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Research Article

Data fusion approach for eucalyptus trees identification

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Pages 4087-4109 | Received 16 Apr 2020, Accepted 12 Nov 2020, Published online: 02 Mar 2021

References

  • Ali, S. S., P. Dare, and S. D. Jones. 2008. “Fusion of Remotely Sensed Multispectral Imagery and Lidar Data for Forest Structure Assessment at the Tree Level.” ISPRS Proceedings, Beijing, 37. Citeseer: B7.
  • Antrop, M. 2004. “Landscape Change and the Urbanization Process in Europe.” Landscape and Urban Planning 67 (1): 9–26. doi:10.1016/S0169-2046(03)00026-4.
  • Ardeshir Goshtasby, A., and S. Nikolov. 2007. “Guest Editorial: Image Fusion: Advances in the State of the Art.” Information Fusion 8 (2): 114–118. Elsevier Science Publishers BV.
  • Ayhan, E., and O. Kansu. 2012. “Analysis of Image Classification Methods for Remote Sensing.” Experimental Techniques 36 (1): 18–25. John Wiley & Sons, Ltd. doi: 10.1111/j.1747-1567.2011.00719.x.
  • Baumgardner, M. F., F. S. LeRoy, L. L. Biehl, and E. R. Stoner. 1986. “Reflectance Properties of Soils”. In Advances in Agronomy, edited by, N C B T - Advances in Agronomy Brady, Vol. 38, 1–44. Cambridge, Massachusetts, USA: Academic Press. doi: 10.1016/S0065-2113(08)60672-0.
  • Beliakov, G., A. Pradera, and T. Calvo. 2007. Aggregation Functions: A Guide for Practitioners. Vol. 221. Edited by K. Janusz. Berlin Heidelberg New York: Springer.
  • Beliakov, G., and J. Warren. 2001. “Appropriate Choice of Aggregation Operators in Fuzzy Decision Support Systems.” IEEE Transactions on Fuzzy Systems 9 (6): 773–784. doi:10.1109/91.971696.
  • Ben-Dor, E., Y. Inbar, and Y. Chen. 1997. “The Reflectance Spectra of Organic Matter in the Visible Near-Infrared and Short Wave Infrared Region (400–2500 Nm) during a Controlled Decomposition Process.” Remote Sensing of Environment 61 (1): 1–15. doi:10.1016/S0034-4257(96)00120-4.
  • Bleiholder, J., and F. Naumann. 2009. “Data Fusion”. ACM Computing Surveys 41(1). New York, NY, USA: Association for Computing Machinery. doi:10.1145/1456650.1456651.
  • Bourdarias, C., P. Da-Cunha, R. Drai, F. S. Luıs, and R. A. Ribeiro. 2010. “Optimized and Flexible Multi-Criteria Decision Making for Hazard Avoidance.” In Proceedings of the 33rd Annual AAS Rocky Mountain Guidance and Control Conference, Breckenridge, CO, USA, 5–10. Citeseer.
  • CA3-UNINOVA. 2019. “IPSTERS (Ipsentinel Terrestrial Enhanced Recognition System).” https://www.ca3-uninova.org/project_ipsters.
  • Calvo, T., G. Mayor, and R. Mesiar. 2012. Aggregation Operators: New Trends and Applications. Vol. 97. Physica. New York, USA.
  • Câmara, F., J. Oliveira, T. Hormigo, J. Araújo, R. Ribeiro, A. Falcão, M. Gomes, O. Dubois-Matra, and S. Vijendran. 2015. “Data Fusion Strategies for Hazard Detection and Safe Site Selection for Planetary and Small Body Landings.” CEAS Space Journal 7 (2): 271–290. doi:10.1007/s12567-014-0072-y.
  • Campanella, G., and R. A. Ribeiro. 2011. “A Framework for Dynamic Multiple-Criteria Decision Making.” Decision Support Systems 52 (1): 52–60. doi:10.1016/j.dss.2011.05.003.
  • Ceccato, P., S. Flasse, and G. Jean-Marie. 2002. “Designing a Spectral Index to Estimate Vegetation Water Content from Remote Sensing Data: Part 2. Validation and Applications.” Remote Sensing of Environment 82 (2): 198–207. doi:10.1016/S0034-4257(02)00036-6.
