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Research Article

Improving wetland cover classification using artificial neural networks with ensemble techniques

, , &
Pages 603-623 | Received 13 Jan 2021, Accepted 16 May 2021, Published online: 02 Jun 2021

References

  • Adam, E., O. Mutanga, J. Odindi, and E. M. Abdel-Rahman. 2014. “Land-use/cover Classification in a Heterogeneous Coastal Landscape Using RapidEye Imagery: Evaluating the Performance of Random Forest and Support Vector Machines Classifiers.” International Journal of Remote Sensing 35 (10): 3440–3458. doi:10.1080/01431161.2014.903435.
  • Adam, E., O. Mutanga, and D. Rugege. 2010. “Multispectral and Hyperspectral Remote Sensing for Identification and Mapping of Wetland Vegetation: A Review.” Wetlands Ecology and Management 18 (3): 281–296. doi:10.1007/s11273-009-9169-z.
  • Amani, M., B. Salehi, S. Mahdavi, B. Brisco, and M. Shehata. 2018. “A Multiple Classifier System to Improve Mapping Complex Land Covers: A Case Study of Wetland Classification Using SAR Data in Newfoundland, Canada.” International Journal of Remote Sensing 39 (21): 7370–7383. doi:10.1080/01431161.2018.1468117.
  • Amani, M., B. Salehi, S. Mahdavi, J. Granger, and B. Brisco. 2017. “Wetland Classification in Newfoundland and Labrador Using Multi-source SAR and Optical Data Integration.” GIScience & Remote Sensing 54 (6): 779–796. doi:10.1080/15481603.2017.1331510.
  • Basheer, I. A., and M. N. Hajmeer. 2000. “Artificial Neural Networks: Fundamentals, Computing, Design, and Application.” Journal of Microbiological Methods 43 (1): 3–31. doi:10.1016/S0167-7012(00)00201-3.
  • Bauer, E., and R. Kohavi. 1999. “An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants.” Machine Learning 36 (1/2): 105–139. doi:10.1023/A:1007515423169.
  • Breiman, L. 1996. “Bagging Predictors.” Machine Learning 24 (2): 123–140. doi:10.1007/BF00058655.
  • Breiman, L. 2001. “Random Forest.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
  • Cai, Y., X. Li, M. Zhang, and H. Lin. 2020. “Mapping Wetland Using the Object-based Stacked Generalization Method Based on Multi-temporal Optical and SAR Data.” International Journal of Applied Earth Observation and Geoinformation 88: 92. doi:10.1016/j.jag.2020.102064.
  • Chen, H., Q. Zhu, C. Peng, N. Wu, Y. Wang, X. Fang, Y. Gao, et al. 2013. “The Impacts of Climate Change and Human Activities on Biogeochemical Cycles on the Qinghai-Tibetan Plateau.” Global Change Biology 19 (10): 2940–2955. doi:10.1111/gcb.12277.
  • Chen, W., H. Hong, S. Li, H. Shahabi, B. B. Ahmad, X. Wang, and B. B. Ahmad. 2019. “Flood Susceptibility Modelling Using Novel Hybrid Approach of Reduced-error Pruning Trees with Bagging and Random Subspace Ensembles.” Journal of Hydrology 575: 864–873. doi:10.1016/j.jhydrol.2019.05.089.
  • Chen, Y., P. Dou, and X. Yang. 2017. “Improving Land Use/cover Classification with a Multiple Classifier System Using AdaBoost Integration Technique.” Remote Sensing 9 (10): 10. doi:10.3390/rs9101055.
  • Congalton, R. G., R. G. Oderwald, and R. A. Mead. 1983. “Assessing Landsat Classification Accuracy Using Discrete Multivariate Analysis Statistical Techniques.” Photogrammetric Engineering and Remote Sensing 49 (12): 1671–1678.
  • Cordeiro, C. L. D. O., and D. D. F. Rossetti. 2015. “Mapping Vegetation in a Late Quaternary Landform of the Amazonian Wetlands Using Object-based Image Analysis and Decision Tree Classification.” International Journal of Remote Sensing 36 (13): 3397–3422. doi:10.1080/01431161.2015.1060644.
