메뉴 건너뛰기




Volumn 27, Issue 2, 2017, Pages 326-337

Urban areas extraction from multi sensor data based on machine learning and data fusion

Author keywords

data fusion; machine learning; spectral indices; urban areas extraction

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA FUSION; DISASTERS; EXTRACTION; IMAGE PROCESSING; LEARNING SYSTEMS; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; SATELLITE IMAGERY; SUPPORT VECTOR MACHINES; SURVEYS; URBAN PLANNING; VEGETATION;

EID: 85020833433     PISSN: 10546618     EISSN: 15556212     Source Type: Journal    
DOI: 10.1134/S1054661816040131     Document Type: Article
Times cited : (13)

References (59)
  • 1
    • 84891742167 scopus 로고    scopus 로고
    • Building change detection from multitemporal high-resolution remotely sensed images based on a morphological building index
    • X. Huang, L. Zhang, and T. Zhu, “Building change detection from multitemporal high-resolution remotely sensed images based on a morphological building index,” IEEE J. Select. Topics Appl. Earth Observ. Remote Sensing 7 (1), 105–115 (2014).
    • (2014) IEEE J. Select. Topics Appl. Earth Observ. Remote Sensing , vol.7 , Issue.1 , pp. 105-115
    • Huang, X.1    Zhang, L.2    Zhu, T.3
  • 2
    • 84924281925 scopus 로고    scopus 로고
    • Building parameters extraction from remote-sensing data and GIS analysis for the derivation of a building taxonomy of settlements: A contribution to flood building susceptibility assessment
    • A. Blanco-Vogt, N. Haala, and J. Schanze, “Building parameters extraction from remote-sensing data and GIS analysis for the derivation of a building taxonomy of settlements: A contribution to flood building susceptibility assessment,” Int. J. Image Data Fusion 6 (1), 22–41 (2015).
    • (2015) Int. J. Image Data Fusion , vol.6 , Issue.1 , pp. 22-41
    • Blanco-Vogt, A.1    Haala, N.2    Schanze, J.3
  • 4
    • 84902144036 scopus 로고    scopus 로고
    • The pixel rectangle index used in object based building extraction from high resolution images
    • W. H. Cui, X. Feng, and K. Qin, “The pixel rectangle index used in object based building extraction from high resolution images,” in IOP Conf. Series: Earth and Environmental Science (2014), p. 012233.
    • (2014) IOP Conf. Series: Earth and Environmental Science , pp. 012233
    • Cui, W.H.1    Feng, X.2    Qin, K.3
  • 5
    • 29544440639 scopus 로고    scopus 로고
    • Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information
    • X. Jin, and C.H. Davis, “Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information,” EURASIP J. Appl. Signal Processing 14, 2196–2206 (2005).
    • (2005) EURASIP J. Appl. Signal Processing , vol.14 , pp. 2196-2206
    • Jin, X.1    Davis, C.H.2
  • 6
    • 57849112797 scopus 로고    scopus 로고
    • Building extraction from high resolution satellite imagery based on multi-scale image segmentation and model matching
    • Z. Liu, S. Cui, and Q. Yan, “Building extraction from high resolution satellite imagery based on multi-scale image segmentation and model matching,” in Proc. Conf. on Earth Observation and Remote Sensing Applications (Beijing, 2008), pp. 1–7.
    • (2008) Proc. Conf. on Earth Observation and Remote Sensing Applications , pp. 1-7
    • Liu, Z.1    Cui, S.2    Yan, Q.3
  • 7
    • 84930273499 scopus 로고    scopus 로고
    • Development of new indices for extraction of built-up area and bare soil from Landsat data
    • W. M. Muhammad, M. J. Fatimah, M. Fafia, and H. Ejaz, “Development of new indices for extraction of built-up area and bare soil from Landsat data,” Open Access Sci. Rep. 1, 1–4 (2012).
