Parameter tuning in the support vector machine and random forest and their performances in cross- and same-year crop classification using TerraSAR-X

International Journal of Remote Sensing

Volumn 35, Issue 23, 2014, Pages 7898-7909

  Sonobe, Rei ^a   Tani, Hiroshi ^a   Wang, Xiufeng ^a   Kobayashi, Nobuyuki ^b   Shimamura, Hideki ^c  

^a HOKKAIDO UNIVERSITY   (Japan)

^b Smart Link Hokkaido   (Japan)

^c PASCO CORPORATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL MACHINERY; CROPS; DECISION TREES; SUPPORT VECTOR MACHINES;

AGRICULTURAL DISASTERS; CLASSIFICATION ALGORITHM; CLASSIFICATION AND REGRESSION TREE; CLASSIFICATION MAPS; CROP CLASSIFICATION; OVERALL ACCURACIES; PARAMETER-TUNING; RANDOM FORESTS;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; AGRICULTURAL LAND; ALGORITHM; FOREST COVER; IMAGE CLASSIFICATION; PARAMETERIZATION; TERRASAR-X; VEGETATION MAPPING;

HOKKAIDO; JAPAN;

EID: 84912033001     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2014.978038     Document Type: Article

References (41)

1. Ager, T. P., and P. C. Bresnahan. 2009. “Geometric Precision in Space Radar Imaging: Results from TerraSAR-X.” ASPRS 2009 Annual Conference, Baltimore, MD, March 9–13.
2. Bargiel, D., and S. Herrmann. 2011. “Multi-Temporal Land-Cover Classification of Agricultural Areas in Two European Regions with High Resolution Spotlight TerraSAR-X Data.” Remote Sensing 3 (12): 859–877. doi:10.3390/rs3050859.
3. Beriaux, E., C. Lucau-Danila, E. Auquiere, and P. Defourny. 2013. “Multiyear Independent Validation of the Water Cloud Model for Retrieving Maize Leaf Area Index from SAR Time Series.” International Journal of Remote Sensing 34 (12): 4156–4181. doi:10.1080/01431161.2013.772676.
4. Blaes, X., and P. Defourny. 2003. “Retrieving Crop Parameters Based on Tandem ERS 1/2 Interferometric Coherence Images.” Remote Sensing of Environment 88 (4): 374–385. doi:10.1016/j.rse.2003.08.008.
5. Blaes, X., P. Defourny, U. Wegmuller, A. Della Vecchia, L. Guerriero, and P. Ferrazzoli. 2006. “C-Band Polarimetric Indexes for Maize Monitoring Based on a Validated Radiative Transfer Model.” IEEE Transactions on Geoscience and Remote Sensing 44 (4): 791–800. doi:10.1109/TGRS.2005.860969.
6. Bovolo, F., L. Bruzzone, and L. Carlin. 2010. “A Novel Technique for Subpixel Image Classification Based on Support Vector Machine.” IEEE Transactions on Image Processing 19 (11): 2983–2999. doi:10.1109/TIP.2010.2051632.
7. Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
8. Brisco, B., A. Schmitt, K. Murnaghan, S. Kaya, and A. Roth. 2013. “SAR Polarimetric Change Detection for Flooded Vegetation.” International Journal of Digital Earth 6 (2): 103–114. doi:10.1080/17538947.2011.608813.
9. Choudhury, I., and M. Chakraborty. 2006. “SAR Signature Investigation of Rice Crop Using RADARSAT Data.” International Journal of Remote Sensing 27 (3): 519–534. doi:10.1080/01431160500239172.
10. Congalton, R. G., and K. Green. 2008. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, FL: CRC Press.
11. Cortes, C., and V. Vapnik. 1995. “Support-Vector Networks.” Machine Learning 20 (3): 273–297. doi:10.1007/BF00994018.