  • Cui, Q., X. Wang, C. Li, Y. Cai, Q. Liu, and R. Li. 2015. “Ecosystem Service Value Analysis of CO2 Management Based on Land Use Change of Zoige Alpine Peat Wetland, Tibetan Plateau.” Ecological Engineering 76: 158–165. doi:10.1016/j.ecoleng.2014.03.035.
  • Cui, Q., X. Wang, D. Li, and X. Guo. 2012. “An Ecosystem Health Assessment Method Integrating Geochemical Indicators of Soil in Zoige Wetland, Southwest China.” Procedia Environmental Sciences 13: 1527–1534. doi:10.1016/j.proenv.2012.01.145.
  • Dai, L., and C. Liu. 2010. “Multiple Classifier Combination for Land Cover Classification of Remote Sensing Image.” Paper presented at the Proceedings of the 2010 2nd International Conference on Information Science and Engineering (ICISE), Hangzhou, China, 4–6 December, 2010.
  • DeLancey, E. R., J. F. Simms, M. Mahdianpari, B. Brisco, C. Mahoney, and J. Kariyeva. 2019. “Comparing Deep Learning and Shallow Learning for Large-scale Wetland Classification in Alberta, Canada.” Remote Sensing 12 (1): 1. doi:10.3390/rs12010002.
  • Di Vittorio, C. A., and A. P. Georgakakos. 2018. “Land Cover Classification and Wetland Inundation Mapping Using MODIS.” Remote Sensing of Environment 204: 1–17. doi:10.1016/j.rse.2017.11.001.
  • Dietterich, T. G. 2000. “An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization.” Machine Learning 40 (2): 139–157. doi:10.1023/A:1007607513941.
  • Dronova, I. 2015. “Object-based Image Analysis in Wetland Research: A Review.” Remote Sensing 7 (5): 6380–6413. doi:10.3390/rs70506380.
  • Dubeau, P., D. King, D. Unbushe, and L.-M. Rebelo. 2017. “Mapping the Dabus Wetlands, Ethiopia, Using Random Forest Classification of Landsat, PALSAR and Topographic Data.” Remote Sensing 9 (10): 10. doi:10.3390/rs9101056.
  • Duro, D. C., S. E. Franklin, and M. G. Dubé. 2012. “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 Sensing of Environment 118: 259–272. doi:10.1016/j.rse.2011.11.020.
  • Eeti, L. N., and K. M. Buddhiraju. 2019. “Two Hidden Layer Neural Network-based Rotation Forest Ensemble for Hyperspectral Image Classification.” Geocarto International 1: 1–18. doi:10.1080/10106049.2019.1678680.
  • Fariba, M., S. Bahram, M. Masoud, M. Mahdi, and B. Brian. 2018. “An Efficient Feature Optimization for Wetland Mapping by Synergistic Use of Sar Intensity, Interferometry, and Polarimetry Data.” International Journal of Applied Earth Observation & Geoinformation 73: 450–462. doi:10.1016/j.jag.2018.06.005.
  • Feng, M., J. O. Sexton, S. Channan, and J. R. Townshend. 2015. “A Global, High-resolution (30-m) Inland Water Body Dataset for 2000: First Results of A Topographic–spectral Classification Algorithm.” International Journal of Digital Earth 9 (2): 113–133. doi:10.1080/17538947.2015.1026420.
  • Fluet-Chouinard, E., B. Lehner, L.-M. Rebelo, F. Papa, and S. K. Hamilton. 2015. “Development of a Global Inundation Map at High Spatial Resolution from Topographic Downscaling of Coarse-scale Remote Sensing Data.” Remote Sensing of Environment 158: 348–361. doi:10.1016/j.rse.2014.10.015.
  • Franklin, S., and O. Ahmed. 2017. “Object-based Wetland Characterization Using Radarsat-2 Quad-Polarimetric SAR Data, Landsat-8 OLI Imagery, and Airborne Lidar-derived Geomorphometric Variables.” Photogrammetric Engineering & Remote Sensing 83 (1): 27–36. doi:10.14358/pers.83.1.27.
  • Freund, Y., and R. E. Schapire. 1996. “Experiments with a New Boosting Algorithm.” In Thirteenth International Conference on ML, 148–156. Bari, Italy.