  • Chang, N.-B., and K. Bai. 2018. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. 1st ed. Boca Raton, USA: CRC Press.
  • Colditz, R. R. 2015. “An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms.” Remote Sensing. doi:10.3390/rs70809655.
  • Coops, N. C., C. Stone, D. S. Culvenor, L. A. Chisholm, and R. N. Merton. 2003. “Chlorophyll Content in Eucalypt Vegetation at the Leaf and Canopy Scales as Derived from High Resolution Spectral Data.” Tree Physiology 23 (1): 23–31. doi:10.1093/treephys/23.1.23.
  • Dai, X., and S. Khorram. 1999. “Data Fusion Using Artificial Neural Networks: A Case Study on Multitemporal Change Analysis.” Computers, Environment and Urban Systems 23 (1): 19–31. doi:10.1016/S0198-9715(98)00051-9.
  • Datt, B. 1999. “A New Reflectance Index for Remote Sensing of Chlorophyll Content in Higher Plants: Tests Using Eucalyptus Leaves.” Journal of Plant Physiology 154 (1): 30–36. doi:10.1016/S0176-1617(99)80314-9.
  • Davidson, N. C., and C. M. Finlayson. 2007. “Earth Observation for Wetland Inventory, Assessment and Monitoring.” Aquatic Conservation: Marine and Freshwater Ecosystems 17 (3): 219–228. John Wiley & Sons, Ltd. doi: 10.1002/aqc.846.
  • Desclée, B., P. Bogaert, and P. Defourny. 2006. “Forest Change Detection by Statistical Object-Based Method.” Remote Sensing of Environment 102 (1): 1–11. doi:10.1016/j.rse.2006.01.013.
  • Fauvel, M., J. Chanussot, and J. A. Benediktsson. 2006. “Decision Fusion for the Classification of Urban Remote Sensing Images.” IEEE Transactions on Geoscience and Remote Sensing 44 (10): 2828–2838. doi:10.1109/TGRS.2006.876708.
  • Forstmaier, A., A. Shekhar, and J. Chen. 2020. “Mapping of Eucalyptus in Natura 2000 Areas Using Sentinel 2 Imagery and Artificial Neural Networks.” Remote Sensing 12 (14): 4–6. doi:10.3390/rs12142176.
  • Friedl, M. A., and C. E. Brodley. 1997. “Decision Tree Classification of Land Cover from Remotely Sensed Data.” Remote Sensing of Environment 61 (3): 399–409. doi:10.1016/S0034-4257(97)00049-7.
  • Gallego, F. J., and H. J. Stibig. 2013. “Area Estimation from a Sample of Satellite Images: The Impact of Stratification on the Clustering Efficiency.” International Journal of Applied Earth Observation and Geoinformation 22: 139–146. doi:10.1016/j.jag.2012.03.003.
  • Garcia, H. 2017. “A Floresta Em Portugal. Causas E Consequências Da Expansão Do Eucalipto. Caso De Estudo: O Concelho De Torres Vedras.” Doctoral Dissertation - Universidade Nova de Lisboa, Faculdade de Ciências Sociais e Humanas.
  • Ghamisi, P., B. Rasti, N. Yokoya, Q. Wang, B. Hofle, L. Bruzzone, F. Bovolo, et al. 2019. “Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art.” IEEE Geoscience and Remote Sensing Magazine 7 (1): 6–39. doi:10.1109/MGRS.2018.2890023.
  • Gitelson, A. A., Y. J. Kaufman, and M. N. Merzlyak. 1996. “Use of a Green Channel in Remote Sensing of Global Vegetation from EOS-MODIS.” Remote Sensing of Environment 58 (3): 289–298. doi:10.1016/S0034-4257(96)00072-7.
  • Haywood, A., and C. Stone. 2011. “Semi-Automating the Stand Delineation Process in Mapping Natural Eucalypt Forests.” Australian Forestry 74 (1): 13–22. Taylor & Francis. doi: 10.1080/00049158.2011.10676341.
