Assimilation of endmember variability in spectral for urban land cover extraction mixture analysis

被引:6
|
作者
Kumar, Uttam [1 ,2 ,3 ]
Raja, S. Kumar [4 ]
Mukhopadhyay, Chiranjit [2 ]
Ramachandra, T. V. [1 ,5 ,6 ]
机构
[1] Indian Inst Sci, Ctr Ecol Sci, Energy & Wetlands Res Grp, Bangalore 560012, Karnataka, India
[2] Indian Inst Sci, Dept Management Studies, Bangalore 560012, Karnataka, India
[3] Int Inst Informat Technol IIITB, Bangalore 560100, Karnataka, India
[4] Airbus Engn Ctr India, EADS Innovat Works, Bangalore 560048, Karnataka, India
[5] Indian Inst Sci, Ctr Sustainable Technol, Bangalore 560012, Karnataka, India
[6] Indian Inst Sci, Ctr Infrastruct Sustainable Transportat & Urban P, Bangalore 560012, Karnataka, India
关键词
Linear mixture model; Mixed pixel; Variable endmember; ABUNDANCE ESTIMATION; SELECTION; CLASSIFICATION; ALGORITHMS; IMAGERY; MODEL;
D O I
10.1016/j.asr.2013.08.022
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2015 / 2033
页数:19
相关论文
共 50 条
  • [41] Measuring the physical composition of urban morphology using multiple endmember spectral mixture models
    Rashed, T
    Weeks, JR
    Roberts, D
    Rogan, J
    Powell, R
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2003, 69 (09): : 1011 - 1020
  • [42] A New Model for a Spectral Mixture Analysis Without Accurate Endmember Spectra
    Schramm, Matthias
    Landmann, Tobias
    Lohmann, Peter
    Heipke, Christian
    [J]. PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION, 2008, (05): : 351 - 362
  • [43] A new tool for variable multiple endmember spectral mixture analysis (VMESMA)
    García-Haro, FJ
    Sommer, S
    Kemper, T
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2005, 26 (10) : 2135 - 2162
  • [44] A SPARSE MULTIPLE ENDMEMBER SPECTRAL MIXTURE ANALYSIS ALGORITHM OF HYPERSPECTRAL IMAGE
    Zhao Chun-hui
    Cui Shi-ling
    Qi Bin
    [J]. 2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP), 2014, : 687 - 692
  • [45] Multiple endmember object spectral mixture analysis for high spatial resolution remote sensing imagery of urban areas
    Du, Zhenhong
    Zhang, Yiran
    Zhang, Feng
    Liu, Renyi
    Chen, Yiwen
    [J]. JOURNAL OF APPLIED REMOTE SENSING, 2017, 11
  • [46] Spectral mixture analysis of land covers
    Borisova, D.
    Kancheva, R.
    Nikolov, H.
    [J]. GLOBAL DEVELOPMENTS IN ENVIRONMENTAL EARTH OBSERVATION FROM SPACE, 2006, : 509 - +
  • [47] Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters (vol 33, pg 290, 2014)
    Fan, Fenglei
    Deng, Yingbin
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2015, 36 : 103 - 105
  • [48] A Geographic Information-Assisted Temporal Mixture Analysis for Addressing the Issue of Endmember Class and Endmember Spectra Variability
    Li, Wenliang
    Wu, Changshan
    [J]. SENSORS, 2017, 17 (03)
  • [49] Robust Extraction of Urban Land Cover Information From HSR Multi-Spectral and LiDAR Data
    Berger, Christian
    Voltersen, Michael
    Hese, Soeren
    Walde, Irene
    Schmullius, Christiane
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (05) : 2196 - 2211
  • [50] A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper
    Dennison, PE
    Halligan, KQ
    Roberts, DA
    [J]. REMOTE SENSING OF ENVIRONMENT, 2004, 93 (03) : 359 - 367