  • Gallant, A. 2015. “The Challenges of Remote Monitoring of Wetlands.” Remote Sensing 7 (8): 10938–10950. doi:10.3390/rs70810938.
  • Ghimire, B., J. Rogan, V. R. Galiano, P. Panday, and N. Neeti. 2013. “An Evaluation of Bagging, Boosting, and Random Forests for Land-cover Classification in Cape Cod, Massachusetts, USA.” GIScience & Remote Sensing 49 (5): 623–643. doi:10.2747/1548-1603.49.5.623.
  • Glanz, H., L. Carvalho, D. Sulla-Menashe, and M. A. Friedl. 2014. “A Parametric Model for Classifying Land Cover and Evaluating Training Data Based on Multi-temporal Remote Sensing Data.” ISPRS Journal of Photogrammetry and Remote Sensing 97: 219–228. doi:10.1016/j.isprsjprs.2014.09.004.
  • Gorham, E. 1991. “Northern Peatlands: Role in the Carbon Cycle and Probable Responses to Climatic Warming.” Ecological Applications 1 (2): 182–195. doi:10.2307/1941811.
  • Gosselin, G., R. Touzi, and F. Cavayas. 2014. “Polarimetric Radarsat-2 Wetland Classification Using the Touzi Decomposition: Case of the Lac Saint-Pierre Ramsar Wetland.” Canadian Journal of Remote Sensing 39 (6): 491–506. doi:10.5589/m14-002.
  • Halmy, M. W. A., and P. E. Gessler. 2015. “The Application of Ensemble Techniques for Land-cover Classification in Arid Lands.” International Journal of Remote Sensing 36 (22): 5613–5636. doi:10.1080/01431161.2015.1103915.
  • Haralick, R. M., K. Shanmugam, and K. Shanmugam. 1973. “Textural Features for Image Classification.” IEEE Transactions on Systems, Man, and Cybernetics 3 (6): 610–621. doi:10.1109/TSMC.1973.4309314.
  • Hong, S.-H., H.-O. Kim, S. Wdowinski, and E. Feliciano. 2015. “Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types.” Remote Sensing 7 (7): 8563–8585. doi:10.3390/rs70708563.
  • Hou, M., J. Ge, J. Gao, B. Meng, Y. Li, J. Yin, J. Liu, Q. Feng, and T. Liang. 2020. “Ecological Risk Assessment and Impact Factor Analysis of Alpine Wetland Ecosystem Based on LUCC and Boosted Regression Tree on the Zoige Plateau, China.” Remote Sensing 12 (3): 3. doi:10.3390/rs12030368.
  • Hu, X., H. Mei, H. Zhang, Y. Li, and M. Li. 2021. “Performance Evaluation of Ensemble Learning Techniques for Landslide Susceptibility Mapping at the Jinping County, Southwest China.” Natural Hazards 105 (2): 1663–1689. doi:10.1007/s11069-020-04371-4.
  • Hu, X., H. Zhang, H. Mei, D. Xiao, Y. Li, and M. Li. 2020. “Landslide Susceptibility Mapping Using the Stacking Ensemble Machine Learning Method in Lushui, Southwest China.” Applied Sciences 10 (11): 4016–4037. doi:10.3390/app10114016.
  • Jozdani, S. E., B. A. Johnson, and D. Chen. 2019. “Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-based Urban Land Use/land Cover Classification.” Remote Sensing 11 (14): 14. doi:10.3390/rs11141713.
  • Kesikoglu, M. H., U. H. Atasever, F. Dadaser-Celik, and C. Ozkan. 2019. “Performance of ANN, SVM and MLH Techniques for Land Use/cover Change Detection at Sultan Marshes Wetland, Turkey.” Water Science and Technology 80 (3): 466–477. doi:10.2166/wst.2019.290.
  • Kumar, L., and P. Sinha. 2014. “Mapping Salt-marsh Land-cover Vegetation Using High-spatial and Hyperspectral Satellite Data to Assist Wetland Inventory.” GIScience & Remote Sensing 51 (5): 483–497. doi:10.1080/15481603.2014.947838.
