Tree crown delineation on UltraCam-D aerial imagery with SVM classification technique optimised by Taguchi method in Zagros woodlands

References

• Aber, S., Salari, D., and Parsa, M.R., 2010. Employing the Taguchi method to obtain the optimum conditions of coagulation-flocculation process in tannery wastewater treatment. Chemical Engineering Journal, 162, 127–134. doi:10.1016/j.cej.2010.05.012
   Web of Science ®Google Scholar
• Al-Darrab, I.A., et al., 2009. Application of the Taguchi method for optimization of parameters to maximize text message entering performance of mobile phone users. International Journal of Quality & Reliability Management, 26, 469–479. doi:10.1108/02656710910956193
   Google Scholar
• Ali, S.A., Rangzan, K., and Pirasteh, S., 2003. Remote sensing and GIS study of tectonics and net erosion rates in the Zagros structural belt, Southwestern Iran. Mapping Sciences & Remote Sensing, 40 (4), 258–267. doi:10.2747/0749-3878.40.4.258
   Google Scholar
• Belousov, A.I., Verzakov, S.A., and Von Frese, J., 2002. Applicational aspects of support vector machines. Journal of Chemometrics, 16, 482–489. doi:10.1002/cem.744
   Web of Science ®Google Scholar
• Biondi, F., Myers, D.E., and Avery, C.C., 1994. Geostatistically modeling stem size and increment in an old-growth forest. Canadian Journal of Forest Research, 24, 1354–1368. doi:10.1139/x94-176
   Web of Science ®Google Scholar
• Burton, M., et al., 2010. Systematic design customization of sport wheelchairs using the Taguchi method. Procedia Engineering, 2, 2659–2665. doi:10.1016/j.proeng.2010.04.048
   Google Scholar
• Camps-Valls, G., et al., 2004. Robust support vector method for hyperspectral data classification and knowledge discovery. IEEE Transactions on Geoscience and Remote Sensing, 42, 1530–1542. doi:10.1109/TGRS.2004.827262
   Web of Science ®Google Scholar
• Carreiras, J.M.B., Pereira, J.M.C., and Pereira, J.S., 2006. Estimation of tree canopy cover in evergreen oak woodlands using remote sensing. Forest Ecology and Management, 223, 45–53. doi:10.1016/j.foreco.2005.10.056
   Web of Science ®Google Scholar
• Chang, K.Y., Lin, H.J., and Chen, P.C., 2009. The optimal performance estimation for an unknown PEMFC based on the Taguchi method and a generic numerical PEMFC model. International Journal of Hydrogen Energy, 34, 1990–1998. doi:10.1016/j.ijhydene.2008.11.100
   Web of Science ®Google Scholar
• Chopping, M., et al., 2008. Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer. Remote Sensing of Environment, 112, 2051–2063. doi:10.1016/j.rse.2007.07.024
   Web of Science ®Google Scholar
• Chou, C.S., Ho, C.Y., and Huang, C.I., 2009. The optimum conditions for communication of magnetic particles driven by a rotating magnetic field using the Taguchi method. Advanced Powder Technology, 20, 55–61. doi:10.1016/j.apt.2008.02.002
   Web of Science ®Google Scholar
• Colgan, M.S., et al., 2012. Mapping Savanna tree species at ecosystem scales using support vector machine classification and BRDF correction on airborne hyperspectral and LiDAR data. Remote Sensing, 4, 3462–3480. doi:10.3390/rs4113462
   Web of Science ®Google Scholar
• Dingal, S., et al., 2008. The application of Taguchi’s method in the experimental investigation of the laser sintering process. The International Journal of Advanced Manufacturing Technology, 38, 904–914. doi:10.1007/s00170-007-1154-1
   Web of Science ®Google Scholar
• Djamali, M., et al., 2009. Vegetation history of the SE section of the Zagros Mountains during the last five millennia; a pollen record from the Maharlou Lake, Fars Province, Iran. Vegetation History and Archaeobotany, 18, 123–136. doi:10.1007/s00334-008-0178-2
   Web of Science ®Google Scholar
• Erfanifard, Y., Behnia, N., and Moosavi, V., 2013. Tree crown delineation on VHR aerial imagery with SVM classification technique optimized by Taguchi method: a case study in Zagros woodlands. In: H. Arefi et al., eds. The international archives of the photogrammetry, remote sensing and spatial information sciences, 5–8 October 2013 Tehran. Enschede: ISPRS, 153–158.