    • (2012) Open Access Sci. Rep. , vol.1 , pp. 1-4
    • Muhammad, W.M.1    Fatimah, M.J.2    Fafia, M.3    Ejaz, H.4
  • 8
    • 84879167586 scopus 로고    scopus 로고
    • Automatic building extraction using LiDAR and aerial photographs
    • M. Uzar, and N. Yastikli, “Automatic building extraction using LiDAR and aerial photographs,” Boletim de ciencias geodesicas. 19 (2), 153–171 (2013).
    • (2013) Boletim de ciencias geodesicas. , vol.19 , Issue.2 , pp. 153-171
    • Uzar, M.1    Yastikli, N.2
  • 10
    • 70350150491 scopus 로고    scopus 로고
    • Building extraction and 3D reconstruction in urban areas from high-resolution optical and SAR imagery
    • H. Sportouche, F. Tupin, and L. Denise, “Building extraction and 3D reconstruction in urban areas from high-resolution optical and SAR imagery,” in Proc. Joint Conf. on Urban Remote Sensing Event2009 (Shanghai, 2009), pp. 1–11.
    • (2009) Proc. Joint Conf. on Urban Remote Sensing Event2009 , pp. 1-11
    • Sportouche, H.1    Tupin, F.2    Denise, L.3
  • 11
    • 84937887411 scopus 로고    scopus 로고
    • A rapid extraction of water body features from Antarctic coastal oasis using very high-resolution satellite remote sensing data
    • S. D. Jawak, and A. J. Luis, “A rapid extraction of water body features from Antarctic coastal oasis using very high-resolution satellite remote sensing data,” Aquatic Proc. 4, 125–132 (2015).
    • (2015) Aquatic Proc. , vol.4 , pp. 125-132
    • Jawak, S.D.1    Luis, A.J.2
  • 12
    • 84922704792 scopus 로고    scopus 로고
    • A spectral index for highlighting forest cover from remotely sensed imagery
    • W. Ye, X. Li, X. Chen, and G. Zhang, “A spectral index for highlighting forest cover from remotely sensed imagery,” in SPIE Asia Pacific Remote Sensing (2014), pp. 92601L–92601L.
    • (2014) SPIE Asia Pacific Remote Sensing , pp. 92601L
    • Ye, W.1    Li, X.2    Chen, X.3    Zhang, G.4
  • 13
    • 84943361518 scopus 로고    scopus 로고
    • A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery
    • K. Shahi, H.Z. Shafri, E. Taherzadeh, S. Mansor, and R. Muniandy, “A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery,” Egypt. J. Remote Sensing Space Sci. 18 (1), 27–33 (2015).
    • (2015) Egypt. J. Remote Sensing Space Sci. , vol.18 , Issue.1 , pp. 27-33
    • Shahi, K.1    Shafri, H.Z.2    Taherzadeh, E.3    Mansor, S.4    Muniandy, R.5
  • 14
    • 3843090619 scopus 로고    scopus 로고
    • An effective approach to automatically extract urban land-use from TM imagery
    • Y. Zha, S. X. Ni, and S. Yang, “An effective approach to automatically extract urban land-use from TM imagery,” J. Remote Sens. 7, 37–40 (2003).
    • (2003) J. Remote Sens. , vol.7 , pp. 37-40
    • Zha, Y.1    Ni, S.X.2    Yang, S.3
  • 15
    • 0002872223 scopus 로고
    • Monitoring vegetation systems in the Great Plains with ERTS
    • J. W. Rouse, R. H. Haas, J. A. Schell, and D. W. Deering, “Monitoring vegetation systems in the Great Plains with ERTS,” in Proc. 3rd ERTS Symp. (Washington, 1973), pp. 309–317.
    • (1973) Proc. 3rd ERTS Symp. , pp. 309-317
    • Rouse, J.W.1    Haas, R.H.2    Schell, J.A.3    Deering, D.W.4
  • 16
    • 0024165401 scopus 로고
    • A soil-adjusted vegetation index (SAVI)
    • A. R. Huete, “A soil-adjusted vegetation index (SAVI),” Remote Sens. Environ. 25 (3), 295–309 (1988).
