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Volumn 190, Issue , 2017, Pages 188-197

Using mixed objects in the training of object-based image classifications

Author keywords

Mixed pixels; OBIA; Over segmentation; Scale parameter; Under segmentation

Indexed keywords

IMAGE ANALYSIS; IMAGE SEGMENTATION; MAPPING; NEURAL NETWORKS; PIXELS; REMOTE SENSING;

EID: 85008210901     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2016.12.017     Document Type: Article
Times cited : (50)

References (88)
  • 1
    • 84862886508 scopus 로고    scopus 로고
    • Introduction to the GEOBIA 2010 special issue: from pixels to geographic objects in remote sensing image analysis
    • Addink, E.A., Van Coillie, F.M.B., De Jong, S.M., Introduction to the GEOBIA 2010 special issue: from pixels to geographic objects in remote sensing image analysis. Int. J. Appl. Earth Obs. Geoinf. 15 (2012), 1–6, 10.1016/j.jag.2011.12.001.
    • (2012) Int. J. Appl. Earth Obs. Geoinf. , vol.15 , pp. 1-6
    • Addink, E.A.1    Van Coillie, F.M.B.2    De Jong, S.M.3
  • 2
    • 0001812168 scopus 로고    scopus 로고
    • Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation
    • J. Strobl T. Blaschke G. Griesebner Herbert Wichmann Verlag Heidelberg
    • Baatz, M., Schäpe, A., Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation. Strobl, J., Blaschke, T., Griesebner, G., (eds.) Angewandte Geographische Informationsverarbeitung XII Beiträge Zum AGIT-Symposium Salzburg 2000, 2000, Herbert Wichmann Verlag, Heidelberg, 12–23.
    • (2000) Angewandte Geographische Informationsverarbeitung XII, Beiträge Zum AGIT-Symposium Salzburg 2000 , pp. 12-23
    • Baatz, M.1    Schäpe, A.2
  • 3
    • 84904909081 scopus 로고    scopus 로고
    • Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery
    • Belgiu, M., Drǎguţ, L., Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery. ISPRS J. Photogramm. Remote Sens. 96 (2014), 67–75, 10.1016/j.isprsjprs.2014.07.002.
    • (2014) ISPRS J. Photogramm. Remote Sens. , vol.96 , pp. 67-75
    • Belgiu, M.1    Drǎguţ, L.2
  • 4
    • 0033434029 scopus 로고    scopus 로고
    • A fuzzy set-based accuracy assessment of soft classification
    • Binaghi, E., Brivio, P.A., Ghezzi, P., Rampini, A., A fuzzy set-based accuracy assessment of soft classification. Pattern Recogn. Lett. 20 (1999), 935–948, 10.1016/S0167-8655(99)00061-6.
    • (1999) Pattern Recogn. Lett. , vol.20 , pp. 935-948
    • Binaghi, E.1    Brivio, P.A.2    Ghezzi, P.3    Rampini, A.4
  • 6
    • 84876249625 scopus 로고    scopus 로고
    • Object-based mapping of native vegetation and para grass (Urochloa mutica) on a monsoonal wetland of Kakadu NP using a Landsat 5 TM dry-season time series
    • Boyden, J., Joyce, K.E., Boggs, G., Wurm, P., Object-based mapping of native vegetation and para grass (Urochloa mutica) on a monsoonal wetland of Kakadu NP using a Landsat 5 TM dry-season time series. J. Spat. Sci. 58 (2013), 53–77, 10.1080/14498596.2012.759086.
    • (2013) J. Spat. Sci. , vol.58 , pp. 53-77
    • Boyden, J.1    Joyce, K.E.2    Boggs, G.3    Wurm, P.4
  • 7
    • 85008236601 scopus 로고    scopus 로고
    • Carta de uso e ocupação do solo de Portugal Continental para 2007: Memória descritiva
    • Instituto Geográfico Português Lisbon
    • Caetano, M., Nunes, A., Dinis, J., Pereira, M.D.C., Marrecas, P., Nunes, V., Carta de uso e ocupação do solo de Portugal Continental para 2007: Memória descritiva. 2010, Instituto Geográfico Português, Lisbon.
    • (2010)
    • Caetano, M.1    Nunes, A.2    Dinis, J.3    Pereira, M.D.C.4    Marrecas, P.5    Nunes, V.6
  • 8
    • 85007884501 scopus 로고    scopus 로고
    • A comparison of object-based and contextual pixel-based classifications using high and medium spatial resolution images
    • Cai, S., Liu, D., A comparison of object-based and contextual pixel-based classifications using high and medium spatial resolution images. Remote Sens. Lett. 4 (2013), 998–1007, 10.1080/2150704X.2013.828180.
    • (2013) Remote Sens. Lett. , vol.4 , pp. 998-1007
    • Cai, S.1    Liu, D.2
  • 9
    • 84938420549 scopus 로고    scopus 로고
    • A local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery
    • Cánovas-García, F., Alonso-Sarría, F., A local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery. Geocarto Int. 30 (2015), 937–961, 10.1080/10106049.2015.1004131.