12. Costa, M. P. F. 2004. “Use of SAR Satellites for Mapping Zonation of Vegetation Communities in the Amazon Floodplain.” International Journal of Remote Sensing 25 (10): 1817–1835. doi:10.1080/0143116031000116985.
13. Duro, D. C., S. E. Franklin, and M. G. Dubé. 2012. “Multi-Scale Object-Based Image Analysis and Feature Selection of Multi-Sensor Earth Observation Imagery Using Random Forests.” International Journal of Remote Sensing 33 (14): 4502–4526. doi:10.1080/01431161.2011.649864.
14. Fontanelli, G., S. Paloscia, M. Zribi, and A. Chahbi. 2013. “Sensitivity Analysis of X-Band SAR to Wheat and Barley Leaf Area Index in the Merguellil Basin.” Remote Sensing Letters 4 (11): 1107–1116. doi:10.1080/2150704X.2013.842285.
15. Foody, G. M., and A. Mathur. 2004. “A Relative Evaluation of Multiclass Image Classification by Support Vector Machines.” IEEE Transactions on Geoscience and Remote Sensing 42 (6): 1335–1343. doi:10.1109/TGRS.2004.827257.
16. Gislason, P. O., J. A. Benediktsson, and J. R. Sveinsson. 2006. “Random Forests for Land Cover Classification.” Pattern Recognition Letters 27 (4): 294–300. doi:10.1016/j.patrec.2005.08.011.
17. Hartfield, K. A., S. E. Marsh, C. D. Kirk, and Y. Carrière. 2013. “Contemporary and Historical Classification of Crop Types in Arizona.” International Journal of Remote Sensing 34 (17): 6024–6036. doi:10.1080/01431161.2013.793861.
18. Jia, K., Q. Li, Y. Tian, B. Wu, F. Zhang, and J. Meng. 2012. “Crop Classification Using Multi-Configuration SAR Data in the North China Plain.” International Journal of Remote Sensing 33 (1): 170–183. doi:10.1080/01431161.2011.587844.
19. Karatzoglou, A., A. Smola, and K. Hornik. 2013. “Package ‘Kernlab’.” http://cran.r-project.org/web/packages/kernlab/kernlab.pdf
20. Kavzoglu, T., and I. Colkesen. 2013. “An Assessment of the Effectiveness of a Rotation Forest Ensemble for Land-Use and Land-Cover Mapping.” International Journal of Remote Sensing 34 (12): 4224–4241. doi:10.1080/01431161.2013.774099.
21. Kuenzer, C., and K. Knauer. 2013. “Remote Sensing of Rice Crop Areas.” International Journal of Remote Sensing 34 (6): 2101–2139. doi:10.1080/01431161.2012.738946.
22. Liaw, A., and M. Wiener. 2002. “Classification and Regression by Random Forest.” R News 2 (3): 18–22.
23. Lievens, H., and N. E. C. Verhoest. 2011. “On the Retrieval of Soil Moisture in Wheat Fields from L-Band SAR Based on Water Cloud Modeling, the IEM, and Effective Roughness Parameters.” IEEE Geoscience and Remote Sensing Letters 8 (4): 740–744. doi:10.1109/LGRS.2011.2106109.
24. Lizarazo, I. 2008. “SVM-Based Segmentation and Classification of Remotely Sensed Data.” International Journal of Remote Sensing 29 (24): 7277–7283. doi:10.1080/01431160802326081.
25. Mattia, F., T. Le Toan, G. Picard, F. I. Posa, A. D’alessio, C. Notarnicola, A. M. Gatti, M. Rinaldi, G. Satalino, and G. Pasquariello. 2003. “Multitemporal C-Band Radar Measurements on Wheat Fields.” IEEE Transactions on Geoscience and Remote Sensing 41 (7): 1551–1560. doi:10.1109/TGRS.2003.813531.