  • Lagos, N. A., P. Paolini, E. Jaramillo, C. Lovengreen, C. Duarte, and H. Contreras. 2008. “Environmental Processes, Water Quality Degradation, and Decline of Waterbird Populations in the Rio Cruces Wetland, Chile.” Wetlands 28 (4): 938–950. doi:10.1672/07-119.1.
  • LeCun, Y., B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel. 1989. “Backpropagation Applied to Handwritten Zip Code Recognition.” Neural Computation 1 (4): 541–551. doi:10.1162/neco.1989.1.4.541.
  • Lei, G., A. Li, J. Bian, H. Yan, X. Nan, Z. Zhang, and X. Nan. 2020. “Oic-mce: A Practical Land Cover Mapping Approach for Limited Samples Based on Multiple Classifier Ensemble and Iterative Classification.” Remote Sensing 12 (6): 987–1008. doi:10.3390/rs12060987.
  • Li, H., A. B. Nicotra, D. Xu, and G. Du. 2015. “Habitat-specific Responses of Leaf Traits to Soil Water Conditions in Species from a Novel Alpine Swamp Meadow Community.” Conservation Physiology 3 (1): 1–8. doi:10.1093/conphys/cov046.
  • Liu, G. S., and G. X. Wang. 2018. “Influence of Short-term Experimental Warming on Heat-water Processes of the Active Layer in a Swamp Meadow Ecosystem of the Qinghai-Tibet Plateau.” Sciences in Cold and Arid Regions 8 (2): 125–134. doi:10.3724/SP.J.1226.2016.00125.
  • Ma, M., X. Zhou, and G. Du. 2011. “Soil Seed Bank Dynamics in Alpine Wetland Succession on the Tibetan Plateau.” Plant and Soil 346 (1–2): 19–28. doi:10.1007/s11104-011-0790-2.
  • Mahdavi, S., B. Salehi, J. Granger, M. Amani, B. Brisco, and W. Huang. 2017. “Remote Sensing for Wetland Classification: A Comprehensive Review.” GIScience & Remote Sensing 55 (5): 623–658. doi:10.1080/15481603.2017.1419602.
  • Mahdianpari, M., B. Salehi, F. Mohammadimanesh, S. Homayouni, and E. Gill. 2018a. “The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 M Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform.” Remote Sensing 11 (1): 1. doi:10.3390/rs11010043.
  • Mahdianpari, M., B. Salehi, F. Mohammadimanesh, and M. Motagh. 2017. “Random Forest Wetland Classification Using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 130: 13–31. doi:10.1016/j.isprsjprs.2017.05.010.
  • Mahdianpari, M., B. Salehi, M. Rezaee, F. Mohammadimanesh, and Y. Zhang. 2018b. “Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery.” Remote Sensing 10 (7): 7. doi:10.3390/rs10071119.
  • Mohammadimanesh, F., B. Salehi, M. Mahdianpari, M. Motagh, and B. Brisco. 2018. “An Efficient Feature Optimization for Wetland Mapping by Synergistic Use of SAR Intensity, Interferometry, and Polarimetry Data.” International Journal of Applied Earth Observation and Geoinformation 73: 450–462. doi:10.1016/j.jag.2018.06.005.
  • Niu, B., Y. He, X. Zhang, G. Fu, P. Shi, M. Du, Y. Zhang, and N. Zong. 2016. “Tower-based Validation and Improvement of MODIS Gross Primary Production in an Alpine Swamp Meadow on the Tibetan Plateau.” Remote Sensing 8 (7): 7. doi:10.3390/rs8070592.
  • Niu, K., P. Choler, F. De Bello, N. Mirotchnick, G. Du, and S. Sun. 2014. “Fertilization Decreases Species Diversity but Increases Functional Diversity: A Three-year Experiment in A Tibetan Alpine Meadow.” Agriculture, Ecosystems & Environment 182: 106–112. doi:10.1016/j.agee.2013.07.015.
  • Nogueira, K., O. A. B. Penatti, and J. A. D. Santos. 2017. “Towards Better Exploiting Convolutional Neural Networks for Remote Sensing Scene Classification.” Pattern Recognition 61: 539–556. doi:10.1016/j.patcog.2016.07.001.