    • (1988) Remote Sens. Environ. , vol.25 , Issue.3 , pp. 295-309
    • Huete, A.R.1
  • 17
    • 33747136902 scopus 로고    scopus 로고
    • Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery
    • H. Xu, “Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery,” Int. J. Remote Sens. 27, 3025–3033 (2006).
    • (2006) Int. J. Remote Sens. , vol.27 , pp. 3025-3033
    • Xu, H.1
  • 18
    • 0027063079 scopus 로고
    • GEMI: a non-linear index to monitor global vegetation from satellites
    • B. Pinty, and M. M. Verstraete, “GEMI: a non-linear index to monitor global vegetation from satellites,” Vegetatio 101 (1), 15–20 (1992).
    • (1992) Vegetatio , vol.101 , Issue.1 , pp. 15-20
    • Pinty, B.1    Verstraete, M.M.2
  • 19
    • 46349084185 scopus 로고    scopus 로고
    • A new index for delineating built-up land features in satellite imagery
    • H. Xu, “A new index for delineating built-up land features in satellite imagery,” Int. J. Remote Sens. 29 (14), 4269–4276 (2008).
    • (2008) Int. J. Remote Sens. , vol.29 , Issue.14 , pp. 4269-4276
    • Xu, H.1
  • 21
    • 79958709785 scopus 로고    scopus 로고
    • Development of an urban classification method using a built-up index
    • J. Lee, S. S. Lee, and K. H. Chi, “Development of an urban classification method using a built-up index,” in Proc. 6th WSEAS Int. Conf. on Remote Sensing (Iwate, 2010), pp. 39–43.
    • (2010) Proc. 6th WSEAS Int. Conf. on Remote Sensing , pp. 39-43
    • Lee, J.1    Lee, S.S.2    Chi, K.H.3
  • 22
    • 84879731666 scopus 로고    scopus 로고
    • The VHR data region-based classification possibilities in the framework of control with remote sensing of European CAP
    • A. Carleer, and E. Wolff, “The VHR data region-based classification possibilities in the framework of control with remote sensing of European CAP,” in Proc. 31st Int. Symp. of Remote Sensing on Environment (St. Petersburg, 2005).
    • (2005) Proc. 31st Int. Symp. of Remote Sensing on Environment
    • Carleer, A.1    Wolff, E.2
  • 23
    • 0041959832 scopus 로고    scopus 로고
    • Spectral resolution requirements for mapping urban areas
    • M. Herold, M. E. Gardner, and D. Roberts, “Spectral resolution requirements for mapping urban areas,” IEEE Trans. Geosci. Remote Sensing 41 (9), 1907–1919 (2003).
    • (2003) IEEE Trans. Geosci. Remote Sensing , vol.41 , Issue.9 , pp. 1907-1919
    • Herold, M.1    Gardner, M.E.2    Roberts, D.3
  • 24
    • 77953562671 scopus 로고    scopus 로고
    • Accessing free Landsat data via the Internet: Africa’s challenge
    • D. P. Roy, J. Ju, C. Mbow, P. Frost, and T. Loveland, “Accessing free Landsat data via the Internet: Africa’s challenge,” Remote Sensing Lett. 1 (2), 111–117 (2010).
    • (2010) Remote Sensing Lett. , vol.1 , Issue.2 , pp. 111-117
    • Roy, D.P.1    Ju, J.2    Mbow, C.3    Frost, P.4    Loveland, T.5
  • 25
    • 39749112645 scopus 로고    scopus 로고
    • The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally
    • J. Ju, and D. P. Roy, “The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally,” Remote Sensing Environ. 112 (3), 1196–1211 (2008).
    • (2008) Remote Sensing Environ. , vol.112 , Issue.3 , pp. 1196-1211
    • Ju, J.1    Roy, D.P.2
  • 27
    • 33745615125 scopus 로고    scopus 로고
    • Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery
    • Q. Yu, P. Gong, N. Clinton, G. Biging, M. Kelly, and D. Schirokauer, “Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery,” Photogrammetric Eng. Remote Sensing 72 (7), 799–811 (2006).
