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Research Article

A distributed land cover classification of FP and CP SAR observation using MapReduce-based multi-layer perceptron algorithm over the Mumbai mangrove region of India

ORCID Icon, ORCID Icon &
Pages 1510-1532 | Received 19 Oct 2022, Accepted 19 Feb 2023, Published online: 10 Mar 2023

References

  • Ba, J., and R. Caruana. 2014. “Do Deep Nets Really Need to be Deep?“ In Advances in Neural Information Processing Systems, edited by Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence and K.Q. Weinberger, Vol. 27. Curran Associates, Inc. https://proceedings.neurips.cc/paper/2014/file/ea8fcd92d59581717e06eb187f10666d-Paper.pdf
  • Brisco, B., M. Mahdianpari, and F. Mohammadimanesh. 2020. “Hybrid Compact Polarimetric SAR for Environmental Monitoring with the RADARSAT Constellation Mission.” Remote Sensing 12 (20): 3283. doi:10.3390/rs12203283.
  • Chen, J., X. Yan, L. Zheng, C. Wang, and H. Zhang. 2017. “The Analysis of Target Parameters in L Band Full Polarimetric Data.” In 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), Beijing, China, November 13-14, 1–4. IEEE. doi:10.1109/BIGSARDATA.2017.8124937.
  • Cloude, S. R., D. G. Goodenough, and H. Chen. 2011. “Compact Decomposition Theory.” IEEE Geoscience and Remote Sensing Letters 9 (1): 28–32. doi:10.1109/LGRS.2011.2158983.
  • Dabboor, M., S. Banks, L. White, B. Brisco, A. Behnamian, Z. Chen, and K. Murnaghan. 2019. “Comparison of Compact and Fully Polarimetric SAR for Multitemporal Wetland Monitoring.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 (5): 1417–1430. doi:10.1109/JSTARS.2019.2909437.
  • Dey, S., A. Bhattacharya, D. Ratha, D. Mandal, and A. C. Frery. 2020. “Target Characterization and Scattering Power Decomposition for Full and Compact Polarimetric SAR Data.” IEEE Transactions on Geoscience and Remote Sensing 59 (5): 3981–3998. doi:10.1109/TGRS.2020.3010840.
  • Dey, S., A. Bhattacharya, D. Ratha, D. Mandal, H. McNairn, J. M. Lopez-Sanchez, and Y. S. Rao. 2020. “Novel Clustering Schemes for Full and Compact Polarimetric SAR Data: An Application for Rice Phenology Characterization.” Isprs Journal of Photogrammetry and Remote Sensing 169: 135–151. doi:10.1016/j.isprsjprs.2020.09.010.
  • Du, P., A. Samat, P. Gamba, and X. Xie. 2014. “Polarimetric SAR Image Classification by Boosted Multiple-Kernel Extreme Learning Machines with Polarimetric and Spatial Features.” International Journal of Remote Sensing 35 (23): 7978–7990. doi:10.1080/2150704X.2014.978952.
  • Ferrentino, E., F. Nunziata, H. Zhang, and M. Migliaccio. 2020. “On the Ability of PolSar Measurements to Discriminate Among Mangrove Species.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13: 2729–2737. doi:10.1109/JSTARS.2020.2989872.
  • Garg, R., A. Kumar, M. Prateek, K. Pandey, and S. Kumar. 2022. “Land Cover Classification of Spaceborne Multifrequency SAR and Optical Multispectral Data Using Machine Learning.” Advances in Space Research 69 (4): 1726–1742. doi:10.1016/j.asr.2021.06.028.
  • Gopal Singh, P., N. Bordu, D. Singh, H. Yahia, and K. Daoudi. 2021. “Permuted Spectral and Permuted Spectral-Spatial CNN Models for PolSar-Multispectral Data Based Land Cover Classification.” International Journal of Remote Sensing 42 (3): 1096–1120.
  • Guo, S., Y. Tian, L. Yang, S. Chen, and W. Hong. 2015. “Unsupervised Classification Based on H/Alpha Decomposition and Wishart Classifier for Compact Polarimetric SAR.” In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, July 26-31, 1614–1617. IEEE.
  • Hao, S., Y. Zhou, and Y. Guo. 2020. “A Brief Survey on Semantic Segmentation with Deep Learning.” Neurocomputing 406: 302–321. doi:10.1016/j.neucom.2019.11.118.
  • Hou, W., F. Zhao, X. Liu, and R. Wang. 2021. “Comparing Target Detection Performance Between Quad-, Compact- and Dual-Polarimetric SAR Systems.” In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 4763–4766.
  • Hou, W., F. Zhao, X. Liu, H. Zhang, and R. Wang. 2022. “A Unified Framework for Comparing the Classification Performance Between Quad-, Compact-, and Dual-Polarimetric SARs.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–14. doi:10.1109/TGRS.2022.3215431.
