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Volumn 108, Issue , 2015, Pages 191-204

Decision fusion and non-parametric classifiers for land use mapping using multi-temporal RapidEye data

Author keywords

Agricultural land use; Decision fusion; High resolution; Multi temporal; RapidEye; Supervised classification

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURE; ALGORITHMS; CROPS; DATA MINING; DECISION TREES; LAND USE; MAPPING; SUPPORT VECTOR MACHINES;

EID: 84942546109     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2015.07.001     Document Type: Article
Times cited : (72)

References (91)
  • 1
    • 84887290816 scopus 로고    scopus 로고
    • Parcel-level identification of crop types using different classification algorithms and multi-resolution imagery in southeastern Turkey
    • Alganci U., Sertel E., Ozdogan M., Ormeci C. Parcel-level identification of crop types using different classification algorithms and multi-resolution imagery in southeastern Turkey. Photogramm. Eng. Remote Sens. 2013, 79:1053-1065. 10.14358/PERS.79.11.1053.
    • (2013) Photogramm. Eng. Remote Sens. , vol.79 , pp. 1053-1065
    • Alganci, U.1    Sertel, E.2    Ozdogan, M.3    Ormeci, C.4
  • 2
    • 84874788283 scopus 로고    scopus 로고
    • Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs
    • Atzberger C. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sens. 2013, 5:949-981. 10.3390/rs5020949.
    • (2013) Remote Sens. , vol.5 , pp. 949-981
    • Atzberger, C.1
  • 3
    • 73749086442 scopus 로고    scopus 로고
    • Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification
    • Balaguer A., Ruiz L.A., Hermosilla T., Recio J.A. Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Comput. Geosci. 2010, 36:231-240. 10.1016/j.cageo.2009.05.003.
    • (2010) Comput. Geosci. , vol.36 , pp. 231-240
    • Balaguer, A.1    Ruiz, L.A.2    Hermosilla, T.3    Recio, J.A.4
  • 4
    • 37249003229 scopus 로고    scopus 로고
    • Multiple classifier systems in remote sensing: from basics to recent developments
    • Springer, Berlin, Heidelberg, M. Haindl, J. Kittler, F. Roli (Eds.)
    • Benediktsson J.A., Chanussot J., Fauvel M. Multiple classifier systems in remote sensing: from basics to recent developments. Multiple Classifier Systems 2007, 501-512. Springer, Berlin, Heidelberg. M. Haindl, J. Kittler, F. Roli (Eds.).
    • (2007) Multiple Classifier Systems , pp. 501-512
    • Benediktsson, J.A.1    Chanussot, J.2    Fauvel, M.3
  • 5
    • 0032635034 scopus 로고    scopus 로고
    • Classification of multisource and hyperspectral data based on decision fusion
    • Benediktsson J.A., Kanellopoulos I. Classification of multisource and hyperspectral data based on decision fusion. IEEE Trans. Geosci. Remote Sens. 1999, 37:1367-1377. 10.1109/36.763301.
    • (1999) IEEE Trans. Geosci. Remote Sens. , vol.37 , pp. 1367-1377
    • Benediktsson, J.A.1    Kanellopoulos, I.2
  • 6
    • 0037560727 scopus 로고    scopus 로고
    • Multisource remote sensing data classification based on consensus and pruning
    • Benediktsson J.A., Sveinsson J.R. Multisource remote sensing data classification based on consensus and pruning. IEEE Trans. Geosci. Remote Sens. 2003, 41. 10.1109/TGRS.2003.812000.
    • (2003) IEEE Trans. Geosci. Remote Sens. , vol.41
    • Benediktsson, J.A.1    Sveinsson, J.R.2
  • 7
    • 0025453627 scopus 로고
    • Neural network approaches versus statistical methods in classification of multisource remote sensing data
    • Benediktsson J.A., Swain P.H., Erase O.K. Neural network approaches versus statistical methods in classification of multisource remote sensing data. IEEE Trans. Geosci. Remote Sens. 1990, 28:540-551.