    • (2006) Photogrammetric Eng. Remote Sensing , vol.72 , Issue.7 , pp. 799-811
    • Yu, Q.1    Gong, P.2    Clinton, N.3    Biging, G.4    Kelly, M.5    Schirokauer, D.6
  • 28
    • 36749021061 scopus 로고    scopus 로고
    • Extraction of urban built-up land features from Landsat imagery using a thematic oriented index combination technique
    • H. Xu, “Extraction of urban built-up land features from Landsat imagery using a thematic oriented index combination technique,” Photogrammetric Eng. Remote Sensing 73 (12), 1381–1391 (2007).
    • (2007) Photogrammetric Eng. Remote Sensing , vol.73 , Issue.12 , pp. 1381-1391
    • Xu, H.1
  • 29
    • 0036401356 scopus 로고    scopus 로고
    • Detection of buildings from Landsat-7 ETM+ and SPOT panchromatic data in Beijing, China
    • J. Wang, “Detection of buildings from Landsat-7 ETM+ and SPOT panchromatic data in Beijing, China,” in Proc. IEEE Int. Geoscience and Remote Sensing Symp. (2002), pp. 2977–2979.
    • (2002) Proc. IEEE Int. Geoscience and Remote Sensing Symp. , pp. 2977-2979
    • Wang, J.1
  • 30
    • 84877637684 scopus 로고    scopus 로고
    • A new decision tree classification approach for extracting urban land from Landsat TM in a coastal city, China
    • L. Hua, W. Man, Q. Wang, and X. Zhao, “A new decision tree classification approach for extracting urban land from Landsat TM in a coastal city, China,” in Proc. Int. Symp. on Information Science and Engineering (ISISE) (Toronto, 2012), pp. 282–286.
    • (2012) Proc. Int. Symp. on Information Science and Engineering (ISISE) , pp. 282-286
    • Hua, L.1    Man, W.2    Wang, Q.3    Zhao, X.4
  • 32
    • 84930178797 scopus 로고    scopus 로고
    • Extraction of impervious features from spectral indices using artificial neural network
    • N. Patel, and R. Mukherjee, “Extraction of impervious features from spectral indices using artificial neural network,” Arabian J. Geosci. 8 (6), 3729–3741 (2014).
    • (2014) Arabian J. Geosci. , vol.8 , Issue.6 , pp. 3729-3741
    • Patel, N.1    Mukherjee, R.2
  • 33
    • 79955412923 scopus 로고    scopus 로고
    • Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach
    • C. He, P. Shi, D. Xie, and Y. Zhao, “Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach,” Remote Sensing Lett. 1 (4), 213–221 (2010).
    • (2010) Remote Sensing Lett. , vol.1 , Issue.4 , pp. 213-221
    • He, C.1    Shi, P.2    Xie, D.3    Zhao, Y.4
  • 34
    • 84861606048 scopus 로고    scopus 로고
    • Building extraction from very high resolution multispectral images using NDVI based segmentation and morphological operators
    • D. Singh, R. Maurya, A. S. Shukla, M. K. Sharma, and P. R. Gupta, “Building extraction from very high resolution multispectral images using NDVI based segmentation and morphological operators,” in Proc. Conf. on Engineering and Systems (SCES) (Busan, 2012), pp. 1–5.
    • (2012) Proc. Conf. on Engineering and Systems (SCES) , pp. 1-5
    • Singh, D.1    Maurya, R.2    Shukla, A.S.3    Sharma, M.K.4    Gupta, P.R.5
  • 36
    • 34948884613 scopus 로고    scopus 로고
    • Automatic building extraction for 3D terrain reconstruction using interpretation techniques
    • Y. H. Lu, J. Trunder, and K. Kubik, “Automatic building extraction for 3D terrain reconstruction using interpretation techniques,” in Proc. School of Surveying and Spatial Information Systems (University of New South Wales, 2002).