  • Hsu, S.-L., P.-W. Gau, I.-L. Wu, and J.-H. Jeng. 2009. “Region-Based Image Fusion with Artificial Neural Network.” World Academy of Science, Engineering and Technology 53: 156–159.
  • Hyder, A. K., E. Shahbazian, and E. Waltz. 2012. Multisensor Fusion. Vol. 70. Springer-Verlag New Yor.
  • ICNF, Instituto da Conservação da Natureza e das Florestas. 2019. “6th Portuguese Forest Inventory (IFN6).” http://www2.icnf.pt/portal/florestas/ifn/ifn6.
  • Jassbi, J. J., R. A. Ribeiro, L. M. Camarinha-Matos, J. Barata, and M. I. Gomes. 2018. “Continuous Reinforcement Operator Applied to Resilience in Disaster Rescue Networks.” In FUZZ-IEEE WCCI2018 Conference, July 8-13, Rio Janeiro, Brasil, 942–947. doi:10.1109/FUZZ-IEEE.2018.8491482.
  • Jenicka, S. 2018. “Sugeno Fuzzy-Inference-System-Based Land Cover Classification of Remotely Sensed Images.” In Environmental Information Systems: Concepts, Methodologies, Tools, and Applications, 3:1247–1283.IGI Global. doi:10.4018/978-1-5225-7033-2.ch057.
  • Kanellopoulos, I., and G. G. Wilkinson. 1997. “Strategies and Best Practice for Neural Network Image Classification.” International Journal of Remote Sensing 18 (4): 711–725. Taylor & Francis. doi: 10.1080/014311697218719.
  • Klein, L. A. 2004. Sensor and Data Fusion: A Tool for Information Assessment and Decision Making. Vol. 138. Bellingham, Washington USA: SPIE press.
  • Lavreniuk, M. S., S. V. Skakun, A. Ju, B. Shelestov, Y. Ya, S. L. Yanchevskii, D. J. U. Yaschuk, and A. Ì. Kosteckiy. 2016. “Large-Scale Classification of Land Cover Using Retrospective Satellite Data.” Cybernetics and Systems Analysis 52 (1): 127–138. doi:10.1007/s10559-016-9807-4.
  • Le Maire, G., C. Marsden, W. Verhoef, F. J. Ponzoni, D. L. Seen, A. Bégué, J.-L. Stape, and Y. Nouvellon. 2011. “Leaf Area Index Estimation with MODIS Reflectance Time Series and Model Inversion during Full Rotations of Eucalyptus Plantations.” Remote Sensing of Environment 115 (2): 586–599. doi:10.1016/j.rse.2010.10.004.
  • Lee, H., B. Lee, K. Park, and R. Elmasri. 2010. “Fusion Techniques for Reliable Information: A Survey.” International Journal of Digital Content Technology and Its Applications 4 (2): 74–88. Advanced Institute of Convergence IT.
  • Li, Z., and X. Guo. 2015. “Remote Sensing of Terrestrial Non-Photosynthetic Vegetation Using Hyperspectral, Multispectral, SAR, and LiDAR Data.” Progress in Physical Geography: Earth and Environment 40 (2): 276–304. SAGE Publications Ltd. doi: 10.1177/0309133315582005.
  • Liu, H., and L. Jianhua. 2010. “The Study of the Ecological Problems of Eucalyptus Plantation and Sustainable Development in Maoming Xiaoliang.” Journal of Sustainable Development 3 (1): 197–201. doi:10.5539/jsd.v3n1p197.
  • Manyika, J., and H. Durrant-Whyte. 1995. Data Fusion and Sensor Management: A Decentralized Information-Theoretic Approach. New Jersey, USA: Prentice Hall PTR.
  • Mardani, A., M. Nilashi, E. K. Zavadskas, S. R. Awang, H. Zare, and N. M. Jamal. 2018. “Decision Making Methods Based on Fuzzy Aggregation Operators: Three Decades Review from 1986 to 2017.” International Journal of Information Technology & Decision Making 17 (2): 391–466. World Scientific Publishing Co. doi: 10.1142/S021962201830001X.