    • (2015) Geocarto Int. , vol.30 , pp. 937-961
    • Cánovas-García, F.1    Alonso-Sarría, F.2
  • 10
    • 39749111391 scopus 로고    scopus 로고
    • Contribution of multispectral and multitemporal information from MODIS images to land cover classification
    • Carrão, H., Goncalves, P., Caetano, M., Contribution of multispectral and multitemporal information from MODIS images to land cover classification. Remote Sens. Environ. 112 (2008), 986–997, 10.1016/j.rse.2007.07.002.
    • (2008) Remote Sens. Environ. , vol.112 , pp. 986-997
    • Carrão, H.1    Goncalves, P.2    Caetano, M.3
  • 11
    • 84893924014 scopus 로고    scopus 로고
    • The impact of object size on the thematic accuracy of landcover maps
    • Castilla, G., Hernando, A., Zhang, C., McDermid, G.J., The impact of object size on the thematic accuracy of landcover maps. Int. J. Remote Sens. 35 (2014), 1029–1037, 10.1080/01431161.2013.875630.
    • (2014) Int. J. Remote Sens. , vol.35 , pp. 1029-1037
    • Castilla, G.1    Hernando, A.2    Zhang, C.3    McDermid, G.J.4
  • 12
    • 77949838817 scopus 로고    scopus 로고
    • Accuracy assessment measures for object-based image segmentation goodness. Photogramm. Eng
    • Clinton, N., Holt, A., Scarborough, J., Yan, L., Gong, P., Accuracy assessment measures for object-based image segmentation goodness. Photogramm. Eng. Remote Sens. 76 (2010), 289–299.
    • (2010) Remote Sens. , vol.76 , pp. 289-299
    • Clinton, N.1    Holt, A.2    Scarborough, J.3    Yan, L.4    Gong, P.5
  • 13
    • 84930066941 scopus 로고    scopus 로고
    • Integrating user needs on misclassification error sensitivity into image segmentation quality assessment
    • Costa, H., Foody, G.M., Boyd, D.S., Integrating user needs on misclassification error sensitivity into image segmentation quality assessment. Photogramm. Eng. Remote Sens. 81 (2015), 451–459, 10.14358/PERS.81.6.451.
    • (2015) Photogramm. Eng. Remote Sens. , vol.81 , pp. 451-459
    • Costa, H.1    Foody, G.M.2    Boyd, D.S.3
  • 14
    • 0032551520 scopus 로고    scopus 로고
    • Synergy in remote sensing-what's in a pixel?
    • Cracknell, A.P., Synergy in remote sensing-what's in a pixel?. Int. J. Remote Sens. 19 (1998), 2025–2047.
    • (1998) Int. J. Remote Sens. , vol.19 , pp. 2025-2047
    • Cracknell, A.P.1
  • 15
    • 0043267583 scopus 로고    scopus 로고
    • An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities
    • Dean, A.M., Smith, G.M., An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities. Int. J. Remote Sens. 24 (2003), 2905–2920, 10.1080/01431160210155910.
    • (2003) Int. J. Remote Sens. , vol.24 , pp. 2905-2920
    • Dean, A.M.1    Smith, G.M.2
  • 16
    • 0043196816 scopus 로고    scopus 로고
    • Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification
    • Dorren, L., Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification. For. Ecol. Manag. 183 (2003), 31–46, 10.1016/S0378-1127(03)00113-0.
    • (2003) For. Ecol. Manag. , vol.183 , pp. 31-46
    • Dorren, L.1
  • 17
    • 81355138692 scopus 로고    scopus 로고
    • Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China
    • Dronova, I., Gong, P., Wang, L., Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sens. Environ. 115 (2011), 3220–3236, 10.1016/j.rse.2011.07.006.
    • (2011) Remote Sens. Environ. , vol.115 , pp. 3220-3236
    • Dronova, I.1    Gong, P.2    Wang, L.3
  • 18
    • 84867594546 scopus 로고    scopus 로고
    • Landscape analysis of wetland plant functional types: the effects of image segmentation scale, vegetation classes and classification methods
    • Dronova, I., Gong, P., Clinton, N.E., Wang, L., Fu, W., Qi, S., Liu, Y., Landscape analysis of wetland plant functional types: the effects of image segmentation scale, vegetation classes and classification methods. Remote Sens. Environ. 127 (2012), 357–369, 10.1016/j.rse.2012.09.018.
    • (2012) Remote Sens. Environ. , vol.127 , pp. 357-369
    • Dronova, I.1    Gong, P.2    Clinton, N.E.3    Wang, L.4    Fu, W.5    Qi, S.6    Liu, Y.7
  • 19
    • 0036827910 scopus 로고    scopus 로고
    • Bayesian soft classification for sub-pixel analysis: a critical evaluation
    • Eastman, J.R., Laney, R.M., Bayesian soft classification for sub-pixel analysis: a critical evaluation. Photogramm. Eng. Remote. Sens. 68 (2002), 1149–1154.
    • (2002) Photogramm. Eng. Remote. Sens. , vol.68 , pp. 1149-1154
    • Eastman, J.R.1    Laney, R.M.2
  • 20
    • 0031190719 scopus 로고    scopus 로고
    • Hierarchical maximum-likelihood classification for improved accuracies
    • Ediriwickrema, J., Khorram, S., Hierarchical maximum-likelihood classification for improved accuracies. IEEE Trans. Geosci. Remote Sens. 35 (1997), 810–816, 10.1109/36.602523.