    • (1990) IEEE Trans. Geosci. Remote Sens. , vol.28 , pp. 540-551
    • Benediktsson, J.A.1    Swain, P.H.2    Erase, O.K.3
  • 8
    • 0029756565 scopus 로고    scopus 로고
    • Information combination operators for data fusion: a comparative review with classification
    • Bloch I. Information combination operators for data fusion: a comparative review with classification. IEEE Trans. Syst. Man, Cybern. A Syst. Humans 1996, 26:52-67.
    • (1996) IEEE Trans. Syst. Man, Cybern. A Syst. Humans , vol.26 , pp. 52-67
    • Bloch, I.1
  • 9
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Mach. Learn. 1996, 24:123-140.
    • (1996) Mach. Learn. , vol.24 , pp. 123-140
    • Breiman, L.1
  • 10
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman L. Random forests. Mach. Learn. 2001, 45:5-32.
    • (2001) Mach. Learn. , vol.45 , pp. 5-32
    • Breiman, L.1
  • 11
    • 26444567985 scopus 로고    scopus 로고
    • Random Forests - Classification Description: Random Forests
    • [WWW Document]. Stat
    • Breiman, L., Cutler, A., 2007. Random Forests - Classification Description: Random Forests [WWW Document]. Stat- (accessed 01.11.13). http://www.berkeley.edu/users/breiman/RandomForests/cc_home.htm.
    • (2007)
    • Breiman, L.1    Cutler, A.2
  • 14
    • 57049119072 scopus 로고    scopus 로고
    • Estimating per-pixel thematic uncertainty in remote sensing classifications
    • Brown K.M., Foody G.M., Atkinson P.M. Estimating per-pixel thematic uncertainty in remote sensing classifications. Int. J. Remote Sens. 2009, 30:209-229. 10.1080/01431160802290568.
    • (2009) Int. J. Remote Sens. , vol.30 , pp. 209-229
    • Brown, K.M.1    Foody, G.M.2    Atkinson, P.M.3
  • 15
    • 0032638011 scopus 로고    scopus 로고
    • A neural-statistical approach to multitemporal and multisource remote-sensing image classification
    • Bruzzone L., Prieto D.F., Serpico S.B. A neural-statistical approach to multitemporal and multisource remote-sensing image classification. IEEE Trans. Geosci. Remote Sens. 1999, 37:1350-1359.
    • (1999) IEEE Trans. Geosci. Remote Sens. , vol.37 , pp. 1350-1359
    • Bruzzone, L.1    Prieto, D.F.2    Serpico, S.B.3
  • 16
    • 0242515926 scopus 로고    scopus 로고
    • Attribute bagging: improving accuracy of classiÿer ensembles by using random feature subsets
    • Bryll R., Gutierrez-osuna R., Quek F. Attribute bagging: improving accuracy of classiÿer ensembles by using random feature subsets. Pattern Recognit. 2003, 36:1291-1302.
    • (2003) Pattern Recognit. , vol.36 , pp. 1291-1302
    • Bryll, R.1    Gutierrez-osuna, R.2    Quek, F.3
  • 17
    • 78649847038 scopus 로고    scopus 로고
    • On the influence of feature reduction for the classification of hyperspectral images based on the extended morphological profile
    • Castaings T., Waske B., Benediktsson J.A., Chanussot J. On the influence of feature reduction for the classification of hyperspectral images based on the extended morphological profile. Int. J. Remote Sens. 2010, 31:5921-5939. 10.1080/01431161.2010.512313.
    • (2010) Int. J. Remote Sens. , vol.31 , pp. 5921-5939
    • Castaings, T.1    Waske, B.2    Benediktsson, J.A.3    Chanussot, J.4
  • 19
    • 84930621165 scopus 로고    scopus 로고
    • Geographic stacking: decision fusion to increase global land cover map accuracy
    • Clinton N., Yu L., Gong P. Geographic stacking: decision fusion to increase global land cover map accuracy. ISPRS J. Photogramm. Remote Sens. 2015, 103:57-65. 10.1016/j.isprsjprs.2015.02.010.
