Surface Area Classification Using Sentinel-1 SAR Backscattering Coefficients
Surface Area Classification Using Sentinel1 SAR Backscattering Coefficients
|© 2021 by IJETT Journal|
|Year of Publication : 2021|
|Authors : Prachi Kaushik, Suraiya Jabin
|DOI : 10.14445/22315381/IJETT-V69I12P206|
How to Cite?
Prachi Kaushik, Suraiya Jabin, "Surface Area Classification Using Sentinel1 SAR Backscattering Coefficients," International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 39-46, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I12P206
The Sentinel-1 synthetic aperture radar satellite captures high-resolution images of land and sea. The land cover classification of the earth`s surface can be done by analyzing the backscatter values recorded by the sensor. The images are calibrated to convert the digital number of each pixel into backscattering coefficients. For this study, the co-polarized and cross-polarized bands for the land cover classes were collected for the test area of Bhiwani. This enables the mathematical analysis of the bands to study the dependency of the coefficients for different land cover categories. There is a significant difference between the backscatter coefficients for the categories viz. apartments, villages, low-rise buildings, forests, parks, agricultural land, and water. Statistical analysis is done to study the level of correlation between class categories. Apartments and urban areas show a strong positive correlation of 0.992, indicating that apartments are strongly related to urban areas. A weak positive correlation of 0.288 between apartments and villages indicates that apartment-like structures are less likely in rural areas. Further, a few classification models for surface area classification were trained in seven categories, out of which ensemble bagged trees model performed with an accuracy of 95.3 percent on the test data.
backscatter, SAR, Cubic SVM, ensemble, calibration, MATLAB
 Abdikan, S., Sekertekin, A., Ustunern, M., Sanli, F.B. and Nasirzadehdizaji, R., Backscatter analysis using multi-temporal sentinel-1 sar data for crop growth of maize in Konya basin, turkey. Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci, 42 (2018) 9-13.
 Vreugdenhil, M., Wagner, W., Bauer-Marschallinger, B., Pfeil, I., Teubner, I., Rüdiger, C. and Strauss, P., Sensitivity of Sentinel-1 backscatter to vegetation dynamics: An Austrian case study. Remote Sensing, 10(9) (2018) 1396.
 Paloscia, S.; Macelloni, G. Pampaloni, P. The relations between backscattering coefficient and biomass of narrow and wide leaf crops. In Proceedings of the 1998 IEEE International Geoscience and Remote Sensing Symposium Proceedings, Seattle, WA, USA, 6–10 July 1998; 1 (1998) 100–102.
 F. T. Ulaby, K. Sarabandi, K. C. McDonald, M. Whitt, and M. C. Dobson, Michigan microwave canopy scattering model Int. J. Remote Sensing, 11(7) (1990) 1223–1253.
 C. Dobson, F. Ulaby, T. Le Toan, A. Beaudoin, E. Kasiscke, and N. Christensen, A dependence of radar backscatter on coniferous forest biomass, IEEE Trans. Geosci. Remote Sensing, 30 (1992) 412–415. Jan. 1992
 P. Ferrazzoli and L. Guerriero, Radar sensitivity to tree geometry and woody volume: A model analysis, IEEE Trans. Geosci. Remote Sensing, 33 (1997) 360–371.
 Koppel, K., Zalite, K., Voormansik, K. and Jagdhuber, T., Sensitivity of Sentinel-1 backscatter to characteristics of buildings. International Journal of Remote Sensing, 38(22) (2017) 6298-6318.
 Dong, Y., B. Forster, and C. Ticehurst., Radar Backscatter Analysis for Urban Environments. International Journal of Remote Sensing 18 (6) (1997) 1351–1364. doi:10.1080/014311697218467.
 Charlton, M.B. and White, K., 2006. Sensitivity of radar backscatter to desert surface roughness. International Journal of Remote Sensing, 27(8) (2006) 1641-1659.
 Nasirzadehdizaji, R.; Balik Sanli, F.; Abdikan, S.; Cakir, Z.; Sekertekin, A.; Ustuner, M. Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage. Appl. Sci. , 9 (2019) 655.
 Kaushik, P., & Jabin, S., Deforestation Mapping Using MODIS Tree Cover Mask and Sentinel-1 Images. In Micro-Electronics and Telecommunication Engineering, (2021) 73-80. Springer, Singapore.
 Kaushik, P., & Jabin, S. (2018, December). A Comparative study of pre-processing techniques of SAR images. In 2018 4th International Conference on Computing Communication and Automation (ICCCA) (2018) 1-4. IEEE.
 Kaushik,P., & Jabin, S.(2021, August). A study of Surface Area Classification of Bhiwani area using Sentinel-1 Images. In International Journal of Scientific Research (IJSR), (2021)
 (2020) Copernicus Open Access Hub [Online]. Available: https://scihub.copernicus.eu/
 (2020) European Space Agency STEP: Science toolbox exploitation Platform [Online]. Available: https://step.esa.int/main/toolboxes/snap/
 (2020) Pearson`s correlation coefficient [Online]. Available: https://www.oxfordreference.com/view/10.1093/oi/authority.20110803100313153
 Constantino-Recillas, D. E., Arizmendi-Vasconcelos, E., Monsiváis-Huertero, A., Jiménez-Escalona, J. C., Torres-Gómez, A. C., De La Rosa-Montero, I. E., ... & Judge, J., Understanding the Backscattering from Sentinel-1 Over a Growing Season of Corn in Central Mexico Using the Thexmex Datasets. In IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium (2020) 4526-4529. IEEE.
 Modanesi, S., Massari, C., Gruber, A., Lievens, H., Tarpanelli, A., Morbidelli, R., & De Lannoy, G. J., Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land. Hydrology and Earth System Sciences Discussions, (2021) 1-39.
 He, Z., Li, S., Deng, Y., Zhai, P., & Hu, Y. (2021, July). Rice Paddy Fields Identification Based on Backscatter Features of Quad-Pol RADARSAT-2 Data and Simple Decision Tree Method. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, (2021) 6765-6768. IEEE.
 Delgado Blasco, J. M., Fitrzyk, M., Patruno, J., Ruiz-Armenteros, A. M., & Marconcini, M., Effects on the double bounce detection in urban areas based on SAR polarimetric characteristics. Remote Sensing, 12(7) (2020) 1187.
 S.V.Hwan, Dr. Eun-Kyung JO., Survey of Land Use and Land Cover Change Detection using Remote Sensing. IJETT International Journal of Geoinformatics and Geological Science, 1(2) (2014) 5-9.
 F. Lalbiakmawia., Ground Water Quality Mapping of Kolasib District, Mizoram, India Using Geo-Spatial Technology. IJETT International Journal of Geoinformatics and Geological Science 2(2) (2015) 1-7.
 S.Anandharaj, Dr.C.Sulaxna sharma., Urbanization in India by using Remote sensing and GIS techniques. IJETT International Journal of Geoinformatics and Geological Science 3(2) (2016) 1-5.