  • Iyyappan, M., and S. Shanmugam Ramakrishnan. 2020. “Enhancing Land Cover Classification for Multispectral Images Using Hybrid Polarimetry SAR Data.” International Journal of Remote Sensing 41 (17): 6718–6754. doi:10.1080/01431161.2020.1750730.
  • Kim, H.C., S. Pang, J. Hong-Mo, D. Kim, and S.Y. Bang. 2002. “Support Vector Machine Ensemble with Bagging.” In International Workshop on Support Vector Machines, 397–408. Springer.
  • Kotru, R., M. Shaikh, V. Turkar, S. Simu, S. Banerjee, and G. Singh. 2021. “Semantic Segmentation of PolSar Images for Various Land Cover Features.” In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, July 11–16, 351–354. IEEE.
  • Kumar, A., A. Das, and R. K. Panigrahi. 2017. “RISAT Data Analysis for Land-Cover Classification.” In Proceedings of International Radar Symposium India (IRIS), NIMHANS Convention Centre, Bangalore INDIA, 1–4.
  • Lee, J.S., M. R. Grunes, T. L. Ainsworth, D. Li-Jen, D. L. Schuler, and S. R. Cloude. 1999. “Unsupervised Classification Using Polarimetric Decomposition and the Complex Wishart Classifier.” IEEE Transactions on Geoscience and Remote Sensing 37 (5): 2249–2258. doi:10.1109/36.789621.
  • Li, Y., H. Lin, Y. Zhang, and J. Chen. 2015. “Comparisons of Circular Transmit and Linear Receive Compact Polarimetric SAR Features for Oil Slicks Discrimination.” Journal of Sensors 2015: 1–14. doi:10.1155/2015/631561.
  • Luo, M., L. Zhang, J. Liu, J. Guo, and Q. Zheng. 2017. “Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier.” Neurocomputing 261: 164–170. doi:10.1016/j.neucom.2016.03.112.
  • 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.
  • Mangalam, K., and V. Uday Prabhu. 2019. “Do Deep Neural Networks Learn Shallow Learnable Examples First?”
  • Memon, N., H. Parikh, S. B. Patel, D. Patel, and V. D. Patel. 2021. “Automatic Land Cover Classification of Multi-Resolution Dualpol Data Using Convolutional Neural Network (CNN).” Remote Sensing Applications: Society and Environment 22: 100491. doi:10.1016/j.rsase.2021.100491.
  • Modava, M., and G. Akbarizadeh. 2017. “Coastline Extraction from SAR Images Using Spatial Fuzzy Clustering and the Active Contour Method.” International Journal of Remote Sensing 38 (2): 355–370. doi:10.1080/01431161.2016.1266104.
  • Modava, M., G. Akbarizadeh, and M. Soroosh. 2019a. “Hierarchical Coastline Detection in SAR Images Based on Spectral-Textural Features and Global–Local Information.” IET Radar, Sonar & Navigation 13 (12): 2183–2195. doi:10.1049/iet-rsn.2019.0063.
  • Modava, M., G. Akbarizadeh, and M. Soroosh. 2019b. “Integration of Spectral Histogram and Level Set for Coastline Detection in SAR Images.” IEEE Transactions on Aerospace and Electronic Systems 55 (2): 810–819. doi:10.1109/TAES.2018.2865120.
  • Ohki, M., and M. Shimada. 2018. “Large-Area Land Use and Land Cover Classification with Quad, Compact, and Dual Polarization SAR Data by PALSAR-2.” IEEE Transactions on Geoscience and Remote Sensing 56 (9): 5550–5557. doi:10.1109/TGRS.2018.2819694.
  • Okwuashi, O., C. E. Ndehedehe, D. Nihinlola Olayinka, A. Eyoh, and H. Attai. 2021. “Deep Support Vector Machine for PolSar Image Classification.” International Journal of Remote Sensing 42 (17): 6498–6536. doi:10.1080/01431161.2021.1939910.
  • Parikh, H., S. Patel, and V. Patel. 2020. “Classification of SAR and PolSar Images Using Deep Learning: A Review.” International Journal of Image and Data Fusion 11 (1): 1–32. doi:10.1080/19479832.2019.1655489.
  • Passah, A., S. Nath Sur, B. Paul, and D. Kandar. 2022. “SAR Image Classification: A Comprehensive Study and Analysis.” IEEE Access 10: 20385–20399. doi:10.1109/ACCESS.2022.3151089.
  • Persello, C., J. Dirk Wegner, R. Hansch, D. Tuia, P. Ghamisi, M. Koeva, and G. Camps-Valls. 2022. “Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current Approaches, Open Challenges, and Future Opportunities.” IEEE Geoscience and Remote Sensing Magazine 10 (2): 172–200. doi:10.1109/MGRS.2021.3136100.