26. Mishra, N. B., and K. A. Crews. 2014. “Mapping Vegetation Morphology Types in a Dry Savanna Ecosystem: Integrating Hierarchical Object-Based Image Analysis with Random Forest.” International Journal of Remote Sensing 35 (3): 1175–1198. doi:10.1080/01431161.2013.876120.
27. Otsu, N. 1979. “A Threshold Selection Method from Gray-Level Histograms.” IEEE Transactions on Systems, Man, and Cybernetics 9 (1): 62–66. doi:10.1109/TSMC.1979.4310076.
28. Pal, M. 2005. “Random Forest Classifier for Remote Sensing Classification.” International Journal of Remote Sensing 26 (1): 217–222. doi:10.1080/01431160412331269698.
29. Pal, M. 2008. “Ensemble of Support Vector Machines for Land Cover Classification.” International Journal of Remote Sensing 29 (10): 3043–3049. doi:10.1080/01431160802007624.
30. Pontius, R. G., and M. Millones. 2011. “Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment.” International Journal of Remote Sensing 32 (15): 4407–4429. doi:10.1080/01431161.2011.552923.
31. R Core Team. 2013. “A Language and Environment for Statistical Computing.” Vienna: R Foundation for Statistical Computing. Accessed October11. http://www.R-project.org/
32. Rodriguez-Galiano, V. F., M. Chica-Olmo, F. Abarca-Hernandez, P. M. Atkinson, and C. Jeganathan. 2012. “Random Forest Classification of Mediterranean Land Cover Using Multi-Seasonal Imagery and Multi-Seasonal Texture.” Remote Sensing of Environment 121: 93–107. doi:10.1016/j.rse.2011.12.003.
33. Roth, A., M. Huber, and D. Kosmann. 2004. “Geocording of TerraSAR-X Data.” In 20th ISPRS Congress, edited by O. Altan, Istanbul, July12–23, 840–844.
34. Sarker, L. R., and J. E. Nichol. 2011. “Improved Forest Biomass Estimates Using ALOS AVNIR-2 Texture Indices.” Remote Sensing of Environment 115 (4): 968–977. doi:10.1016/j.rse.2010.11.010.
35. Scholkopf, B., K.-K. Sung, C. J. Burges, F. Girosi, P. Niyogi, T. Poggio, and V. Vapnik. 1997. “Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers.” IEEE Transactions on Signal Processing 45 (11): 2758–2765. doi:10.1109/78.650102.
36. Sonobe, R., H. Tani, X. Wang, N. Kobayashi, A. Kimura, and H. Shimamura. 2014a. “Application of Multi-Temporal TerraSAR-X Data to Map Winter Wheat Planted Areas in Hokkaido, Japan.” Japan Agricultural Research Quarterly 48 (4): 465–470. doi:10.6090/jarq.48.465.
37. Sonobe, R., H. Tani, X. Wang, N. Kobayashi, and H. Shimamura. 2014b. “Random Forest Classification of Crop Type Using Multi-Temporal TerraSAR-X Dual-Polarimetric Data.” Remote Sensing Letters 5 (2): 157–164. doi:10.1080/2150704X.2014.889863.
38. Sonobe, R., H. Tani, X. Wang, N. Kobayashi, and H. Shimamura. 2014c. “Winter Wheat Growth Monitoring Using Multi-Temporal TerraSAR-X Dual-Polarimetric Data.” Japan Agricultural Research Quarterly 48 (4): 471–476. doi:10.6090/jarq.48.471.
39. Therneau, T., B. Atkinson, and B. Riple. 2013. “Package ‘Rpart’.” http://cran.r-project.org/web/packages/rpart/rpart.pdf
40. Ulaby, F. T., M. K. Moore, and A. K. Fung. 1986. Microwave Remote Sensing Active and Passive. Norwood, MA: Artech House.
41. Vyas, S. P., M. D. Steven, K. W. Jaggard, and H. Xu. 2003. “Comparison of Sugar Beet Crop Cover Estimates from Radar and Optical Data.” International Journal of Remote Sensing 24 (5): 1071–1082. doi:10.1080/01431160210164262.