    • (2002) Proc. School of Surveying and Spatial Information Systems
    • Lu, Y.H.1    Trunder, J.2    Kubik, K.3
  • 40
    • 79957818977 scopus 로고    scopus 로고
    • Building extraction from high resolution color imagery based on edge flow driven active contour and JSEG
    • Y. Song and J. Shan, “Building extraction from high resolution color imagery based on edge flow driven active contour and JSEG,” IAPRSIS 37, 185–190 (2008).
    • (2008) IAPRSIS , vol.37 , pp. 185-190
    • Song, Y.1    Shan, J.2
  • 41
    • 70349642303 scopus 로고    scopus 로고
    • Automated building extraction from high-resolution satellite imagery using spectral and structural information based on artificial neural networks
    • Z. Lari, and H. Ebadi, “Automated building extraction from high-resolution satellite imagery using spectral and structural information based on artificial neural networks,” in Proc. ISPRS Workshop (Hannover, 2007).
    • (2007) Proc. ISPRS Workshop
    • Lari, Z.1    Ebadi, H.2
  • 42
    • 84891817462 scopus 로고    scopus 로고
    • Using highresolution aerial photography and neural networks to inventory properties at risk of earthquakes
    • San Antonio, TX
    • L. Sahar, S. Muthukumar, and S. P. French, “Using highresolution aerial photography and neural networks to inventory properties at risk of earthquakes,” in Proc. MAPPS/ASPRS Fall Conf. (San Antonio, TX, 2006).
    • (2006) Proc. MAPPS/ASPRS Fall Conf.
    • Sahar, L.1    Muthukumar, S.2    French, S.P.3
  • 44
    • 84911383062 scopus 로고    scopus 로고
    • Developing remote sensing methodology to distinguish urban builtup areas and bare land in Mafikeng town, South Africa
    • L. G. Palamuleni, and N. N. Ndou, “Developing remote sensing methodology to distinguish urban builtup areas and bare land in Mafikeng town, South Africa,” in Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS) (Quebec, 2014), pp. 2205–2208.
    • (2014) Proc. IEEE Int. Geoscience and Remote Sensing Symp. , pp. 2205-2208
    • Palamuleni, L.G.1    Ndou, N.N.2
  • 45
    • 85020811142 scopus 로고    scopus 로고
    • SVM classification of urban high-resolution imagery using composite kernels and contour information
    • D. Mammass, A. Elhassouny, and D. Ducrot, “SVM classification of urban high-resolution imagery using composite kernels and contour information,” Statistics 4 (7), 126–141 (2013).
    • (2013) Statistics , vol.4 , Issue.7 , pp. 126-141
    • Mammass, D.1    Elhassouny, A.2    Ducrot, D.3
  • 46
    • 84892161220 scopus 로고    scopus 로고
    • Building detection from pansharpened Ikonos imagery through support vector machines classification
    • M. Turker, and K. San, “Building detection from pansharpened Ikonos imagery through support vector machines classification,” in Proc. 8th ISPRS Technical Com. Symp. (Kyoto, 2010), pp. 841–846.
    • (2010) Proc. 8th ISPRS Technical Com. Symp. , pp. 841-846
    • Turker, M.1    San, K.2
  • 47
    • 84920677344 scopus 로고    scopus 로고
    • Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping
    • M. Turker, and D. Koc-San, “Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping,” Int. J. Appl. Earth Observ. Geoinf. 34, 58–69 (2015).
    • (2015) Int. J. Appl. Earth Observ. Geoinf. , vol.34 , pp. 58-69
    • Turker, M.1    Koc-San, D.2
  • 48
    • 84926662675 scopus 로고
    • Nearest neighbor pattern classification
    • T. M. Cover and P. E. Hart, “Nearest neighbor pattern classification,” IEEE Trans. Inf. Theory 13 (1), 21–27 (1967).