    • (2015) ISPRS J. Photogramm. Remote Sens. , vol.103 , pp. 57-65
    • Clinton, N.1    Yu, L.2    Gong, P.3
  • 20
    • 84955496418 scopus 로고    scopus 로고
    • CNES [WWW Document].
    • CNES, 2015. CNES [WWW Document]. http://smsc.cnes.fr/VENUS/.
    • (2015)
  • 21
    • 81355138685 scopus 로고    scopus 로고
    • Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions
    • Colditz R., Schmidt M., Conrad C., Hansen M.C., Dech S. Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions. Remote Sens. Environ. 2011, 115:3264-3275. 10.1016/j.rse.2011.07.010.
    • (2011) Remote Sens. Environ. , vol.115 , pp. 3264-3275
    • Colditz, R.1    Schmidt, M.2    Conrad, C.3    Hansen, M.C.4    Dech, S.5
  • 22
    • 0026278621 scopus 로고
    • A review of assessing the accuracy of classifications of remotely sensed data
    • Congalton R.G. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ. 1991, 37:35-46.
    • (1991) Remote Sens. Environ. , vol.37 , pp. 35-46
    • Congalton, R.G.1
  • 23
    • 81755185783 scopus 로고    scopus 로고
    • Temporal segmentation of MODIS time series for improving crop classification in Central Asian irrigation systems
    • Conrad C., Colditz R., Dech S., Klein D., Vlek P.L.G. Temporal segmentation of MODIS time series for improving crop classification in Central Asian irrigation systems. Int. J. Remote Sens. 2011, 32:8763-8778. 10.1080/01431161.2010.550647.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 8763-8778
    • Conrad, C.1    Colditz, R.2    Dech, S.3    Klein, D.4    Vlek, P.L.G.5
  • 24
    • 84896005616 scopus 로고    scopus 로고
    • Derivation of temporal windows for accurate crop discrimination in heterogeneous croplands of Uzbekistan using multitemporal RapidEye images
    • Conrad C., Dech S., Dubovyk O., Fritsch S., Klein D., Löw F., Schorcht G., Zeidler J. Derivation of temporal windows for accurate crop discrimination in heterogeneous croplands of Uzbekistan using multitemporal RapidEye images. Comput. Electron. Agric. 2014, 103:63-74.
    • (2014) Comput. Electron. Agric. , vol.103 , pp. 63-74
    • Conrad, C.1    Dech, S.2    Dubovyk, O.3    Fritsch, S.4    Klein, D.5    Löw, F.6    Schorcht, G.7    Zeidler, J.8
  • 25
    • 84887607665 scopus 로고    scopus 로고
    • Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan
    • Conrad C., Rahmann M., Machwitz M., Stulina G., Paeth H., Dech S. Satellite based calculation of spatially distributed crop water requirements for cotton and wheat cultivation in Fergana Valley, Uzbekistan. Glob. Planet. Change 2013, 110:88-98. 10.1016/j.gloplacha.2013.08.002.
    • (2013) Glob. Planet. Change , vol.110 , pp. 88-98
    • Conrad, C.1    Rahmann, M.2    Machwitz, M.3    Stulina, G.4    Paeth, H.5    Dech, S.6
  • 26
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes C., Vapnik V. Support-vector networks. Mach. Learn. 1995, 20:273-297.
    • (1995) Mach. Learn. , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 27
    • 6344256799 scopus 로고    scopus 로고
    • Efficiency and accuracy of per-field classification for operational crop mapping
    • De Wit A., Clevers J.G.P.W. Efficiency and accuracy of per-field classification for operational crop mapping. Int. J. Remote Sens. 2004, 25:4091-4112. 10.1080/01431160310001619580.