  • Marinelli, G. C. C., F. Dukatz, and R. Ferrati. 2008. “Artificial Neural Networks and Remote Sensing in the Analysis of the Highly Variable Pampean Shallow Lakes.” Mathematical Biosciences and Engineering 5 (4): 691–711. doi:10.3934/mbe.2008.5.691.
  • Marques-Pereira, R., and R. A. Ribeiro. 2003. “Aggregation with Generalized Mixture Operators Using Weighting Functions.” Fuzzy Sets and Systems 137: 43–58. http://www.uninova.pt/ca3/en/docs/BJ23-FSS2003.pdf.
  • Mas, J. F., and J. J. Flores. 2008. “The Application of Artificial Neural Networks to the Analysis of Remotely Sensed Data.” International Journal of Remote Sensing 29 (3): 617–663. Taylor & Francis. doi: 10.1080/01431160701352154.
  • Mora, A., M. A. Tiago Santos, S. Łukasik, M. N. João Silva, J. António Falcão, M. José Fonseca, A. Rita Ribeiro, et al. 2017. “Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study.” Information 8 (4): 147. doi:10.3390/info8040147.
  • Mora, A. D., A. J. Falcão, L. Miranda, R. A. Ribeiro, and J. M. Fonseca. 2015. “A Fuzzy Multicriteria Approach for Data Fusion.” In Multisensor Data Fusion from Algorithms and Architectural Design to Applications, edited by H. Fourati, 109–126. Boca Raton, USA: CRC Press.
  • Mora, A. D., A. J. Falcão, L. Miranda, R. A. Ribeiro, and J. M. Fonseca. 2016. “A Fuzzy Multicriteria Approach for Data Fusion.” In Multisensor Data Fusion: From Algorithms and Architectural Design to Applications, edited by H. Fourati, 109–126, Taylor and Francis Group. Boca Raton, USA: CRC Press.
  • Olofsson, P., G. M. Foody, S. V. Martin Herold, C. E. W. Stehman, and M. A. Wulder. 2014. “Good Practices for Estimating Area and Assessing Accuracy of Land Change.” Remote Sensing of Environment 148: 42–57. Elsevier Inc. doi:10.1016/j.rse.2014.02.015.
  • Paliwal, M., and U. A. Kumar. 2009. “Neural Networks and Statistical Techniques: A Review of Applications.” Expert Systems with Applications 36 (1): 2–17. Elsevier Ltd. doi: 10.1016/j.eswa.2007.10.005.
  • Piella, G. 2003. “A General Framework for Multiresolution Image Fusion: From Pixels to Regions.” Information Fusion 4 (4): 259–280. doi:10.1016/S1566-2535(03)00046-0.
  • Piiroinen, R., J. Heiskanen, E. Maeda, A. Viinikka, and P. Pellikka. 2017. “Classification of Tree Species in a Diverse African Agroforestry Landscape Using Imaging Spectroscopy and Laser Scanning.” Remote Sensing. doi:10.3390/rs9090875.
  • Reshmidevi, T. V., T. I. Eldho, and R. Jana. 2009. “A GIS-Integrated Fuzzy Rule-Based Inference System for Land Suitability Evaluation in Agricultural Watersheds.” Agricultural Systems 101 (1): 101–109. doi:10.1016/j.agsy.2009.04.001.
  • Ribeiro, R. A., T. C. Pais, and L. F. Simões. 2010. “Benefits of Full-Reinforcement Operators for Spacecraft Target Landing BT - Preferences and Decisions: Models and Applications.” In Preferences and Decisions, edited by, S. Greco, R. A. M. Pereira, M. Squillante, R. R. Yager, and J. Kacprzyk, 353–367. Berlin, Heidelberg: Springer Berlin Heidelberg. doi: 10.1007/978-3-642-15976-3_21
  • Ribeiro, R. A., A. Falcão, A. Mora, and J. M. Fonseca. 2014. “FIF: A Fuzzy Information Fusion Algorithm Based on Multi-Criteria Decision Making.” Knowledge-Based Systems 58 (March 2014): 23–32. doi:10.1016/j.knosys.2013.08.032.