    • (1997) IEEE Trans. Geosci. Remote Sens. , vol.35 , pp. 810-816
    • Ediriwickrema, J.1    Khorram, S.2
  • 21
    • 84940957376 scopus 로고    scopus 로고
    • Pixel-based and object-based classifications using high- and medium-spatial-resolution imageries in the urban and suburban landscapes
    • Estoque, R.C., Murayama, Y., Akiyama, C.M., Pixel-based and object-based classifications using high- and medium-spatial-resolution imageries in the urban and suburban landscapes. Geocarto Int. 30 (2015), 1113–1129, 10.1080/10106049.2015.1027291.
    • (2015) Geocarto Int. , vol.30 , pp. 1113-1129
    • Estoque, R.C.1    Murayama, Y.2    Akiyama, C.M.3
  • 22
    • 0031080306 scopus 로고    scopus 로고
    • The pixel: a snare and a delusion
    • Fisher, P., The pixel: a snare and a delusion. Int. J. Remote Sens. 18 (1997), 679–685, 10.1080/014311697219015.
    • (1997) Int. J. Remote Sens. , vol.18 , pp. 679-685
    • Fisher, P.1
  • 23
    • 0028982899 scopus 로고
    • Cross-entropy for the evaluation of the accuracy of a fuzzy land cover classification with fuzzy ground data
    • Foody, G.M., Cross-entropy for the evaluation of the accuracy of a fuzzy land cover classification with fuzzy ground data. ISPRS J. Photogramm. Remote Sens. 50 (1995), 2–12, 10.1016/0924-2716(95)90116-V.
    • (1995) ISPRS J. Photogramm. Remote Sens. , vol.50 , pp. 2-12
    • Foody, G.M.1
  • 24
    • 0030135691 scopus 로고    scopus 로고
    • Approaches for the production and evaluation of fuzzy land cover classifications from remotely-sensed data
    • Foody, G.M., Approaches for the production and evaluation of fuzzy land cover classifications from remotely-sensed data. Int. J. Remote Sens. 17 (1996), 1317–1340, 10.1080/01431169608948706.
    • (1996) Int. J. Remote Sens. , vol.17 , pp. 1317-1340
    • Foody, G.M.1
  • 25
    • 21744459008 scopus 로고    scopus 로고
    • Fully fuzzy supervised classification of land cover from remotely sensed imagery with an artificial neural network
    • Foody, G.M., Fully fuzzy supervised classification of land cover from remotely sensed imagery with an artificial neural network. Neural Comput. & Applic. 5 (1997), 238–247, 10.1007/BF01424229.
    • (1997) Neural Comput. & Applic. , vol.5 , pp. 238-247
    • Foody, G.M.1
  • 26
    • 0033005338 scopus 로고    scopus 로고
    • The continuum of classification fuzziness in thematic mapping
    • Foody, G.M., The continuum of classification fuzziness in thematic mapping. Photogramm. Eng. Remote Sens. 65 (1999), 443–451.
    • (1999) Photogramm. Eng. Remote Sens. , vol.65 , pp. 443-451
    • Foody, G.M.1
  • 27
    • 0033372875 scopus 로고    scopus 로고
    • The significance of border training patterns in classification by a feedforward neural network using back propagation learning
    • Foody, G.M., The significance of border training patterns in classification by a feedforward neural network using back propagation learning. Int. J. Remote Sens. 20 (1999), 3549–3562, 10.1080/014311699211192.
    • (1999) Int. J. Remote Sens. , vol.20 , pp. 3549-3562
    • Foody, G.M.1
  • 28
    • 0034010010 scopus 로고    scopus 로고
    • Estimation of sub-pixel land cover composition in the presence of untrained classes
    • Foody, G.M., Estimation of sub-pixel land cover composition in the presence of untrained classes. Comput. Geosci. 26 (2000), 469–478, 10.1016/S0098-3004(99)00125-9.
    • (2000) Comput. Geosci. , vol.26 , pp. 469-478
    • Foody, G.M.1
  • 29
    • 40349114181 scopus 로고    scopus 로고
    • Harshness in image classification accuracy assessment
    • Foody, G.M., Harshness in image classification accuracy assessment. Int. J. Remote Sens. 29 (2008), 3137–3158, 10.1080/01431160701442120.
    • (2008) Int. J. Remote Sens. , vol.29 , pp. 3137-3158
    • Foody, G.M.1
  • 30
    • 0030292025 scopus 로고    scopus 로고
    • Incorporating mixed pixels in the training, allocation and testing stages of supervised classifications
    • Foody, G.M., Arora, M.K., Incorporating mixed pixels in the training, allocation and testing stages of supervised classifications. Pattern Recogn. Lett. 17 (1996), 1389–1398, 10.1016/S0167-8655(96)00095-5.
    • (1996) Pattern Recogn. Lett. , vol.17 , pp. 1389-1398
    • Foody, G.M.1    Arora, M.K.2
  • 31
    • 33745756516 scopus 로고    scopus 로고
    • The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM
    • Foody, G.M., Mathur, A., The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM. Remote Sens. Environ. 103 (2006), 179–189, 10.1016/j.rse.2006.04.001.
