PIER M
 
Progress In Electromagnetics Research M
ISSN: 1937-8726
Home | Search | Notification | Authors | Submission | PIERS Home | EM Academy
Home > Vol. 61 > pp. 29-41

C-BAND DUAL-POLARIZATION SYNTHETIC APERTURE RADAR APPLICATION FOR PEAT DEPTH CLASSIFICATION: A CASE STUDY IN SIAK REGENCY, RIAU PROVINCE, INDONESIA

By D. A. Novresiandi and R. Nagasawa

Full Article PDF (848 KB)

Abstract:
Knowledge of peat depth distribution is vitally important for accurately estimating carbon stock within tropical peatlands. These estimates aid in understanding the role of tropical peatlands in global environmental change processes. This study evaluates the potential of C-band dual-polarization synthetic aperture radar (SAR) data for peat depth classification on oil palm plantations in Siak Regency, Riau Province, Indonesia. Specifically, features derived after the ground-range radar cross section (sigma-naught or sigma0) and slant-range perpendicular radar cross section (gamma-naught or γ0) for both polarization channels of C-band Sentinel-1 data were compared and evaluated on monthly basis, during 2015, for discriminating peat depth classes using the decision tree classifier. Overall, γ0 features yielded a higher value of distance factors (DF) for peat depth classes, for both polarization channels, than those produced by the sigma0, indicating a better performance in discriminating peat depth classes. Moreover, the seasonal variation of rainfall intensity was discovered to be influencing feature selection for peat depth classification. Thus, the combination of γ0 features derived in the much rain months was selected for separating the shallow- and medium-peat classes, whereas those derived in the less rain months was selected for discriminating the deep- and very deep-peat classes. In addition, the developed methodology gave the best accuracy for the very deep-peat class, with 76% and 67.86%, producer's accuracy (PA) and user's accuracy (UA), respectively, followed by the shallow-peat class that yielded a PA of 64% and UA of 80%. Subsequently, the deep-peat class produced a PA of 58% and UA of 59.18%, whereas the medium-peat class yielded the lowest PA and UA, of 54% and 49.09%, respectively. This study showed that the C-band dual-polarization SAR data have potential for classifying peat depth classes, particularly on oil palm plantations, and might serve as an efficient tool in peat depth classification used for sustainable management of tropical peatlands.

Citation:
D. A. Novresiandi and R. Nagasawa, "C-Band Dual-Polarization Synthetic Aperture Radar Application for Peat Depth Classification: a Case Study in Siak Regency, Riau Province, Indonesia," Progress In Electromagnetics Research M, Vol. 61, 29-41, 2017.
doi:10.2528/PIERM17062903

References:
1. Osaki, M., D. Nursyamsi, M. Noor, Wahyunto, and H. Segah, "Peatland in Indonesia," Tropical Peatland Ecosystems, M. Osaki and N. Tsuji (eds)., 49-58, Springer, Tokyo, Japan, 2016.

2. Miettinen, J., A. Hooijer, R. Vernimmen, S. C. Liew, and S. E. Page, "From carbon sink to carbon source: Extensive peat oxidation in insular Southeast Asia since 1990," Environmental Research Letters, Vol. 12, No. 024014, 1-10, 2017.

3. Hirano, T., S. Sundari, and H. Yamada, "CO2 balance of tropical peat ecosystems," Tropical Peatland Ecosystems, M. Osaki and N. Tsuji (eds.), 329-338, Springer, Tokyo, Japan, 2016.

4. Shimada, S., H. Takahashi, and M. Osaki, "Carbon stock estimate," Tropical Peatland Ecosystems, M. Osaki and N. Tsuji (eds.), 455-467, Springer, Tokyo, Japan, 2016.

5. Agus, F., K. Hairiah, and A. Mulyani, Measuring Carbon Stock in Peat Soils: Practical Guidelines, World Agroforestry Centre (ICRAF) Southeast Asia Regional Program and Indonesian Centre for Agricultural Land Resources Research and Development, Bogor, Indonesia, 2011.

6. Jaenicke, J., J. O. Rieley, C. Mott, P. Kimman, and F. Siegert, "Determination of the amount of carbon stored in Indonesian peatlands," Geoderma, Vol. 147, 151-158, 2008.
doi:10.1016/j.geoderma.2008.08.008

7. Lawson, I. T., T. J. Kelly, P. Aplin, A. Boom, G. Dargie, F. C. H. Draper, P. N. Z. B. P. Hassan, J. Hoyos-Santillan, J. Kaduk, D. Large, W. Murphy, S. E. Page, K. H. Roucoux, S. Sjögersten, K. Tansey, M. Waldram, B. M. M. Wedeux, and J. Wheeler, "Improving estimates of tropical peatland area, carbon storage, and greenhouse gas fluxes," Wetlands Ecology Management, Vol. 23, 327-346, 2015.
doi:10.1007/s11273-014-9402-2

8. Kuntz, S., "Potential of spaceborne SAR for monitoring the tropical environments," Tropical Ecology, Vol. 51, No. 1, 3-10, 2010.

9. Wijaya, A., P. R. Marpu, and R. Gloaguen, "Discrimination of peatlands in tropical swamp forests using dual-polarimetric SAR and Landsat ETM data," International Journal of Image Data Fusion, Vol. 1, No. 3, 257-270, 2010.
doi:10.1080/19479832.2010.495323

10. Hoekman, D. H., M. A. M. Vissers, and N. Wielaard, "PALSAR wide-area mapping of borneo: Methodology and map validation," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 3, No. 4, 605-617, 2010.
doi:10.1109/JSTARS.2010.2070059

11. Antropov, O., Y. Rauste, J. Praks, M. Hallikainen, and T. Häme, "Peatland delineation under forest canopy with polsar data using model based decomposition technique," Proceeding IEEE International Geoscience and Remote Sensing Symposium, 4918-4921, 2012.

