land Use and Landscape Pattern on the Expansion of the City[J].Jouranl of Natural Resources,2010,25(2):320-321.[杨叶涛,龚健雅,周启鸣,等.土地利用景观格局对城市扩张影响研究[J].自然资源学报,2010,25(2):320-321.]

[23]Li Haitao,Gu Haiyan,Zhang Bing,et al.Research on Hyperspectral Remote Sensing Image Classification based on MNF and SVM[J].Remote Sensing Information,2007,(5):12-15.[李海涛,顾海燕,张兵,等.基于MNF 和SVM 的高光谱遥感影像分类研究[J].遥感信息,2007,(5):12-15.]


 

No Suggested Reading articles found!