Research Article
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A Comparison of Image Classification on Synthetic Aperture Radar and Optical Images For Detection of Water Bodies Case of Lake Burdur, Türkiye

Year 2024, Volume: 1 Issue: 7, 47 - 61, 04.02.2024

Ben Forsyth Selin Güzel

Abstract

This study presents a comparison of the classification results of two different datasets using two individual methods. This study utilises both sentinel-1 data and Landsat data, with the first method involving the application of image classification on the sentinel data obtained and comparing the results. Additionally, data fusion as a second method was also performed on the sentinel VV polarisation and VH polarisation with Landsat 8 bands 3,5 and 8 in an attempt to improve the accuracy results of the classification. The classification results of the first method and the second method are compared in this paper. Water detection was the primary goal of this study, leading to these specific choices of Landsat bands.

Keywords

Water body detection climate change image classification synthetic aperture radar optical imagery image fusion

References

  • A. Moreira, P. Prats-Iraola, M. Younis, G. Krieger, I. Hajnsek and K. P. Papathanassiou, "A tutorial on synthetic aperture radar," in IEEE Geoscience and Remote Sensing Magazine, vol. 1, no. 1, pp. 6-43, March 2013, doi: 10.1109/MGRS.2013.2248301.
  • Amazirh, A., Merlin, O., Er-Raki, S., Gao, Q., Rivalland, V., Malbeteau, Y., Khabba, S., & Escorihuela, M. J. (2018). Retrieving surface soil moisture at high spatio-temporal resolution from a synergy between sentinel-1 radar and Landsat Thermal Data: A study case over bare soil. Remote Sensing of Environment, 211, 321–337. https://doi.org/10.1016/j.rse.2018.04.013
  • Bayik, C., Abdikan, S., Ozbulak, G., Alasag, T., Aydemir, S., & Balik Sanli, F. (2018). Exploiting multi- temporal sentinel-1 SAR data for flood extent mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3/W4, 109–113. https://doi.org/10.5194/isprs- archives-xlii-3-w4-109-2018
  • Fu, J., Wang, J., & Li, J. (2007). Study on the automatic extraction of water body from TM image using decision tree algorithm. SPIE Proceedings. https://doi.org/10.1117/12.790602
  • Huang, W.; DeVries, B.; Huang, C.; Lang, M.W.; Jones, J.W.; Creed, I.F.; Carroll, M.L. Automated Extraction of Surface Water Extent from Sentinel-1 Data. Remote Sens. 2018, 10, 797. https://doi.org/10.3390/rs10050797 Krieger, G., Hajnsek, I., Papathanassiou, K. P., Younis, M., & Moreira, A. (2010). Interferometric synthetic aperture radar (SAR) missions employing formation flying. Proceedings of the IEEE, 98(5), 816–843. https://doi.org/10.1109/jproc.2009.2038948
  • L., L., Riordan, K., B., R., Miller, N., & Nowels, M. (2009). Improving wetland characterization with multi-sensor, multi-temporal SAR and optical/infrared data fusion. Advances in Geoscience and Remote Sensing. https://doi.org/10.5772/8327
  • Quang, N. H., Tuan, V. A., Hao, N. T., Hang, L. T., Hung, N. M., Anh, V. L., Phuong, L. T., & Carrie, R. (2019). Synthetic aperture radar and optical remote sensing image fusion for flood monitoring in the Vietnam Lower Mekong basin: A prototype application for the Vietnam Open Data Cube. European Journal of Remote Sensing, 52(1), 599–612. https://doi.org/10.1080/22797254.2019.1698319 Ramsar Sites Information Service. Lake Burdur | Ramsar Sites Information Service. (n.d.). Retrieved December 30, 2022, from https://rsis.ramsar.org/ris/658
  • Santoro, M., Wegmüller, U., Lamarche, C., Bontemps, S., Defourny, P., & Arino, O. (2015). Strengths and weaknesses of multi-year Envisat Asar Backscatter measurements to map permanent open water bodies at global scale. Remote Sensing of Environment, 171, 185–201. https://doi.org/10.1016/j.rse.2015.10.031 Twele, A., Cao, W., Plank, S., Martinis, S., 2016. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing 37, 2990–3004
  • Wang, Y., Ruan, R., She, Y., & Yan, M. (2011). Extraction of water information based on Radarsat Sar and Landsat ETM+. Procedia Environmental Sciences, 10, 2301–2306. https://doi.org/10.1016/j.proenv.2011.09.359
  • Zhang, B., Wdowinski, S., Gann, D., Hong, S.H. and Sah, J., 2022. Spatiotemporal variations of wetland backscatter: The role of water depth and vegetation characteristics in Sentinel-1 dual-polarization SAR observations. Remote Sensing of Environment, 270, p.11