    • (1967) IEEE Trans. Inf. Theory , vol.13 , Issue.1 , pp. 21-27
    • Cover, T.M.1    Hart, P.E.2
  • 49
    • 84921941015 scopus 로고    scopus 로고
    • Remote sensing and GIS for mapping and monitoring land cover and land use changes using support vector machine algorithm (Case study: Ilam dam watershed)
    • E. Shahkooeei, S. Arekhi, and A. N. Kani, “Remote sensing and GIS for mapping and monitoring land cover and land use changes using support vector machine algorithm (Case study: Ilam dam watershed),” Int. Res. J. Appl. Basic Sci. 8 (4), 464–473 (2014).
    • (2014) Int. Res. J. Appl. Basic Sci. , vol.8 , Issue.4 , pp. 464-473
    • Shahkooeei, E.1    Arekhi, S.2    Kani, A.N.3
  • 51
  • 52
    • 84921991935 scopus 로고    scopus 로고
    • River boundary delineationfrom remotely sensed imagery based on SVM and relaxation labeling of water index and DSM
    • P. Horkaew, S. Puttinaovarat, and K. Khaimook, “River boundary delineationfrom remotely sensed imagery based on SVM and relaxation labeling of water index and DSM,” J. Theor. Appl. Inform. Technol. 71 (3), 376–386 (2015).
    • (2015) J. Theor. Appl. Inform. Technol. , vol.71 , Issue.3 , pp. 376-386
    • Horkaew, P.1    Puttinaovarat, S.2    Khaimook, K.3
  • 54
    • 85020760137 scopus 로고    scopus 로고
    • Estimation tree density as object-based in arid and semi-arid regionsusing ALOS
    • H. Fadaei, R. Suzuki, and R. Avtar, “Estimation tree density as object-based in arid and semi-arid regionsusing ALOS,” in Proc. 4th GEOBIA (Ghent, 2010), pp. 668–671.
    • (2010) Proc. 4th GEOBIA , pp. 668-671
    • Fadaei, H.1    Suzuki, R.2    Avtar, R.3
  • 55
    • 84876535859 scopus 로고    scopus 로고
    • Coastline extraction using support vector machine from remote sensing image
    • Z. Hannv, J. Qigang, and X. Jiang, “Coastline extraction using support vector machine from remote sensing image,” J. Multimedia 8 (2), 175–182 (2013).
    • (2013) J. Multimedia , vol.8 , Issue.2 , pp. 175-182
    • Hannv, Z.1    Qigang, J.2    Jiang, X.3
  • 56
    • 0031238275 scopus 로고    scopus 로고
    • Application of majority voting to pattern recognition: an analysis of its behavior and performance
    • L. Lam, and C. Y. Suen, “Application of majority voting to pattern recognition: an analysis of its behavior and performance,” IEEE Trans. Syst., Man Cybernet., Part A: Syst. Humans 27 (5), 553–568 (1997).
    • (1997) IEEE Trans. Syst., Man Cybernet., Part A: Syst. Humans , vol.27 , Issue.5 , pp. 553-568
    • Lam, L.1    Suen, C.Y.2
  • 57
    • 0031190038 scopus 로고    scopus 로고
    • Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing
    • L. Hégarat-Mascle, I. Bloch, and D. Vidal-Madjar, “Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing,” in Proc. IEEE Trans. Geosci. Remote Sensing 35 (4), 1018–1031 (1997).
    • (1997) Proc. IEEE Trans. Geosci. Remote Sensing , vol.35 , Issue.4 , pp. 1018-1031
    • Hégarat-Mascle, L.1    Bloch, I.2    Vidal-Madjar, D.3
  • 58
    • 33645837219 scopus 로고    scopus 로고
    • Automatic building detection using the Dempster-Shafer algorithm
    • Y. H. Lu, J. C. Trinder, and K. Kubik, “Automatic building detection using the Dempster-Shafer algorithm,” Photogrammetric Eng. Remote Sensing 72 (4), 395–403 (2006).
    • (2006) Photogrammetric Eng. Remote Sensing , vol.72 , Issue.4 , pp. 395-403
    • Lu, Y.H.1    Trinder, J.C.2    Kubik, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.