   Google Scholar
• Erzurumlu, T. and Ozcelik, B., 2006. Minimization of warpage and sink index in injection molded thermoplastic parts using Taguchi optimization method. Materials and Design, 27, 853–861. doi:10.1016/j.matdes.2005.03.017
   Web of Science ®Google Scholar
• Foody, M.G. and Mathur, A., 2004. Toward intelligent training of supervised image classifications: directing training data acquisition for SVM classification. Remote Sensing of Environment, 93, 107–117. doi:10.1016/j.rse.2004.06.017
   Web of Science ®Google Scholar
• Geerts Greta, A.V.M., Overturf, J.H., and Oberholzer, T.G., 2008. The effect of different reinforcements on the fracture toughness of materials for interim restorations. The Journal of Prosthetic Dentistry, 99, 461–467. doi:10.1016/S0022-3913(08)60108-0
   PubMed Web of Science ®Google Scholar
• Gleason, C.J. and Im, J., 2011. A review of remote sensing of forest biomass and biofuel: options for small-area applications. GIScience & Remote Sensing, 48 (2), 141–170. doi:10.2747/1548-1603.48.2.141
   Web of Science ®Google Scholar
• Hasçalık, A. and Çaydaş, U., 2008. Optimization of turning parameters for surface roughness and tool life based on the Taguchi method. The International Journal of Advanced Manufacturing Technology, 38, 896–903. doi:10.1007/s00170-007-1147-0
   Web of Science ®Google Scholar
• Hsu, C.W., Chang, C.C., and Lin, C.J., 2009. A practical guide to support vector classification (Technical Report). Taiwan: Department of Computer Science, National Taiwan University.
   Google Scholar
• Hsu, W.C. and Yu, T.Y., 2010. E-mail spam filtering based on support vector machines with Taguchi method for parameter selection. Journal of Convergence Information Technology, 5 (8), 78–88. doi:10.4156/jcit.vol5.issue8.9
   Google Scholar
• Huang, M.L., Hung, Y.H., and Lin, E.J., 2011. Effects of SVM parameter optimization based on the parameter design of Taguchi method. International Journal on Artificial Intelligence Tools, 20 (3), 563–575. doi:10.1142/S0218213011000280
   Web of Science ®Google Scholar
• Joachims, T., 1998. Text categorization with support vector machines—learning with many relevant features. In: C. Nedellec and C. Rouveirol, eds. Proceedings of the 10th European conference on machine learning, 21–24 April 1998 Chemnitz. Berlin: Springer, 137–142.
   Google Scholar
• Korhonen, L., et al., 2006. Estimation of forest canopy cover: a comparison of field measurement techniques. Silva Fennica, 40, 577–588.
   Web of Science ®Google Scholar
• Kramer, J.H., 2001. Observation of the earth and its environment: survey of missions and sensors. 4th ed. Berlin: Springer.
   Google Scholar
• Lakshminarayanan, A.K. and Balasubramanian, V., 2008. Process parameters optimization for friction stir welding of RDE-40 aluminium alloy using Taguchi technique. Transactions of Nonferrous Metals Society of China, 18, 548–554. doi:10.1016/S1003-6326(08)60096-5
   Web of Science ®Google Scholar
• Li, L., et al., 2011. Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification. International Journal of Image and Data Fusion, 2 (4), 347–361. doi:10.1080/19479832.2010.546372
   Google Scholar
• Lin, C.L., et al., 2007. Factorial analysis of variables influencing mechanical characteristics of a single tooth implant placed in the maxilla using finite element analysis and the statistics-based Taguchi method. European Journal of Oral Sciences, 115, 408–416. doi:10.1111/j.1600-0722.2007.00473.x
   PubMed Web of Science ®Google Scholar
• Lowman, M.D. and Wittman, W., 1996. Forest canopies: methods, hypotheses, and future directions. Annual Review of Ecology and Systematics, 27, 55–81. doi:10.1146/annurev.ecolsys.27.1.55
   Google Scholar
• Marjanović, M., et al., 2011. Landslide susceptibility assessment using SVM machine learning algorithm. Engineering Geology, 123, 225–234. doi:10.1016/j.enggeo.2011.09.006
   Web of Science ®Google Scholar
• Mather, P., 2004. Computer processing of remotely sensed images – an introduction. 2nd ed. Chichester: John Wiley & Sons.
   Google Scholar
• Mcintyre, B.M., Scholl, M.A., and Sigmon, J.T., 1990. A quantitative description of a deciduous forest canopy using photographic technique. Forest Science, 36, 381–393.
   Web of Science ®Google Scholar
• Melgani, F. and Bruzzone, L., 2004. Classification of hyperspectral remote sensing images with support vector machines. IEEE Transactions on Geoscience and Remote Sensing, 42, 1778–1790. doi:10.1109/TGRS.2004.831865
   Web of Science ®Google Scholar
• Negri, R.G., Dutra, L.V., and Sant’Anna, S.J.S., 2014. An innovative support vector machine based method for contextual image classification. ISPRS Journal of Photogrammetry and Remote Sensing, 87, 241–248. doi:10.1016/j.isprsjprs.2013.11.004
   Web of Science ®Google Scholar
• Oztop, M.H., Sahin, S., and Sumnu, G., 2007. Optimization of microwave frying of potato slices by using Taguchi technique. Journal of Food Engineering, 79, 83–91. doi:10.1016/j.480jfoodeng.2006.01.031
   Web of Science ®Google Scholar
• Paine, D. and Kiser, J.D., 2012. Aerial photography and image interpretation. 3rd ed. New Jersey, NJ: John Wiley & Sons.