  • Palubinskas, G. 2016. “Model-based View at Multi-resolution Image Fusion Methods and Quality Assessment Measures.” International Journal of Image & Data Fusion 7 (3): 203–218. doi:10.1080/19479832.2016.1180326.
  • Poiani, K. A., W. Carter Johnson, G. A. Swanson, and T. C. Winter. 1996. “Climate Change and Northern Prairie Wetlands: Simulations of Long-term Dynamics.” Limnology and Oceanography 41 (5): 871–881. doi:10.4319/lo.1996.41.5.0871.
  • Polikar, R. 2006. “Ensemble Based Systems in Decision Making.” IEEE Circuits and Systems Magazine 6 (3): 21–45. doi:10.1109/MCAS.2006.1688199.
  • Pouliot, D., R. Latifovic, J. Pasher, and J. Duffe. 2019. “Assessment of Convolution Neural Networks for Wetland Mapping with Landsat in the Central Canadian Boreal Forest Region.” Remote Sensing 11 (7): 7. doi:10.3390/rs11070772.
  • Rezaee, M., M. Mahdianpari, Y. Zhang, and B. Salehi. 2018. “Deep Convolutional Neural Network for Complex Wetland Classification Using Optical Remote Sensing Imagery.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (9): 3030–3039. doi:10.1109/JSTARS.2018.2846178.
  • Rodríguez, J. J., L. I. Kuncheva, and C. J. Alonso. 2006. “Rotation Forest: A New Classifier Ensemble Method.” IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (10): 1619–1630. doi:10.1109/TPAMI.2006.211.
  • Rodriguez-Galiano, V. F., B. Ghimire, J. Rogan, M. Chica-Olmo, and J. P. Rigol-Sanchez. 2012. “An Assessment of the Effectiveness of a Random Forest Classifier for Land-cover Classification.” Isprs Journal of Photogrammetry & Remote Sensing 67: 93–104. doi:10.1016/j.isprsjprs.2011.11.002.
  • Schapire, R. E., Y. Freund, P. Barlett, and W. S. Lee. 1997. “Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods.” Paper presented at the Proceedings of the Fourteenth International Conference on Machine Learning, Nashville, Tennessee, USA, July 8-12, 1997.
  • Simonyan, K., and Z. Andrew. 2014. “Very Deep Convolutional Networks for Large-scale Image Recognition.” arXiv Preprint arXiv 1409 (1556): 1–14.
  • Steven, D. D., and M. M. Toner. 2004. “Vegetation of Upper Coastal Plain Depression Wetlands: Environmental Templates and Wetland Dynamics within a Landscape Framework.” Wetlands 24 (1): 23–42. doi:10.1672/0277-5212(2004)024[0023:VOUCPD]2.0.CO;2.
  • Süha, B., K. T. Yilmaz, and C. Zkan. 2004. “Mapping and Monitoring of Coastal Wetlands of Çukurova Delta in the Eastern Mediterranean Region.” Biodiversity & Conservation 13 (3): 615–633. doi:10.1023/B:BIOC.0000009493.34669.ec.
  • Szantoi, Z., F. J. Escobedo, A. Abd-Elrahman, L. Pearlstine, B. Dewitt, and S. Smith. 2015. “Classifying Spatially Heterogeneous Wetland Communities Using Machine Learning Algorithms and Spectral and Textural Features.” Environmental Monitoring and Assessment 187 (5): 262. doi:10.1007/s10661-015-4426-5.
  • Thomas, C., T. Ranchin, L. Wald, and J. Chanussot. 2008. “Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics.” IEEE Transactions on Geoscience and Remote Sensing 46 (5): 1301–1312. doi:10.1109/TGRS.2007.912448.
  • Thomas, C. D., A. Cameron, R. E. Green, M. Bakkenes, L. J. Beaumont, Y. C. Collingham, and B. F. N. Erasmus. 2004. “Extinction Risk from Climate Change.” Nature 427 (6970): 145–148. doi:10.1038/nature02121.
  • Wang, G., J. Hao, J. Ma, and H. Jiang. 2011. “A Comparative Assessment of Ensemble Learning for Credit Scoring.” Expert Systems with Applications 38 (1): 223–230. doi:10.1016/j.eswa.2010.06.048.