    • (2004) Int. J. Remote Sens. , vol.25 , pp. 4091-4112
    • De Wit, A.1    Clevers, J.G.P.W.2
  • 28
    • 79953222584 scopus 로고    scopus 로고
    • Comparison of pixel-and object-based classification in land cover change mapping
    • Dingle Robertson L., King D.J. Comparison of pixel-and object-based classification in land cover change mapping. Int. J. Remote Sens. 2011, 32:1505-1529.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 1505-1529
    • Dingle Robertson, L.1    King, D.J.2
  • 29
    • 34748885521 scopus 로고    scopus 로고
    • Increasing soft classification accuracy through the use of an ensemble of classifiers
    • Doan H.T.X., Foody G.M. Increasing soft classification accuracy through the use of an ensemble of classifiers. Int. J. Remote Sens. 2007, 28:4609-4623.
    • (2007) Int. J. Remote Sens. , vol.28 , pp. 4609-4623
    • Doan, H.T.X.1    Foody, G.M.2
  • 31
    • 84867335433 scopus 로고    scopus 로고
    • Information fusion techniques for change detection from multi-temporal remote sensing images
    • Du P., Liu S., Xia J., Zhao Y. Information fusion techniques for change detection from multi-temporal remote sensing images. Inf. Fusion 2013, 14:19-27. 10.1016/j.inffus.2012.05.003.
    • (2013) Inf. Fusion , vol.14 , pp. 19-27
    • Du, P.1    Liu, S.2    Xia, J.3    Zhao, Y.4
  • 32
    • 84860267020 scopus 로고    scopus 로고
    • Multiple classifier system for remote sensing image classification: a review
    • Du P., Xia J., Zhang W., Tan K., Liu Y., Liu S. Multiple classifier system for remote sensing image classification: a review. Sensors 2012, 12:4764-4792. 10.3390/s120404764.
    • (2012) Sensors , vol.12 , pp. 4764-4792
    • Du, P.1    Xia, J.2    Zhang, W.3    Tan, K.4    Liu, Y.5    Liu, S.6
  • 33
    • 84455200427 scopus 로고    scopus 로고
    • A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery
    • Duro D.C., Franklin S.E., Dubé M.G. A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery. Remote Sens. Environ. 2012, 118:259-272. 10.1016/j.rse.2011.11.020.
    • (2012) Remote Sens. Environ. , vol.118 , pp. 259-272
    • Duro, D.C.1    Franklin, S.E.2    Dubé, M.G.3
  • 34
    • 0344961367 scopus 로고    scopus 로고
    • Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification
    • El-Magd A.I., Tanton T.W. Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification. Int. J. Remote Sens. 2003, 24:4197-4206.
    • (2003) Int. J. Remote Sens. , vol.24 , pp. 4197-4206
    • El-Magd, A.I.1    Tanton, T.W.2
  • 36
    • 3042661357 scopus 로고    scopus 로고
    • Thematic map comparison: evaluating the statistical significance of differences in classification accuracy
    • Foody G.M. Thematic map comparison: evaluating the statistical significance of differences in classification accuracy. Photogramm. Eng. Remote Sens. 2004, 70:627-633.
    • (2004) Photogramm. Eng. Remote Sens. , vol.70 , pp. 627-633
    • Foody, G.M.1
  • 37
    • 67349093551 scopus 로고    scopus 로고
    • Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority
    • Foody G.M. Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority. Remote Sens. Environ. 2009, 113:1658-1663. 10.1016/j.rse.2009.03.014.
    • (2009) Remote Sens. Environ. , vol.113 , pp. 1658-1663
    • Foody, G.M.1
  • 39
    • 4544272407 scopus 로고    scopus 로고
    • Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification
    • Foody G.M., Mathur A. Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification. Remote Sens. Environ. 2004, 93:107-117. 10.1016/j.rse.2004.06.017.