  • Ribeiro, R. A., and P. Ricardo Alberto Marques. 2003. “Generalized Mixture Operators Using Weighting Functions: A Comparative Study with WA and OWA.” European Journal of Operational Research 145 (2): 329–342. doi:10.1016/S0377-2217(02)00538-6.
  • Ross, T. J. 2004. Fuzzy Logic with Engineering. Wiley, Second ed. New Jersey, USA.
  • Rouse, J. W., Jr, R. Hect Haas, J. A. Schell, and D. W. Deering. 1973. Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation – Technical Report.
  • Rudas, I. J., E. Pap, and J. Fodor. 2013. “Information Aggregation in Intelligent Systems: An Application Oriented Approach.” Knowledge-Based Systems 38: 3–13. doi:10.1016/j.knosys.2012.07.025.
  • Santos, T. M. A., R. A. Andre Mora, and M. N. S. Joao. 2016. “Fuzzy-Fusion Approach for Land Cover Classification.” In Proceedings of INES 2016-20th Jubilee IEEE International Conference on Intelligent Engineering Systems, June 30-July 2 2016, Hungary pp. 177–182. IEEE. doi:10.1109/INES.2016.7555116.
  • Schmitt, M., and X. X. Zhu. 2016. “Data Fusion and Remote Sensing: An Ever-Growing Relationship.” IEEE Geoscience and Remote Sensing Magazine 4 (4): 6–23. doi:10.1109/MGRS.2016.2561021.
  • Sinergise Laboratory for geographical information systems, Ltd. 2021. “Sentinel-2 Bands: Band 11.” https://www.sentinel-hub.com/eoproducts/band-b11.
  • Somers, B., J. Verbesselt, E. M. Ampe, N. Sims, W. W. Verstraeten, and P. Coppin. 2010. “Monitoring of Defoliation in Mixed-Aged Eucalyptus Plantations Using Landsat 5-TM.” In EGU General Assembly Conference Abstracts, Vienna, Austria, 02 – 07 May 2010. 12:11449.
  • Sumfleth, K., and R. Duttmann. 2008. “Prediction of Soil Property Distribution in Paddy Soil Landscapes Using Terrain Data and Satellite Information as Indicators.” Ecological Indicators 8 (5): 485–501. doi:10.1016/j.ecolind.2007.05.005.
  • Taylor, J. C., T. R. Brewer, and A. C. Bird. 2000. “Monitoring Landscape Change in the National Parks of England and Wales Using Aerial Photo Interpretation and GIS.” International Journal of Remote Sensing 21 (13–14): 2737–2752. Taylor & Francis. doi: 10.1080/01431160050110269.
  • Torra, V., and Y. Narukawa. 2007. Modeling Decisions - Information Fusion and Aggregation Operators In Cognitive Technologies. Springer, Heidelberg, Germa.
  • Triantaphyllou, E. 2000. “Multi-Criteria Decision Making Methods“ In Multi-Criteria Decision Making Methods: A Comparative Study” by, E. Triantaphyllou, 5–21. Boston, MA: Springer US. doi: 10.1007/978-1-4757-3157-6_2
  • Xu, M., P. Watanachaturaporn, P. K. Varshney, and M. K. Arora. 2005. “Decision Tree Regression for Soft Classification of Remote Sensing Data.” Remote Sensing of Environment 97 (3): 322–336. doi:10.1016/j.rse.2005.05.008.
  • Yager, R. R., and A. Rybalov. 1998. “Full Reinforcement Operators in Aggregation Techniques.” Transactions on Systems, Man, and Cybernetics Part B 28 (6): 757–769. IEEE Press. doi: 10.1109/3477.735386.
  • Yang, S., Q. Feng, T. Liang, B. Liu, W. Zhang, and H. Xie. 2018. “Modeling Grassland Above-Ground Biomass Based on Artificial Neural Network and Remote Sensing in the Three-River Headwaters Region.” Remote Sensing of Environment 204: 448–455. doi:10.1016/j.rse.2017.10.011.
  • Zhang, L., and W. Xiaolin. 2006. “An Edge-Guided Image Interpolation Algorithm via Directional Filtering and Data Fusion.” IEEE Transactions on Image Processing 15 (8): 2226–2238. IEEE.