12. Antropov, O., Y. Rauste, H. Astola, J. Praks, T. Häme, and M. T. Hallikainen, "Land cover and soil type mapping from spaceborne PolSAR data at L-band with probabilistic neural network," IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, No. 9, 5256-5270, 2014.
doi:10.1109/TGRS.2013.2287712

13. Watanabe, M., K. Kushida, and C. Yonezawa, "PALSAR full-polarimetric observation for peatland," Asian Journal of Geoinformatics, Vol. 11, No. 3, 2011.

14. Dargie, G. C., S. L. Lewis, I. T. Lawson, E. T. A.Mitchard, S. E. Page, Y. E. Bocko, and S. A. Ifo, "Age, extent and carbon storage of the central Congo Basin peatland complex," Nature, Vol. 542, No. 2, 86-90, 2017.
doi:10.1038/nature21048

15. Ritung, S., Wahyunto, and K. Nugroho, "Karakteristik dan sebaran lahan gambut di Sumatera, Kalimantan dan Papua," Pengelolaan Lahan Gambut Berkelanjutan, E. Husen, M. Anda, M. Noor, H. S. Mamat, Maswar, A. Fahmi, and Y. Sulaiman (eds.), BBSDLP, Bogor, Indonesia, 2012.

16. Sabiham, S. and S. Kartawisastra, "Peatland management for oil palm development in indonesia," Indonesian Journal of Land Resources, Vol. 6, No. 2, 55-66, 2012.

17. Irawan, S. and L. Tacconi, Intergovernmental Fiscal Transfer, Forest Conservation and Climate Change, Edward Elgar, Cheltenham, UK, 2016.
doi:10.4337/9781784716608

18. Englhart, S., M. Staengel, and F. Siegert, "Estimation of fire affected areas and carbon emissions on the basis of Sentinel-1," Proceedings of the 15th International Peat Congress 2016: Poster Presentations, 370-374, Kuching, Sarawak, Malaysia, 2016.

19. Dimov, D., J. Kuhn, and C. Conrad, "Assessment of cropping system diversity in the Fergana Valley through image fusion of Landsat 8 and Sentinel-1," ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. III-7, 173-180, 2016.
doi:10.5194/isprsannals-III-7-173-2016

20. Huffman, G. J., R. F. Adler, D. T. Bolvin, and E. J. Nelkin, "The TRMM Multi-satellite Precipitation Analysis (TMPA)," Satellite Rainfall Applications for Surface Hydrology, F. Hossain and M. Gebremichael (eds.), 3-22, Springer Verlag, 2010.

21. Luis, V., J. Lu, M. Foumelis, and M. Engdahl, "ESA’s multi-mission Sentinel-1 Toolbox," Proceedings of the 19th EGU General Assembly, 19398, Vienna, Austria, 2017.

22. Shimada, M., "Ortho-rectification and slope correction of SAR data using DEM and its accuracy evaluation," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 3, No. 3, 657-671, 2010.
doi:10.1109/JSTARS.2010.2072984

23. El-Darymli, K., P. McGuire, E. Gill, D. Power, and C. Moloney, "Understanding the significance of radiometric calibration for synthetic aperture radar imagery," Canadian Conference on Electrical and Computer Engineering, Toronto, Canada, 2014.

24. Farr, T. G., et al., "The shuttle radar topography mission," Reviews of Geophysics, Vol. 45, No. 2, RG2004, 2007.

25. Lee, J. and E. Pottier, Polarimetric SAR Radar Imaging: From Basic to Applications, CRC Press, Taylor & Francis Group, 2009.
doi:10.1201/9781420054989

26. Friedl, M. A. and C. E. Brodley, "Decision tree classification of land cover from remotely sensed data," Remote Sensing of Environment, Vol. 61, 399-409, 1997.
doi:10.1016/S0034-4257(97)00049-7

27. Simard, M., S. S. Saatchi, and G. D. Grandi, "The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest," IEEE Transactions on Geoscience and Remote Sensing, Vol. 38, No. 5, 2310-2321, 2000.
doi:10.1109/36.868888

28. Simard, M., G. D. Grandi, S. Saatchi, and P. Mayaux, "Mapping tropical coastal vegetation using JERS-1 and ERS-1 radar data with a decision tree classifier," International Journal of Remote Sensing, Vol. 23, No. 7, 1461-1474, 2002.
doi:10.1080/01431160110092984

29. Cumming, I. G. and J. J. Van Zyl, "Feature utility in polarimetric radar image classification," Proceeding IEEE International Geoscience and Remote Sensing Symposium, 1841-1846, 1989.

30. Chen, J., H. Lin, and Z. Pei, "Application of ENVISAT ASAR data in mapping rice crop growth in southern China," IEEE Geoscience and Remote Sensing Letters, Vol. 4, No. 3, 431-435, 2007.
doi:10.1109/LGRS.2007.896996

31. Congalton, R. G., "A review of accessing the accuracy of classifications of remotely sensed data," Remote Sensing Environment, Vol. 37, 35-46, 1991.
doi:10.1016/0034-4257(91)90048-B

32. Viera, J. A. and J. M. Garrett, "Understanding interobserver agreement: The kappa statistic," Family Medicine, Vol. 37, No. 5, 360-363, 2005.


© Copyright 2010 EMW Publishing. All Rights Reserved