Year 2024, Volume: 1 Issue: 7, 47 - 61, 04.02.2024

Ben Forsyth Selin Güzel

Abstract

References

  • A. Moreira, P. Prats-Iraola, M. Younis, G. Krieger, I. Hajnsek and K. P. Papathanassiou, "A tutorial on synthetic aperture radar," in IEEE Geoscience and Remote Sensing Magazine, vol. 1, no. 1, pp. 6-43, March 2013, doi: 10.1109/MGRS.2013.2248301.
  • Amazirh, A., Merlin, O., Er-Raki, S., Gao, Q., Rivalland, V., Malbeteau, Y., Khabba, S., & Escorihuela, M. J. (2018). Retrieving surface soil moisture at high spatio-temporal resolution from a synergy between sentinel-1 radar and Landsat Thermal Data: A study case over bare soil. Remote Sensing of Environment, 211, 321–337. https://doi.org/10.1016/j.rse.2018.04.013
  • Bayik, C., Abdikan, S., Ozbulak, G., Alasag, T., Aydemir, S., & Balik Sanli, F. (2018). Exploiting multi- temporal sentinel-1 SAR data for flood extent mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-3/W4, 109–113. https://doi.org/10.5194/isprs- archives-xlii-3-w4-109-2018
  • Fu, J., Wang, J., & Li, J. (2007). Study on the automatic extraction of water body from TM image using decision tree algorithm. SPIE Proceedings. https://doi.org/10.1117/12.790602
  • Huang, W.; DeVries, B.; Huang, C.; Lang, M.W.; Jones, J.W.; Creed, I.F.; Carroll, M.L. Automated Extraction of Surface Water Extent from Sentinel-1 Data. Remote Sens. 2018, 10, 797. https://doi.org/10.3390/rs10050797 Krieger, G., Hajnsek, I., Papathanassiou, K. P., Younis, M., & Moreira, A. (2010). Interferometric synthetic aperture radar (SAR) missions employing formation flying. Proceedings of the IEEE, 98(5), 816–843. https://doi.org/10.1109/jproc.2009.2038948
  • L., L., Riordan, K., B., R., Miller, N., & Nowels, M. (2009). Improving wetland characterization with multi-sensor, multi-temporal SAR and optical/infrared data fusion. Advances in Geoscience and Remote Sensing. https://doi.org/10.5772/8327
  • Quang, N. H., Tuan, V. A., Hao, N. T., Hang, L. T., Hung, N. M., Anh, V. L., Phuong, L. T., & Carrie, R. (2019). Synthetic aperture radar and optical remote sensing image fusion for flood monitoring in the Vietnam Lower Mekong basin: A prototype application for the Vietnam Open Data Cube. European Journal of Remote Sensing, 52(1), 599–612. https://doi.org/10.1080/22797254.2019.1698319 Ramsar Sites Information Service. Lake Burdur | Ramsar Sites Information Service. (n.d.). Retrieved December 30, 2022, from https://rsis.ramsar.org/ris/658
  • Santoro, M., Wegmüller, U., Lamarche, C., Bontemps, S., Defourny, P., & Arino, O. (2015). Strengths and weaknesses of multi-year Envisat Asar Backscatter measurements to map permanent open water bodies at global scale. Remote Sensing of Environment, 171, 185–201. https://doi.org/10.1016/j.rse.2015.10.031 Twele, A., Cao, W., Plank, S., Martinis, S., 2016. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing 37, 2990–3004
  • Wang, Y., Ruan, R., She, Y., & Yan, M. (2011). Extraction of water information based on Radarsat Sar and Landsat ETM+. Procedia Environmental Sciences, 10, 2301–2306. https://doi.org/10.1016/j.proenv.2011.09.359
  • Zhang, B., Wdowinski, S., Gann, D., Hong, S.H. and Sah, J., 2022. Spatiotemporal variations of wetland backscatter: The role of water depth and vegetation characteristics in Sentinel-1 dual-polarization SAR observations. Remote Sensing of Environment, 270, p.11
There are 10 citations in total.

Details

Primary Language English
Subjects Climate Change Impacts and Adaptation (Other)
Journal Section Research Articles
Authors

Ben Forsyth

Selin Güzel 0009-0001-2054-8239

Publication Date February 4, 2024
Submission Date December 10, 2023
Acceptance Date January 7, 2024
Published in Issue Year 2024 Volume: 1 Issue: 7

Cite

MLA Forsyth, Ben and Selin Güzel. “A Comparison of Image Classification on Synthetic Aperture Radar and Optical Images For Detection of Water Bodies Case of Lake Burdur, Türkiye”. International Journal of Water Management and Diplomacy, vol. 1, no. 7, 2024, pp. 47-61.
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