    • (2004) Remote Sens. Environ. , vol.93 , pp. 107-117
    • Foody, G.M.1    Mathur, A.2
  • 42
    • 77957008534 scopus 로고    scopus 로고
    • Uncertainty analysis for the classification of multispectral satellite images using SVMs and SOMs
    • Giacco F., Thiel C., Pugliese L., Scarpetta S., Marinaro M. Uncertainty analysis for the classification of multispectral satellite images using SVMs and SOMs. IEEE Trans. Geosci. Remote Sens. 2010, 48:3769-3779.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , pp. 3769-3779
    • Giacco, F.1    Thiel, C.2    Pugliese, L.3    Scarpetta, S.4    Marinaro, M.5
  • 45
    • 0032139235 scopus 로고    scopus 로고
    • The random subspace method for constructing decision forests
    • Ho T.K. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Mach. Intell. 1998, 20:823-844.
    • (1998) IEEE Trans. Pattern Anal. Mach. Intell. , vol.20 , pp. 823-844
    • Ho, T.K.1
  • 46
    • 0035696907 scopus 로고    scopus 로고
    • Effect of spatial resolution on classification errors of pure and mixed pixels in remote sensing
    • Hsieh P., Lee L.C., Chen N. Effect of spatial resolution on classification errors of pure and mixed pixels in remote sensing. IEEE Trans. Geosci. Remote Sens. 2001, 39:2657-2663.
    • (2001) IEEE Trans. Geosci. Remote Sens. , vol.39 , pp. 2657-2663
    • Hsieh, P.1    Lee, L.C.2    Chen, N.3
  • 47
    • 67849114029 scopus 로고    scopus 로고
    • Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks
    • Hu X., Weng Q. Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks. Remote Sens. Environ. 2009, 113:2089-2102. 10.1016/j.rse.2009.05.014.
    • (2009) Remote Sens. Environ. , vol.113 , pp. 2089-2102
    • Hu, X.1    Weng, Q.2
  • 48
    • 0032657773 scopus 로고    scopus 로고
    • Decision fusion approach for multitemporal classification
    • Jeon B., Landgrebe D.A. Decision fusion approach for multitemporal classification. IEEE Trans. Geosci. Remote Sens. 1999, 37:1227-1233.
    • (1999) IEEE Trans. Geosci. Remote Sens. , vol.37 , pp. 1227-1233
    • Jeon, B.1    Landgrebe, D.A.2
  • 51
    • 0003946071 scopus 로고    scopus 로고
    • An Investigation of the Design and use of Feed-Forward Artificial Neural Networks in the Classification of Remotely Sensed Images
    • (PhD Thesis). The University of Nottingham.
    • Kavzoglu, T., 2001. An Investigation of the Design and use of Feed-Forward Artificial Neural Networks in the Classification of Remotely Sensed Images (PhD Thesis). The University of Nottingham.
    • (2001)
    • Kavzoglu, T.1
  • 52
    • 0346245214 scopus 로고    scopus 로고
    • The use of backpropagating artificial neural networks in land cover classification
    • Kavzoglu T., Mather P.M. The use of backpropagating artificial neural networks in land cover classification. Int. J. Remote Sens. 2003, 24:4907-4938.
    • (2003) Int. J. Remote Sens. , vol.24 , pp. 4907-4938
    • Kavzoglu, T.1    Mather, P.M.2
  • 53
    • 68649112896 scopus 로고    scopus 로고
    • Forest type mapping using object-specific texture measures from multispectral ikonos imagery: segmentation quality and image classification issues
    • Kim M., Madden M., Warner T.A. Forest type mapping using object-specific texture measures from multispectral ikonos imagery: segmentation quality and image classification issues. Photogramm. Eng. Remote Sens. 2009, 75:819-829.
    • (2009) Photogramm. Eng. Remote Sens. , vol.75 , pp. 819-829
    • Kim, M.1    Madden, M.2    Warner, T.A.3
  • 56
    • 4143125530 scopus 로고    scopus 로고
    • Uncertainty and confidence in land cover classification using a hybrid classifier approach
    • Liu W., Gopal S., Woodcock C.E. Uncertainty and confidence in land cover classification using a hybrid classifier approach. Photogramm. Eng. Remote Sens. 2004, 70:963-972.