    • (2006) Remote Sens. Environ. , vol.103 , pp. 179-189
    • Foody, G.M.1    Mathur, A.2
  • 32
    • 77950537175 scopus 로고    scopus 로고
    • Regularization paths for generalized linear models via coordinate descent
    • Friedman, J., Hastie, T., Tibshirani, R., Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33 (2010), 1–22, 10.1359/JBMR.0301229.
    • (2010) J. Stat. Softw. , vol.33 , pp. 1-22
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 34
    • 79960048515 scopus 로고    scopus 로고
    • Optimal region growing segmentation and its effect on classification accuracy
    • Gao, Y., Mas, J.F., Kerle, N., Pacheco, J.A.N., Optimal region growing segmentation and its effect on classification accuracy. Int. J. Remote Sens. 32 (2011), 3747–3763, 10.1080/01431161003777189.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 3747-3763
    • Gao, Y.1    Mas, J.F.2    Kerle, N.3    Pacheco, J.A.N.4
  • 35
    • 84924487116 scopus 로고    scopus 로고
    • Land take and food security: assessment of land take on the agricultural production in Europe
    • Gardi, C., Panagos, P., Van Liedekerke, M., Bosco, C., De Brogniez, D., Land take and food security: assessment of land take on the agricultural production in Europe. J. Environ. Plan. Manag. 58 (2015), 898–912, 10.1080/09640568.2014.899490.
    • (2015) J. Environ. Plan. Manag. , vol.58 , pp. 898-912
    • Gardi, C.1    Panagos, P.2    Van Liedekerke, M.3    Bosco, C.4    De Brogniez, D.5
  • 36
    • 84943374021 scopus 로고    scopus 로고
    • Mapping land cover and land use from object-based classification: an example from a complex agricultural landscape
    • Goodin, D.G., Anibas, K.L., Bezymennyi, M., Mapping land cover and land use from object-based classification: an example from a complex agricultural landscape. Int. J. Remote Sens. 36 (2015), 4702–4723, 10.1080/01431161.2015.1088674.
    • (2015) Int. J. Remote Sens. , vol.36 , pp. 4702-4723
    • Goodin, D.G.1    Anibas, K.L.2    Bezymennyi, M.3
  • 37
    • 84964534052 scopus 로고    scopus 로고
    • Combining transductive and active learning to improve object-based classification of remote sensing images
    • Güttler, F.N., Ienco, D., Poncelet, P., Teisseire, M., Combining transductive and active learning to improve object-based classification of remote sensing images. Remote Sens. Lett. 7 (2016), 358–367, 10.1080/2150704X.2016.1142678.
    • (2016) Remote Sens. Lett. , vol.7 , pp. 358-367
    • Güttler, F.N.1    Ienco, D.2    Poncelet, P.3    Teisseire, M.4
  • 38
    • 34548420140 scopus 로고    scopus 로고
    • A method for calibrated maximum likelihood classification of forest types
    • Hagner, O., Reese, H., A method for calibrated maximum likelihood classification of forest types. Remote Sens. Environ. 110 (2007), 438–444, 10.1016/j.rse.2006.08.017.
    • (2007) Remote Sens. Environ. , vol.110 , pp. 438-444
    • Hagner, O.1    Reese, H.2
  • 40
    • 84856723719 scopus 로고    scopus 로고
    • An object-based classification of mangroves using a hybrid decision tree—support vector machine approach
    • Heumann, B.W., An object-based classification of mangroves using a hybrid decision tree—support vector machine approach. Remote Sens. 3 (2011), 2440–2460, 10.3390/rs3112440.
    • (2011) Remote Sens. , vol.3 , pp. 2440-2460
    • Heumann, B.W.1
  • 41
    • 34548430966 scopus 로고    scopus 로고
    • Representation of an alpine treeline ecotone in SPOT 5 HRG data
    • Hill, R., Granica, K., Smith, G.M., Schardt, M., Representation of an alpine treeline ecotone in SPOT 5 HRG data. Remote Sens. Environ. 110 (2007), 458–467, 10.1016/j.rse.2006.11.031.
    • (2007) Remote Sens. Environ. , vol.110 , pp. 458-467
    • Hill, R.1    Granica, K.2    Smith, G.M.3    Schardt, M.4
  • 42
    • 78951487464 scopus 로고    scopus 로고
    • Image segmentation and classification of Landsat thematic mapper data using a sampling approach for forest cover assessment
    • Hirata, Y., Takahashi, T., Image segmentation and classification of Landsat thematic mapper data using a sampling approach for forest cover assessment. Can. J. For. Res. 41 (2011), 35–43, 10.1139/X10-130.
    • (2011) Can. J. For. Res. , vol.41 , pp. 35-43
    • Hirata, Y.1    Takahashi, T.2
  • 43
    • 18144430667 scopus 로고    scopus 로고
    • On the choice of spatial and categorical scale in remote sensing land cover classification
    • Ju, J., Gopal, S., Kolaczyk, E.D., On the choice of spatial and categorical scale in remote sensing land cover classification. Remote Sens. Environ. 96 (2005), 62–77, 10.1016/j.rse.2005.01.016.