  • Qiu, J., W. Qihui, G. Ding, X. Yuhua, and S. Feng. 2016. “A Survey of Machine Learning for Big Data Processing.” EURASIP Journal on Advances in Signal Processing 2016 (1): 67. doi:10.1186/s13634-016-0355-x.
  • Raney, R. K. 2007. “Hybrid-Polarity SAR Architecture.” IEEE Transactions on Geoscience and Remote Sensing 45 (11): 3397–3404. doi:10.1109/TGRS.2007.895883.
  • Raney, R. K. 2019. “Hybrid Dual-Polarization Synthetic Aperture Radar.” Remote Sensing 11 (13): 1521. doi:10.3390/rs11131521.
  • Roy, S., S. Bhattacharya, and S. Narasipur Omkar. 2020. “Alternating Direction Method-Based Endmember Extraction for a Distributed Fraction Cover Mapping of Mineralogy at Jahazpur, India.” Journal of Applied Remote Sensing 14 (4): 044510. doi:10.1117/1.JRS.14.044510.
  • Roy, S., S. Bhattacharya, and S. Narasipur Omkar. 2022. “Automated Large-Scale Mapping of the Jahazpur Mineralised Belt by a MapReduce Model with an Integrated ELM Method.” PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science 90 (2): 191–209. doi:10.1007/s41064-021-00188-3.
  • Roy, S., S. Gupta, and S. N. Omkar. 2017. “Case Study On: Scalability of Preprocessing Procedure of Remote Sensing in Hadoop.” Procedia computer science 108: 1672–1681. doi:10.1016/j.procs.2017.05.042.
  • Salberg, A.B., Ø. Rudjord, and A. H. Schistad Solberg. 2014. “Oil Spill Detection in Hybrid-Polarimetric SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 52 (10): 6521–6533. doi:10.1109/TGRS.2013.2297193.
  • Samrat, A., M. S. Devy, and T. Ganesh. 2021. “Delineating Fragmented Grassland Patches in the Tropical Region Using Multi-Seasonal Synthetic Aperture Radar (SAR) and Optical Satellite Images.” International Journal of Remote Sensing 42 (10): 3938–3954. doi:10.1080/01431161.2021.1881181.
  • Shakya, A., M. Biswas, and M. Pal. 2020. “CNN-Based Fusion and Classification of SAR and Optical Data.” International Journal of Remote Sensing 41 (22): 8839–8861. doi:10.1080/01431161.2020.1783713.
  • Song, Y., Z. Zhang, R. Kaviani Baghbaderani, F. Wang, Q. Ying, C. Stuttsy, and Q. Hairong 2019. “Land Cover Classification for Satellite Images Through 1D CNN.” In 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Amsterdam, Netherlands, September 24-26, 1–5. IEEE. doi:10.1109/WHISPERS.2019.8921180.
  • Stokes, G. G. 1851. “On the Composition and Resolution of Streams of Polarized Light from Different Sources.” Transactions of the Cambridge Philosophical Society 9: 399.
  • Turkar, V., R. Deo, Y. S. Rao, S. Mohan, and A. Das. 2012. “Classification Accuracy of Multi-Frequency and Multi-Polarization SAR Images for Various Land Covers.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5 (3): 936–941. doi:10.1109/JSTARS.2012.2192915.
  • Turkar, V., D. Shaunak, A. Das, S. Shitole, R. Deo, and K. Patnaik. 2020. “The Effect of Hybrid Polarimetric Descriptors on Classification Accuracy of Various Land Cover Types.” In IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, September 26 - October 2, 3884–3887. IEEE.
  • Turkar, V., Y. R. Shaunak De, S. Shitole, A. Bhattacharya, and A. Das. 2013. “Comparative Analysis of Classification Accuracy for RISAT-1 Compact Polarimetric Data for Various Land-Covers.” In 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, Melbourne, Australia, July 21-26, 3586–3589. IEEE.
  • Zhang, X., Y. Zhou, and J. Luo. 2021. “Deep Learning for Processing and Analysis of Remote Sensing Big Data: A Technical Review.” Big Earth Data 6 (4): 1–34. doi:10.1080/20964471.2021.1964879.
  • Zhong, G., X. Ling, and L.N. Wang. 2019. “From Shallow Feature Learning to Deep Learning: Benefits from the Width and Depth of Deep Architectures.” Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery 9 (1): e1255. doi:10.1002/widm.1255.
  • Zhou, Y., H. Wang, X. Feng, and Y.Q. Jin. 2016. “Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks.” IEEE Geoscience and Remote Sensing Letters 13 (12): 1935–1939. doi:10.1109/LGRS.2016.2618840.
  • Zhu, M., H. Yongning, and H. Qingyu. 2019. “A Review of Researches on Deep Learning in Remote Sensing Application.” International Journal of Geosciences 10 (1): 1–11. doi:10.4236/ijg.2019.101001.

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