   Google Scholar
• Palanikumar, K., Prakash, S., and Shanmugam, K., 2008. Evaluation of delamination in drilling GFRP composites. Materials and Manufacturing Processes, 23, 858–864. doi:10.1080/10426910802385026
   Web of Science ®Google Scholar
• Panta, M., Kim, K., and Joshi, C., 2008. Temporal mapping of deforestation and forest degradation in Nepal: applications to forest conservation. Forest Ecology and Management, 256, 1587–1595. doi:10.1016/j.foreco.2008.07.023
   Web of Science ®Google Scholar
• Pouteau, R., et al., 2012. Support vector machines to map rare and endangered native plants in Pacific islands forests. Ecological Informatics, 9, 37–46. doi:10.1016/j.ecoinf.2012.03.003
   Web of Science ®Google Scholar
• Prasad, P.R.C., et al., 2010. Assessing forest canopy closure in a geospatial medium to address management concerns for tropical islands – Southeast Asia. Environmental Monitoring and Assessment, 160, 541–553. doi:10.1007/s10661-008-0717-4
   PubMed Web of Science ®Google Scholar
• Rautiainen, M., Stenberg, P., and Nilson, T., 2005. Estimating canopy cover in Scots pine stands. Silva Fennica, 39, 137–142.
   Web of Science ®Google Scholar
• Rosa, J.L., et al., 2009. Electro-deposition of copper on titanium wires: Taguchi experimental design approach. Journal of Materials Processing Technology, 209, 1181–1188. doi:10.1016/j.jmatprotec.2008.03.021
   Web of Science ®Google Scholar
• Roy, R.K., 2001. Design of experiments using the Taguchi approach: 16 steps to product and process improvement. 1st ed. New York, NY: John Wiley & Sons.
   Google Scholar
• Sadeghi, S.H., et al., 2012. Soil erosion assessment and prioritization of affecting factors at plot scale using the Taguchi method. Journal of Hydrology, 448, 174–180. doi:10.1016/j.jhydrol.2012.04.038
   Web of Science ®Google Scholar
• Schowengerdt, R.A., 2007. Remote sensing: models and methods for image processing. Massachusetts, MA: Academic Press.
   Google Scholar
• Singaravelu, J., Jeyakumar, D., and Rao, N., 2009. Taguchi’s approach for reliability and safety assessments in the stage separation process of a multistage launch vehicle. Reliability Engineering and System Safety, 94, 1526–1541. doi:10.1016/j.ress.2009.02.017
   Web of Science ®Google Scholar
• Su, L. and Huang, Y., 2009. Support vector machine (SVM) classification: comparison of linkage techniques using a clustering-based method for training data selection. GIScience & Remote Sensing, 46 (4), 411–423. doi:10.2747/1548-1603.46.4.411
   Web of Science ®Google Scholar
• Türkmen, I., Gül, G., and Çelik, C.A., 2008. A Taguchi approach for investigation of some physical properties of concrete produced from mineral admixtures. Building and Environment, 43, 1127–1137. doi:10.1016/j.buildenv.2007.02.005
   Web of Science ®Google Scholar
• Vapnik, V.N., 2000. The nature of statistical learning theory. 2nd ed. New York, NY: Springer.
   Google Scholar
• Vaughn, N.R., Moskal, L.M., and Turnblom, E.C., 2012. Tree species detection accuracies using discrete point LiDAR and airborne waveform LiDAR. Remote Sensing, 4, 377–403. doi:10.3390/rs4020377
   Web of Science ®Google Scholar
• Wang, T.Y. and Huang, C.Y., 2007. Improving forecasting performance by employing the Taguchi method. European Journal of Operational Research, 176, 1052–1065. doi:10.1016/j.ejor.2005.08.020
   Web of Science ®Google Scholar
• Williams, M.S., Patterson, P.L., and Mowrer, H.T., 2003. Comparison of ground sampling methods for estimating canopy cover. Forest Science, 49, 235–246.
   Web of Science ®Google Scholar
• Yang, X., 2011. Parameterizing support vector machines for land cover classification. Photogrammetric Engineering and Remote Sensing, 77, 27–37. doi:10.14358/PERS.77.1.27
   Web of Science ®Google Scholar
• Yang, X.H., et al., 2011. Estimating biophysical parameters of rice with remote sensing data using support vector machines. Science China Life Sciences, 54, 272–281. doi:10.1007/s11427-011-4135-4
   PubMed Web of Science ®Google Scholar
• Zeng, Y., et al., 2008. Change detection of forest crown closure using an inverted geometric-optical model and scaling. In: J. Chen, J. Jiang, and J. Van Genderen, eds. The international archives of the photogrammetry, remote sensing and spatial information sciences, 3–11 July 2008 Beijing. Enschede: ISPRS, 1–6.
   Google Scholar
• Zolfaghari, G.H., et al., 2011. Taguchi optimization approach for Pb(II) and Hg(II) removal from aqueous solutions using modified mesoporous carbon. Journal of Hazardous Materials, 192 (3), 1046–1055. doi:10.1016/j.jhazmat.2011.06.006
   PubMed Web of Science ®Google Scholar