    • (2004) Photogramm. Eng. Remote Sens. , vol.70 , pp. 963-972
    • Liu, W.1    Gopal, S.2    Woodcock, C.E.3
  • 57
    • 0037307653 scopus 로고    scopus 로고
    • Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties
    • Lobell D.B., Asner G.P., Ortiz-Monasterio J.I., Benning T.L. Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties. Agric. Ecosyst. Environ. 2003, 94:205-220. 10.1016/S0167-8809(02)00021-X.
    • (2003) Agric. Ecosyst. Environ. , vol.94 , pp. 205-220
    • Lobell, D.B.1    Asner, G.P.2    Ortiz-Monasterio, J.I.3    Benning, T.L.4
  • 58
    • 84867069504 scopus 로고    scopus 로고
    • Impact of reducing polarimetric SAR input on the uncertainty of crop classifications based on the random forests algorithm
    • Loosvelt L., Peters J., Skriver H. Impact of reducing polarimetric SAR input on the uncertainty of crop classifications based on the random forests algorithm. IEEE Trans. Geosci. Remote Sens. 2012, 50:4185-4200.
    • (2012) IEEE Trans. Geosci. Remote Sens. , vol.50 , pp. 4185-4200
    • Loosvelt, L.1    Peters, J.2    Skriver, H.3
  • 59
    • 84907466218 scopus 로고    scopus 로고
    • Defining the spatial resolution requirements for crop identification using optical remote sensing
    • Löw F., Duveiller G. Defining the spatial resolution requirements for crop identification using optical remote sensing. Remote Sens. 2014, 6:9034-9063. 10.3390/rs6099034.
    • (2014) Remote Sens. , vol.6 , pp. 9034-9063
    • Löw, F.1    Duveiller, G.2
  • 60
    • 84927598104 scopus 로고    scopus 로고
    • Analysis of uncertainty in multi-temporal object-based classification
    • Löw F., Knöfel P., Conrad C. Analysis of uncertainty in multi-temporal object-based classification. ISPRS J. Photogramm. Remote Sens. 2015, 105:91-106. 10.1016/j.isprsjprs.2015.03.004.
    • (2015) ISPRS J. Photogramm. Remote Sens. , vol.105 , pp. 91-106
    • Löw, F.1    Knöfel, P.2    Conrad, C.3
  • 61
    • 84884514639 scopus 로고    scopus 로고
    • Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using support vector machines
    • Löw F., Michel U., Dech S., Conrad C. Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using support vector machines. ISPRS J. Photogramm. Remote Sens. 2013, 85:102-119. 10.1016/j.isprsjprs.2013.08.007.
    • (2013) ISPRS J. Photogramm. Remote Sens. , vol.85 , pp. 102-119
    • Löw, F.1    Michel, U.2    Dech, S.3    Conrad, C.4
  • 63
    • 40349110669 scopus 로고    scopus 로고
    • Crop classification by support vector machine with intelligently selected training data for an operational application
    • Mathur A., Foody G.M. Crop classification by support vector machine with intelligently selected training data for an operational application. Int. J. Remote Sens. 2008, 29:2227-2240. 10.1080/01431160701395203.
    • (2008) Int. J. Remote Sens. , vol.29 , pp. 2227-2240
    • Mathur, A.1    Foody, G.M.2
  • 64
    • 0035837316 scopus 로고    scopus 로고
    • Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains, Japan
    • Murakami T., Ogawa S., Ishitsuka N., Kumagai K., Saito G. Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains, Japan. Int. J. Remote Sens. 2001, 22:1335-1348. 10.1080/01431160151144378.
    • (2001) Int. J. Remote Sens. , vol.22 , pp. 1335-1348
    • Murakami, T.1    Ogawa, S.2    Ishitsuka, N.3    Kumagai, K.4    Saito, G.5
  • 65
    • 33745891242 scopus 로고    scopus 로고
    • Resolution dependent errors in remote sensing of cultivated areas
    • Ozdogan M., Woodcock C.E. Resolution dependent errors in remote sensing of cultivated areas. Remote Sens. Environ. 2006, 103:203-217. 10.1016/j.rse.2006.04.004.
