Mapping land cover using multi-temporal sentinel-1a data: A case study in Hanoi

Le Minh Hang, Vu Van Truong, Nguyen Dinh Duong, Tran Anh Tuan


Land cover mapping is one of the most important applications of both optical and microwave remote sensing. The optical remote sensing recognizes land cover objects using spectral reflectance of the material constituting the land cover. The microwave remote sensing recognizes ground objects using backscatter, of which the intensity depends on the roughness of the ground’s surface. Therefore, the multi temporal SAR images owning a lot of phenology information of land cover are the potential ideal data source for land cover mapping, in particular in the urban area. In this article, the authors present a new approach to the classification of land cover by using multi-temporal Sentinel-1A data. The experience data are single-pole (VV) in Interferometric Wide Swath mode (IW) collected from December 2014 to October 2015 along descending orbit over Hanoi, Vietnam. Decision tree method is applied base on analyzing threshold of standard deviation, mean backscatter value of land cover patterns, and combining double-crop rice classification image. The double-crop rice image is classified by rice phenology using multi-temporal Sentinel-1A images. The threshold in decision tree method is analyzed by field surveying data. The resulting classified image has been assessed using the test points in high-resolution images of Google Earth and field data. The accuracy of proposed method achieved 84.7%.


Abdalla M. Faid, Abdulaziz M., 2012. Monitoring land-use change associated land developement using multitemporal Landsat data and geoinformatics in Kom Ombo area, South Egypt. International Journal of Remote Sensing, 33, 7024-7046.

Abdikan S. et al., 2016. Land cover mapping using Sentinel-1 SAR data. XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic, 757-761.

Björn Waske, Matthias Braun, 2009. Classifier ensembles for land cover mapping using multitemporal SAR imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 64, 450-457.

Daniel Sabel, Zoltan Bartalis, Wolfgang Wagner, Marcela Doubkova, Jean-Pierre Klein., 2012. Development of a Global Backscatter Model in support to the Sentinel-1 mission design. Remote Sensing of Environment, 120, 102-112.

Heiko Balzter et al., 2015. Mapping CORINE Land Cover from Sentinel-1A SAR and SRTM Digital Elevation Model data using Random Forest. Remote Sensing, 14876-14898.

James R.Anderson, E. E., 1976. A land use and land cover classification system for use with remote sensor data. Washington: Geological Survey,
vol. 964.

Lambin E.F., Baulies X., Bockstael N., Fischer G., Krug T., Leemans R., Moran E.F., Rindfuss R.R., Sato Y., Skole D., Turner B.L. II, Vogel C., 1999. Land-Use and Land-Cover Change (LUCC) Implementation Strategy; IGBP Report No. 48/IHDP Report No 10. Sweden. International Geosphere-Biosphere Programme (IGBP), Stockholm.

Li J., Lewis J., Rowland J., Tappan G., Tieszen L.L., 2004. Evaluation of land performance in Senegal using multi-temporal NDVI and rainfall series. J. Arid Environ, 59, 463-480.

Lupo F., Linderman M., Vanacker V. Bartholomé E., Lambin E.F., 2007. Categorization of land-cover change processes based on phenological indicators extracted from time series of vegetation index data. International Journal Remote sensing, 28, 2469-2483.

Myneni R.B., Hall F.G., Sellers P.J., Marshak A.L., 1995. The interpretation of spectral vegetation indexes. IEEE Trans. Geosci. Remote Sensing, 53, 481-486.

Nguyen Ba Duy, Kersten Clauss Senmao Cao, Vahid Naeimi, Claudia Kuenzer, Wolfgang Wagner, 2015. Mapping Rice Seasonality in the Mekong Delta with Multi-Year EnviSat ASAR WSM Data. Remote Sensing, 7, 15868-15893.

Nguyen Dinh Duong, Anh Le Van, Thu Ho Le, 2014. Interpretation of land cover using spectral modulation pattern an example with Landsat 8 OLI image. Vietnam Journal of Earth Sciences, 36, 480-488.

Online, E. S., 2016. ESA EO Missions. Retrieved 2000, from Sentinel-1:

Online E.S., 2016. SENTINEL-1 SAR User Guide Introduction. Retrieved 2000, from Overview:

Thiel C., Cartus O., Eckardt R., Richter N., Thiel C., Schmullius C., 2009. Analysis of multitemporal land observation at C-band. In Proceedings of the 2009 IEEE International Geoscience, doi:10.1109/IGARSS.2009.5417764.

Wagner W., Sabel D., Doubkova M., Hornacek M., Schlaffer S., Bartsch A., 2012. Prospects of Sentinel-1 for land applications. In Geoscience and Remote Sensing Symposium (IGARSS), IEEE International. IEEE, 1741-1744.

Yuan Z, Cuizhen Wang, Jiaping Wu, Jiaguo Qi, William A. Salas, 2009. Mapping paddy rice with multitemporal ALOS/PALSAR imagery in southeast China. International Journal of Remote Sensing, 30 (23), 6301-6315.

Zhiyuan Pei, Songling Zhang, Lin Guo, Heather McNairn, Jiali Shang & Xianfeng Jiao., 2011. Rice identification and change detection using TerraSAR-X data. Canadian Journal of Remote Sensing, 37, 151-156.



Multi-temporal SAR images, land cover, Sentinel-1A, decision tree classification


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