    • (2005) Remote Sens. Environ. , vol.96 , pp. 62-77
    • Ju, J.1    Gopal, S.2    Kolaczyk, E.D.3
  • 44
    • 79957608758 scopus 로고    scopus 로고
    • Multi-scale GEOBIA with very high spatial resolution digital aerial imagery: scale, texture and image objects
    • Kim, M., Warner, T., Multi-scale GEOBIA with very high spatial resolution digital aerial imagery: scale, texture and image objects. Int. J. Remote Sens. 32 (2011), 2825–2850, 10.1080/01431161003745608.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 2825-2850
    • Kim, M.1    Warner, T.2
  • 45
    • 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. 75 (2009), 819–829.
    • (2009) Photogramm. Eng. Remote Sens. , vol.75 , pp. 819-829
    • Kim, M.1    Madden, M.2    Warner, T.A.3
  • 46
    • 84878117929 scopus 로고    scopus 로고
    • GeoDMA—geographic data mining analyst
    • Körting, T.S., Garcia Fonseca, L.M., Câmara, G., GeoDMA—geographic data mining analyst. Comput. Geosci. 57 (2013), 133–145, 10.1016/j.cageo.2013.02.007.
    • (2013) Comput. Geosci. , vol.57 , pp. 133-145
    • Körting, T.S.1    Garcia Fonseca, L.M.2    Câmara, G.3
  • 47
    • 61349099437 scopus 로고    scopus 로고
    • Texture and scale in object-based analysis of subdecimeter resolution unmanned aerial vehicle (UAV) imagery
    • Laliberte, A.S., Rango, A., Texture and scale in object-based analysis of subdecimeter resolution unmanned aerial vehicle (UAV) imagery. IEEE Trans. Geosci. Remote Sens. 47 (2009), 1–10, 10.1109/TGRS.2008.2009355.
    • (2009) IEEE Trans. Geosci. Remote Sens. , vol.47 , pp. 1-10
    • Laliberte, A.S.1    Rango, A.2
  • 48
    • 33744771976 scopus 로고    scopus 로고
    • + using self-organizing map (SOM) neural networks for urban land cover characterization
    • + using self-organizing map (SOM) neural networks for urban land cover characterization. IEEE Trans. Geosci. Remote Sens. 44 (2006), 1642–1654, 10.1109/TGRS.2006.869984.
    • (2006) IEEE Trans. Geosci. Remote Sens. , vol.44 , pp. 1642-1654
    • Lee, S.1    Lathrop, R.G.2
  • 49
    • 85017406334 scopus 로고    scopus 로고
    • A systematic comparison of different object-based classification techniques using high spatial resolution imagery in agricultural environments
    • Li, M., Ma, L., Blaschke, T., Cheng, L., Tiede, D., A systematic comparison of different object-based classification techniques using high spatial resolution imagery in agricultural environments. Int. J. Appl. Earth Obs. Geoinf. 49 (2016), 87–98, 10.1016/j.jag.2016.01.011.
    • (2016) Int. J. Appl. Earth Obs. Geoinf. , vol.49 , pp. 87-98
    • Li, M.1    Ma, L.2    Blaschke, T.3    Cheng, L.4    Tiede, D.5
  • 50
    • 33947591833 scopus 로고    scopus 로고
    • A survey of image classification methods and techniques for improving classification performance
    • Lu, D., Weng, Q., A survey of image classification methods and techniques for improving classification performance. Int. J. Remote Sens. 28 (2007), 823–870, 10.1080/01431160600746456.
    • (2007) Int. J. Remote Sens. , vol.28 , pp. 823-870
    • Lu, D.1    Weng, Q.2
  • 51
    • 84922287164 scopus 로고    scopus 로고
    • Development of a multi-scale object-based shadow detection method for high spatial resolution image
    • Luo, H., Wang, L., Shao, Z., Li, D., Development of a multi-scale object-based shadow detection method for high spatial resolution image. IEEE Geosci. Remote Sens. Lett. 6 (2015), 59–68, 10.1080/2150704X.2014.1001079.
    • (2015) IEEE Geosci. Remote Sens. Lett. , vol.6 , pp. 59-68
    • Luo, H.1    Wang, L.2    Shao, Z.3    Li, D.4
  • 53
    • 84922357427 scopus 로고    scopus 로고
    • Training set size, scale, and features in geographic object-based image analysis of very high resolution unmanned aerial vehicle imagery
    • Ma, L., Cheng, L., Li, M., Liu, Y., Ma, X., Training set size, scale, and features in geographic object-based image analysis of very high resolution unmanned aerial vehicle imagery. ISPRS J. Photogramm. Remote Sens. 102 (2015), 14–27, 10.1016/j.isprsjprs.2014.12.026.
    • (2015) ISPRS J. Photogramm. Remote Sens. , vol.102 , pp. 14-27
    • Ma, L.1    Cheng, L.2    Li, M.3    Liu, Y.4    Ma, X.5
  • 55
    • 84885852299 scopus 로고    scopus 로고
    • Testing instead of assuming the importance of land use change scenarios to model species distributions under climate change
    • Martin, Y., Van Dyck, H., Dendoncker, N., Titeux, N., Testing instead of assuming the importance of land use change scenarios to model species distributions under climate change. Glob. Ecol. Biogeogr. 22 (2013), 1204–1216, 10.1111/geb.12087.