    • (2006) Remote Sens. Environ. , vol.103 , pp. 203-217
    • Ozdogan, M.1    Woodcock, C.E.2
  • 66
    • 13344278660 scopus 로고    scopus 로고
    • Random forest classifier for remote sensing classification
    • Pal M. Random forest classifier for remote sensing classification. Int. J. Remote Sens. 2005, 26:217-222.
    • (2005) Int. J. Remote Sens. , vol.26 , pp. 217-222
    • Pal, M.1
  • 67
    • 77951295936 scopus 로고    scopus 로고
    • Feature selection for classification of hyperspectral data by SVM
    • Pal M., Foody G.M. Feature selection for classification of hyperspectral data by SVM. IEEE Trans. Geosci. Remote Sens. 2010, 48:2297-2307. 10.1109/TGRS.2009.2039484.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , pp. 2297-2307
    • Pal, M.1    Foody, G.M.2
  • 68
    • 13644256120 scopus 로고    scopus 로고
    • Support vector machines for classification in remote sensing
    • Pal M., Mather P.M. Support vector machines for classification in remote sensing. Int. J. Remote Sens. 2005, 26:1007-1011.
    • (2005) Int. J. Remote Sens. , vol.26 , pp. 1007-1011
    • Pal, M.1    Mather, P.M.2
  • 69
    • 33748611921 scopus 로고    scopus 로고
    • Ensemble based systems in decision making
    • Policar R. Ensemble based systems in decision making. IEEE Circuits Syst. Mag. 2006, 6:21-45.
    • (2006) IEEE Circuits Syst. Mag. , vol.6 , pp. 21-45
    • Policar, R.1
  • 70
    • 78650649545 scopus 로고    scopus 로고
    • A Language and Environment for Statistical Computing
    • R Development Core Team, 2014. A Language and Environment for Statistical Computing.
    • (2014)
  • 71
    • 84857753353 scopus 로고    scopus 로고
    • Random forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture
    • Rodriguez-Galiano V.F., Chica-Olmo M., Abarca-Hernandez F., Atkinson P.M., Jeganathan C. Random forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture. Remote Sens. Environ. 2012, 121:93-107. 10.1016/j.rse.2011.12.003.
    • (2012) Remote Sens. Environ. , vol.121 , pp. 93-107
    • Rodriguez-Galiano, V.F.1    Chica-Olmo, M.2    Abarca-Hernandez, F.3    Atkinson, P.M.4    Jeganathan, C.5
  • 73
    • 0033670474 scopus 로고    scopus 로고
    • Irrigation expansion and dynamics of desertification in the Circum-Aral region of Central Asia
    • Saiko T.A., Zonn I.S. Irrigation expansion and dynamics of desertification in the Circum-Aral region of Central Asia. Appl. Geogr. 2000, 20:349-367.
    • (2000) Appl. Geogr. , vol.20 , pp. 349-367
    • Saiko, T.A.1    Zonn, I.S.2
  • 75
    • 84860601047 scopus 로고    scopus 로고
    • Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points
    • Shao Y., Lunetta R.S. Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points. ISPRS J. Photogramm. Remote Sens. 2012, 70:78-87. 10.1016/j.isprsjprs.2012.04.001.
    • (2012) ISPRS J. Photogramm. Remote Sens. , vol.70 , pp. 78-87
    • Shao, Y.1    Lunetta, R.S.2
  • 77
    • 84903538782 scopus 로고    scopus 로고
    • A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5 imagery
    • Tehrany M.S., Pradhan B., Jebuv M.N. A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5 imagery. Geocarto Int. 2013, 29:351-369. 10.1080/10106049.2013.768300.