  • Wang, X., X. Gao, Y. Zhang, X. Fei, Z. Chen, J. Wang, Y. Zhang, X. Lu, and H. Zhao. 2019. “Land-cover Classification of Coastal Wetlands Using the RF Algorithm for Worldview-2 and Landsat 8 Images.” Remote Sensing 11: 16. doi:10.3390/rs11161927.
  • Wang, Y., and Z. Wang. 2019. “A Survey of Recent Work on Fine-grained Image Classification Techniques.” Journal of Visual Communication and Image Representation 59: 210–214. doi:10.1016/j.jvcir.2018.12.049.
  • Wang, Y. L., X. Wang, Q. Y. Zheng, C. H. Li, and X. J. Guo. 2012. “A Comparative Study on Hourly Real Evapotranspiration and Potential Evapotranspiration during Different Vegetation Growth Stages in the Zoige Wetland.” Procedia Environmental Sciences 13: 1585–1594. doi:10.1016/j.proenv.2012.01.150.
  • Warner, B., and C. Rubec. 1997. The Canadian Wetland Classification System. Waterloo, ON, Canada: Wetlands Research Centre, University of Waterloo.
  • Webb, G. I. 2000. “MultiBoosting: A Technique for Combining Boosting and Wagging.” Machine Learning 40 (2): 159–196. doi:10.1023/A:1007659514849.
  • Wen, L., and M. Hughes. 2020. “Coastal Wetland Mapping Using Ensemble Learning Algorithms: A Comparative Study of Bagging, Boosting and Stacking Techniques.” Remote Sensing 12 (10): 10. doi:10.3390/rs12101683.
  • Zhang, C., P. A. Harrison, X. Pan, H. Li, I. Sargent, and P. M. Atkinson. 2020. “Scale Sequence Joint Deep Learning (SS-JDL) for Land Use and Land Cover Classification.” Remote Sensing of Environment 237. doi:10.1016/j.rse.2019.111593.
  • Zhang, S., C. Li, S. Qiu, C. Gao, F. Zhang, Z. Du, and R. Liu. 2019. “EMMCNN: An ETPS-Based Multi-scale and Multi-feature Method Using CNN for High Spatial Resolution Image Land-cover Classification.” Remote Sensing 12 (1): 1. doi:10.3390/rs12010066.
  • Zhang, Y., C. Wang, W. Bai, Z. Wang, Y. Tu, and D. G. Yangjaen. 2010. “Alpine Wetlands in the Lhasa River Basin, China.” Journal of Geographical Sciences 20 (3): 375–388. doi:10.1007/s11442-010-0375-7.
  • Zhao, L., J. Li, S. Xu, H. Zhou, Y. Li, S. Gu, and X. Zhao. 2010. “Seasonal Variations in Carbon Dioxide Exchange in an Alpine Wetland Meadow on the Qinghai-Tibetan Plateau.” Biogeosciences 7 (4): 1207–1221. doi:10.5194/bg-7-1207-2010.
  • Zhao, Q., and W. Song. 2010. “Remote Sensing Image Classification Based on Multiple Classifiers Fusion.” Paper presented at the Proceedings of the 2010 3rd International Congress on Image and Signal Processing (CISP), Yantai, China, 16–18 October, 2010.
  • Zhao, X. M., L. R. Gao, Z. C. Chen, B. Zhang, W. Z. Liao, and X. Yang. 2019. “An Entropy and MRF Model-based CNN for Large-scale Landsat Image Classification.” IEEE Geoscience and Remote Sensing Letters 16 (7): 1145–1149. doi:10.1109/LGRS.2019.2890996.
  • Zhou, Z. 2009. “Ensemble Learning.” Encyclopedia of Biometrics 1: 411–416.
  • Zhu, L., C. Zhang, C. Zhang, X. Zhou, J. Wang, and X. Wang. 2018. “Application of Multiboost-KELM Algorithm to Alleviate the Collinearity of Log Curves for Evaluating the Abundance of Organic Matter in Marine Mud Shale Reservoirs: A Case Study in Sichuan Basin, China.” Acta Geophysica 66 (5): 983–1000. doi:10.1007/s11600-018-0180-8.

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