    • (2013) Glob. Ecol. Biogeogr. , vol.22 , pp. 1204-1216
    • Martin, Y.1    Van Dyck, H.2    Dendoncker, N.3    Titeux, N.4
  • 56
    • 84887456174 scopus 로고    scopus 로고
    • Comparison between pixel- and object-based image classification of a tropical landscape using Système Pour l'Observation de la Terre-5 imagery
    • Memarian, H., Balasundram, S.K., Khosla, R., Comparison between pixel- and object-based image classification of a tropical landscape using Système Pour l'Observation de la Terre-5 imagery. J. Appl. Remote. Sens., 7, 2013, 73512, 10.1117/1.JRS.7.073512.
    • (2013) J. Appl. Remote. Sens. , vol.7 , pp. 73512
    • Memarian, H.1    Balasundram, S.K.2    Khosla, R.3
  • 57
    • 84937918615 scopus 로고    scopus 로고
    • On the importance of training data sample selection in random forest image classification: a case study in peatland ecosystem mapping
    • Millard, K., Richardson, M., On the importance of training data sample selection in random forest image classification: a case study in peatland ecosystem mapping. Remote Sens., 2015, 10.3390/rs70708489.
    • (2015) Remote Sens.
    • Millard, K.1    Richardson, M.2
  • 58
    • 84893953517 scopus 로고    scopus 로고
    • Mapping vegetation morphology types in a dry savanna ecosystem: integrating hierarchical object-based image analysis with random forest
    • Mishra, N.B., Crews, K.a., Mapping vegetation morphology types in a dry savanna ecosystem: integrating hierarchical object-based image analysis with random forest. Int. J. Remote Sens. 35 (2014), 1175–1198, 10.1080/01431161.2013.876120.
    • (2014) Int. J. Remote Sens. , vol.35 , pp. 1175-1198
    • Mishra, N.B.1    Crews, K.A.2
  • 59
    • 84889597563 scopus 로고    scopus 로고
    • A framework for the geometric accuracy assessment of classified objects
    • Möller, M., Birger, J., Gidudu, A., Gläßer, C., A framework for the geometric accuracy assessment of classified objects. Int. J. Remote Sens. 34 (2013), 8685–8698, 10.1080/01431161.2013.845319.
    • (2013) Int. J. Remote Sens. , vol.34 , pp. 8685-8698
    • Möller, M.1    Birger, J.2    Gidudu, A.3    Gläßer, C.4
  • 60
    • 84962563851 scopus 로고    scopus 로고
    • Mapping complex urban land cover from spaceborne imagery: the influence of spatial resolution, spectral band set and classification approach
    • Momeni, R., Aplin, P., Boyd, D., Mapping complex urban land cover from spaceborne imagery: the influence of spatial resolution, spectral band set and classification approach. Remote Sens., 8, 2016, 88, 10.3390/rs8020088.
    • (2016) Remote Sens. , vol.8 , pp. 88
    • Momeni, R.1    Aplin, P.2    Boyd, D.3
  • 61
    • 84941695642 scopus 로고    scopus 로고
    • An object-based approach to delineate wetlands across landscapes of varied disturbance with high spatial resolution satellite imagery
    • Mui, A., He, Y., Weng, Q., An object-based approach to delineate wetlands across landscapes of varied disturbance with high spatial resolution satellite imagery. ISPRS J. Photogramm. Remote Sens. 109 (2015), 30–46, 10.1016/j.isprsjprs.2015.08.005.
    • (2015) ISPRS J. Photogramm. Remote Sens. , vol.109 , pp. 30-46
    • Mui, A.1    He, Y.2    Weng, Q.3
  • 63
    • 84869488312 scopus 로고    scopus 로고
    • Evaluation of SVM, RVM and SMLR for accurate image classification with limited ground data
    • Pal, M., Foody, G.M., Evaluation of SVM, RVM and SMLR for accurate image classification with limited ground data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5 (2012), 1344–1355, 10.1109/JSTARS.2012.2215310.
    • (2012) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. , vol.5 , pp. 1344-1355
    • Pal, M.1    Foody, G.M.2
  • 64
    • 0029341018 scopus 로고
    • A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification
    • Paola, J.D., Schowengerdt, R.a., A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. IEEE Trans. Geosci. Remote Sens. 33 (1995), 981–996, 10.1109/36.406684.
    • (1995) IEEE Trans. Geosci. Remote Sens. , vol.33 , pp. 981-996
    • Paola, J.D.1    Schowengerdt, R.A.2
  • 65
    • 84975753826 scopus 로고    scopus 로고
    • R: A Language and Environment for Statistical Computing
    • R Core Team, R: A Language and Environment for Statistical Computing. 2016.
    • (2016)
    • R Core Team1
  • 66
    • 84886930214 scopus 로고    scopus 로고
    • What makes segmentation good? A case study in boreal forest habitat mapping
    • Räsänen, A., Rusanen, A., Kuitunen, M., Lensu, A., What makes segmentation good? A case study in boreal forest habitat mapping. Int. J. Remote Sens. 34 (2013), 8603–8627, 10.1080/01431161.2013.845318.
    • (2013) Int. J. Remote Sens. , vol.34 , pp. 8603-8627
    • Räsänen, A.1    Rusanen, A.2    Kuitunen, M.3    Lensu, A.4
  • 67
    • 84896318609 scopus 로고    scopus 로고
    • Is there a preferred classifier for operational thematic mapping?