    • (2013) Geocarto Int. , vol.29 , pp. 351-369
    • Tehrany, M.S.1    Pradhan, B.2    Jebuv, M.N.3
  • 79
    • 82155170603 scopus 로고    scopus 로고
    • Field-based crop classification using SPOT4, SPOT5, IKONOS and QuickBird imagery for agricultural areas: a comparison study
    • Turker M., Ozdarici A. Field-based crop classification using SPOT4, SPOT5, IKONOS and QuickBird imagery for agricultural areas: a comparison study. Int. J. Remote Sens. 2011, 32:37-41.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 37-41
    • Turker, M.1    Ozdarici, A.2
  • 81
    • 0004217877 scopus 로고
    • Butterworth & Co. Publishers Ltd., Butterworth
    • Van Rijsbergen C.J. Information Retrieval 1979, Butterworth & Co. Publishers Ltd., Butterworth. second ed.
    • (1979) Information Retrieval
    • Van Rijsbergen, C.J.1
  • 83
    • 39749173163 scopus 로고    scopus 로고
    • Large-area crop mapping using time-series MODIS 250m NDVI data: an assessment for the U.S. Central Great Plains
    • Wardlow B.D., Egbert S.L. Large-area crop mapping using time-series MODIS 250m NDVI data: an assessment for the U.S. Central Great Plains. Remote Sens. Environ. 2008, 112:1096-1116. 10.1016/j.rse.2007.07.019.
    • (2008) Remote Sens. Environ. , vol.112 , pp. 1096-1116
    • Wardlow, B.D.1    Egbert, S.L.2
  • 84
    • 34247523027 scopus 로고    scopus 로고
    • Analysis of time-series MODIS 250m vegetation index data for crop classification in the U.S. Central Great Plains
    • Wardlow B.D., Egbert S.L., Kastens J.H. Analysis of time-series MODIS 250m vegetation index data for crop classification in the U.S. Central Great Plains. Remote Sens. Environ. 2007, 108:290-310. 10.1016/j.rse.2006.11.021.
    • (2007) Remote Sens. Environ. , vol.108 , pp. 290-310
    • Wardlow, B.D.1    Egbert, S.L.2    Kastens, J.H.3
  • 85
    • 36349007145 scopus 로고    scopus 로고
    • Fusion of support vector machines for classification of multisensor data
    • Waske B., Benediktsson J.A. Fusion of support vector machines for classification of multisensor data. IEEE Trans. Geosci. Remote Sens. 2007, 45:3858-3866.
    • (2007) IEEE Trans. Geosci. Remote Sens. , vol.45 , pp. 3858-3866
    • Waske, B.1    Benediktsson, J.A.2
  • 87
    • 69849104695 scopus 로고    scopus 로고
    • Classifier ensembles for land cover mapping using multitemporal SAR imagery
    • Waske B., Braun M. Classifier ensembles for land cover mapping using multitemporal SAR imagery. ISPRS J. Photogramm. Remote Sens. 2009, 64:450-457. 10.1016/j.isprsjprs.2009.01.003.
    • (2009) ISPRS J. Photogramm. Remote Sens. , vol.64 , pp. 450-457
    • Waske, B.1    Braun, M.2
  • 88
    • 45849101525 scopus 로고    scopus 로고
    • Classifying multilevel imagery from SAR and optical sensors by decision fusion
    • Waske B., van der Linden S. Classifying multilevel imagery from SAR and optical sensors by decision fusion. IEEE Trans. Geosci. Remote Sens. 2008, 46:1457-1466.
    • (2008) IEEE Trans. Geosci. Remote Sens. , vol.46 , pp. 1457-1466
    • Waske, B.1    van der Linden, S.2
  • 89
  • 90
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolpert D.H. Stacked generalization. Neural Networks 1992, 5:241-259. 10.1016/S0893-6080(05)80023-1.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.H.1
  • 91
    • 0030784292 scopus 로고    scopus 로고
    • A general approach to the fusion of imprecise information
    • Yager R.R. A general approach to the fusion of imprecise information. Int. J. Intell. Syst. 1997, 12:1-29.
    • (1997) Int. J. Intell. Syst. , vol.12 , pp. 1-29
    • Yager, R.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.