    • Richards, J., Kingsbury, N., Is there a preferred classifier for operational thematic mapping?. IEEE Trans. Geosci. Remote Sens. 52 (2014), 2715–2725, 10.1109/TGRS.2013.2264831.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , pp. 2715-2725
    • Richards, J.1    Kingsbury, N.2
  • 68
    • 79953222584 scopus 로고    scopus 로고
    • Comparison of pixel- and object-based classification in land cover change mapping
    • Robertson, L.D., King, D.J., Comparison of pixel- and object-based classification in land cover change mapping. Int. J. Remote Sens. 32 (2011), 1505–1529, 10.1080/01431160903571791.
    • (2011) Int. J. Remote Sens. , vol.32 , pp. 1505-1529
    • Robertson, L.D.1    King, D.J.2
  • 69
    • 84955719716 scopus 로고    scopus 로고
    • Improved hyperspectral image classification by active learning using pre-designed mixed pixels
    • Samat, A., Li, J., Liu, S., Du, P., Miao, Z., Luo, J., Improved hyperspectral image classification by active learning using pre-designed mixed pixels. Pattern Recogn. 51 (2016), 43–58, 10.1016/j.patcog.2015.08.019.
    • (2016) Pattern Recogn. , vol.51 , pp. 43-58
    • Samat, A.1    Li, J.2    Liu, S.3    Du, P.4    Miao, Z.5    Luo, J.6
  • 70
    • 84940705970 scopus 로고    scopus 로고
    • Estimating burned area in Mato Grosso, Brazil, using an object-based classification method on a systematic sample of medium resolution satellite images
    • Shimabukuro, Y.E., Miettinen, J., Beuchle, R., Grecchi, R.C., Simonetti, D., Achard, F., Estimating burned area in Mato Grosso, Brazil, using an object-based classification method on a systematic sample of medium resolution satellite images. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8 (2015), 4502–4508, 10.1109/JSTARS.2015.2464097.
    • (2015) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. , vol.8 , pp. 4502-4508
    • Shimabukuro, Y.E.1    Miettinen, J.2    Beuchle, R.3    Grecchi, R.C.4    Simonetti, D.5    Achard, F.6
  • 71
    • 33846840792 scopus 로고    scopus 로고
    • Estimation of fuzzy error matrix accuracy measures under stratified random sampling
    • Stehman, S.V., Arora, M.K., Kasetkasem, T., Varshney, P.K., Estimation of fuzzy error matrix accuracy measures under stratified random sampling. Photogramm. Eng. Remote Sens. 73 (2007), 165–173, 10.14358/PERS.73.2.165.
    • (2007) Photogramm. Eng. Remote Sens. , vol.73 , pp. 165-173
    • Stehman, S.V.1    Arora, M.K.2    Kasetkasem, T.3    Varshney, P.K.4
  • 72
    • 84905904405 scopus 로고    scopus 로고
    • A global 1-km consensus land-cover product for biodiversity and ecosystem modelling
    • Tuanmu, M.-N., Jetz, W., A global 1-km consensus land-cover product for biodiversity and ecosystem modelling. Glob. Ecol. Biogeogr. 23 (2014), 1031–1045, 10.1111/geb.12182.
    • (2014) Glob. Ecol. Biogeogr. , vol.23 , pp. 1031-1045
    • Tuanmu, M.-N.1    Jetz, W.2
  • 75
    • 33846195367 scopus 로고    scopus 로고
    • Incorporating uncertainty via hierarchical classification using fuzzy decision trees
    • van de Vlag, D.E., Stein, A., Incorporating uncertainty via hierarchical classification using fuzzy decision trees. IEEE Trans. Geosci. Remote Sens. 45 (2007), 237–245, 10.1109/TGRS.2006.885403.
    • (2007) IEEE Trans. Geosci. Remote Sens. , vol.45 , pp. 237-245
    • van de Vlag, D.E.1    Stein, A.2
  • 76
    • 0003895851 scopus 로고    scopus 로고
    • Modern Applied Statistics with S
    • Springer New York
    • Venables, W.N., Ripley, B.D., Modern Applied Statistics with S. 2002, Springer, New York.
    • (2002)
    • Venables, W.N.1    Ripley, B.D.2
  • 77
    • 84864502305 scopus 로고    scopus 로고
    • External geo-information in the segmentation of VHR imagery improves the detection of imperviousness in urban neighborhoods
    • Verbeeck, K., Hermy, M., Van Orshoven, J., External geo-information in the segmentation of VHR imagery improves the detection of imperviousness in urban neighborhoods. Int. J. Appl. Earth Obs. Geoinf. 18 (2012), 428–435, 10.1016/j.jag.2012.03.015.
    • (2012) Int. J. Appl. Earth Obs. Geoinf. , vol.18 , pp. 428-435
    • Verbeeck, K.1    Hermy, M.2    Van Orshoven, J.3
  • 78
    • 0025402179 scopus 로고
    • Fuzzy supervised classification of remote sensing images
    • Wang, F., Fuzzy supervised classification of remote sensing images. IEEE Trans. Geosci. Remote Sens. 28 (1990), 194–201, 10.1109/36.46698.
    • (1990) IEEE Trans. Geosci. Remote Sens. , vol.28 , pp. 194-201
    • Wang, F.1
  • 79
    • 10844220846 scopus 로고    scopus 로고
    • Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery
    • Wang, L., Sousa, W.P., Gong, P., Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery. Int. J. Remote Sens. 25 (2004), 5655–5668, 10.1080/014311602331291215.
    • (2004) Int. J. Remote Sens. , vol.25 , pp. 5655-5668
    • Wang, L.1    Sousa, W.P.2    Gong, P.3
  • 80
    • 84455175710 scopus 로고    scopus 로고
    • Comparing object-based and pixel-based classifications for mapping savannas
    • Whiteside, T.G., Boggs, G.S., Maier, S.W., Comparing object-based and pixel-based classifications for mapping savannas. Int. J. Appl. Earth Obs. Geoinf. 13 (2011), 884–893, 10.1016/j.jag.2011.06.008.
    • (2011) Int. J. Appl. Earth Obs. Geoinf. , vol.13 , pp. 884-893
    • Whiteside, T.G.1    Boggs, G.S.2    Maier, S.W.3
  • 81
    • 84897470278 scopus 로고    scopus 로고
    • Area-based and location-based validation of classified image objects
    • Whiteside, T.G., Maier, S.W., Boggs, G.S., Area-based and location-based validation of classified image objects. Int. J. Appl. Earth Obs. Geoinf. 28 (2014), 117–130, 10.1016/j.jag.2013.11.009.
    • (2014) Int. J. Appl. Earth Obs. Geoinf. , vol.28 , pp. 117-130
    • Whiteside, T.G.1    Maier, S.W.2    Boggs, G.S.3
  • 82
    • 70449338125 scopus 로고    scopus 로고
    • Quantifying high-resolution impervious surfaces using spectral mixture analysis
    • Wu, C., Quantifying high-resolution impervious surfaces using spectral mixture analysis. Int. J. Remote Sens. 30 (2009), 2915–2932, 10.1080/01431160802558634.
    • (2009) Int. J. Remote Sens. , vol.30 , pp. 2915-2932
    • Wu, C.1
  • 83
    • 84920934323 scopus 로고    scopus 로고
    • A discrepancy measure for segmentation evaluation from the perspective of object recognition
    • Yang, J., He, Y., Caspersen, J., Jones, T., A discrepancy measure for segmentation evaluation from the perspective of object recognition. ISPRS J. Photogramm. Remote Sens. 101 (2015), 186–192, 10.1016/j.isprsjprs.2014.12.015.
    • (2015) ISPRS J. Photogramm. Remote Sens. , vol.101 , pp. 186-192
    • Yang, J.1    He, Y.2    Caspersen, J.3    Jones, T.4
  • 84
    • 0030216623 scopus 로고    scopus 로고
    • A survey on evaluation methods for image segmentation
    • Zhang, Y.J., A survey on evaluation methods for image segmentation. Pattern Recogn. 29 (1996), 1335–1346, 10.1016/0031-3203(95)00169-7.
    • (1996) Pattern Recogn. , vol.29 , pp. 1335-1346
    • Zhang, Y.J.1
  • 85
    • 0035048764 scopus 로고    scopus 로고
    • Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and artificial neural network approaches
    • Zhang, J., Foody, G.M., Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: statistical and artificial neural network approaches. Int. J. Remote Sens. 22 (2001), 615–628, 10.1080/01431160050505883.
    • (2001) Int. J. Remote Sens. , vol.22 , pp. 615-628
    • Zhang, J.1    Foody, G.M.2
  • 86
    • 46249127568 scopus 로고    scopus 로고
    • An object-oriented approach for analysing and characterizing urban landscape at the parcel level
    • Zhou, W., Troy, A., An object-oriented approach for analysing and characterizing urban landscape at the parcel level. Int. J. Remote Sens. 29 (2008), 3119–3135, 10.1080/01431160701469065.
    • (2008) Int. J. Remote Sens. , vol.29 , pp. 3119-3135
    • Zhou, W.1    Troy, A.2
  • 87
    • 66049089993 scopus 로고    scopus 로고
    • Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: a comparison study
    • Zhou, W., Huang, G., Troy, A., Cadenasso, M.L., Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: a comparison study. Remote Sens. Environ. 113 (2009), 1769–1777, 10.1016/j.rse.2009.04.007.
    • (2009) Remote Sens. Environ. , vol.113 , pp. 1769-1777
    • Zhou, W.1    Huang, G.2    Troy, A.3    Cadenasso, M.L.4
  • 88
    • 84874766198 scopus 로고    scopus 로고
    • Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2
    • Zhu, Z., Bi, J., Pan, Y., Ganguly, S., Anav, A., Xu, L., Samanta, A., Piao, S., Nemani, R.R., Myneni, R.B., Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2. Remote Sens., 5, 2013, 927, 10.3390/rs5020927.
    • (2013) Remote Sens. , vol.5 , pp. 927
    • Zhu, Z.1    Bi, J.2    Pan, Y.3    Ganguly, S.4    Anav, A.5    Xu, L.6    Samanta, A.7    Piao, S.8    Nemani, R.R.9    Myneni, R.B.10


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